Blockchain at Berkeley is the first university-based eco-system for blockchain technology, specializing in educating the community, facilitating innovative projects and discussion, and helping companies benefit from blockchain technology by identifying use cases, building out prototypes, and integrating solutions.
“Those who rule data will rule the entire world… That’s what people of the future will say.” — Masayoshi Son³. If we agree on this premise, the question becomes, who do you want to own this data? Do you want this data to be ruled by corporations or do you want to have ownership and control over your own data?
As our lives become increasingly digital, our digital identities are comprised of the series of digital footprints (data points) we leave behind. As a result, digital identity is inextricably tied to data. The following post will outline how blockchain technology can prevent unintended access to this data through minimal disclosure models and monetizable data ownership as well as highlight some of the techniques being employed to ensure more secure data exchange.In light of the advancement of technologies that rely heavily upon our data, it is increasingly important to protect and own our digital identity, arguably one of our most valuable assets.
Note: This is by no means a comprehensive list of digital identity initiatives in the blockchain industry, instead it is a high-level overview illustrating some of the ways that blockchain technology is relevant to the digital identity discussion and highlights select projects that are working on critical components thereof.
In a Digital World, Data = Identity
Identity can be broken down into two distinct aspects. The first is “the fact of being who or what a person or thing is⁵.” My earlier post, The Impact of Digital Identity, focused on the ways in which blockchain technology can be used to create a decentralized personal identity tied to a unique and verifiable “digital fingerprint.” The post that follows will focus mainly on the second aspect of identity, which can be defined as “the characteristics determining who or what a person or thing is⁵.”
We leave digital footprints everywhere we go. Advancements in voice technology and the corresponding proliferation of in-home devices mean data collection is no longer restricted to our online lives. All of our steps can be pieced together to create an accurate picture of what we do, what we like, who we talk to, what we spend money on, and as a result, who we are.
I won’t go into the prevalence of large-scale data breaches or the role user data plays in the business models of many “free” and widely used Internet services. Suffice it to say that we have lost control of our data, and as a result, we have little control over this component of our digital identity.
Why it Matters: Unintended Access and Unintended Inferences
Supreme Court Justice Louis Brandeis perhaps most aptly described the historical view towards privacy as “the right to be let alone.” Now privacy would be better described as “the ability to control data we cannot stop generating.¹” More importantly, as we generate more and more data each day, this data now gives rise to “inferences that we can’t predict.¹” Quite simply, we do not understand the extent to which our data is being collected, with whom it is being shared, or the ways in which it is being utilized to derive insights about our identity. Sometimes our data is used in non-obvious ways. For example, machine learning can be applied to Google searches to draw inferences related to health and language patterns can be detected in anonymously written text / code to infer authorship, among countless other examples.
Even if we have come to accept that our data is for sale, the purpose for which it is being “purchased” is not often clear.
Traditionally, security and privacy have been two distinct fields where security involved the safeguarding of data and privacy involved the protection of user identity. As data is now a primary component of digital identity, the two have blended and more emphasis is being placed on privacy, which has historically taken a back seat to more pressing security concerns. In other words, in a world where prolific machine learning applications raise concerns about unintended inferences, protection against unintended access to data becomes a heightened priority¹.
Governments have taken notice and have begun to implement data privacy regulation (Europe’s GDPR, for example.) However, data privacy regulations will likely be ineffective as our ability to meaningfully consent to data collection is diminished in an environment where unintended usage and unintended inferences impair our ability to value access to our data¹.
This doesn’t mean that users or organizations shouldn’t share their data. Keeping data private doesn’t mean data has to be kept in silos, the real issue is unintended access.
Blockchain technology can help by facilitating models that allow for minimal disclosure of sensitive information and mechanisms through which data owners can be commensurately compensated for allowing access. Privacy-focused blockchains can also allow for a more secure way to exchange information.
Minimal Disclosure Models
Users repeatedly disclose non-relevant but sensitive information when transacting online. For example, if a company needs to prove that Alice is old enough to rent a car, the rental car company might ask Alice for a copy of her driver’s license, which contains her address, her driver’s license number, and other demographic information in addition to her date of birth, which she might not want to share. The rental car company really only needs to know that she is old enough to rent a car, they don’t need to know that she is 5’6’’ and lives on Center St. They don’t even need to know her exact birthdate, they just need to know that she is above a certain age. Repeatedly sharing unnecessary information with multiple parties creates more points of vulnerability. Minimal disclosure models leverage blockchain technology to create systems in which relevant data is disclosed to querying parties, while non-relevant data is kept private, greatly reducing the transmission of and number of parties storing sensitive identifying information.
Civichas developed one such minimal disclosure model, focused on utilizing certificate authorities to create a “re-usable KYC.” Civic has created a system in which previously audited PII (personally identifying information) can be used to assure third parties of a person’s identity without the need to re-share the underlying PII. Using the example from above, with Civic, Alice only has to go through the KYC process once, and then the entity that verified her KYC (this step unfortunately still requires standard forms of ID) can provide attestations that Alice’s PII meets certain criteria. More specifically, the verifying entity can provide an attestation to the car rental company that Alice is above the minimum age required to rent a car without revealing any additional information about Alice. The Civic token (CVC) is used to incentivize third-party validators to provide attestations and can also be used to purchase “identity-related products” such as secure login / registration, multi-factor authentication, etc.
Just as sharing the same sensitive data with multiple parties creates vulnerabilities, using the same user ID and password across multiple platforms is not only bad policy from a security standpoint but can lead to association and tracking of accounts. With this in mind, Microsoft has designed its own minimal disclosure model targeted at authentication.
Microsoft has designed an open source, interoperable Layer 2 DID implementation in which a user creates a DID which is then linked to non-PII data. A user’s actual identity data (PII) resides encrypted off-chain and under control of the user. DIDs are user-generated and not limited to one per account since the idea is to avoid having one set of log-in credentials that can be traced and tracked across multiple platforms or service providers. DIDs can either be public (when you want an interaction linked to you in a way that can be verified by others) or pairwise (in the event that privacy is important and therefore interactions need to be isolated and correlation prevented.)
To walk through a concrete example, lets say that Alice wants to authenticate with an external party. Alice would disclose a DID to that party, and that party would look up the disclosed DID through the Universal Resolver, which would then return the matching non-PII metadata corresponding to that DID. The external party then creates a “challenge” using the public key references in the metadata and performs a “handshake” with Alice, proving that Alice is the owner of the DID. To prevent creation of “false identities,” attestations may be required initially until a level of credibility is established through multiple attestations or endorsements. Organizations requesting authentication can require multiple attestations for higher stake interactions.
Coinbase is also focused on identity, running a dedicated team focused on the topic and recently acquiring Distributed Systems, a company focused on decentralized identity. The company seems to be focused on minimal disclosure, in addition to other aspects of identity, as the company highlighted how decentralized identity could let a user prove that they have a relationship with the Social Security Administration without producing an actual copy of their SSN. While the social security administration and the DMV are currently the strongest purveyors of identity in the U.S., as the world becomes increasingly digital, Coinbase believes this model may ultimately extend to social media posts, photos, and other components of one’s digital identity.
Monetizatable Data Ownership
While minimal disclosure models focus mainly on protecting personal identifiers (SSN, DOB, and other PII), the non-PII data points that comprise a users’ online identity also need to be protected. If users could own their own data, and control access to it, the value of this data would theoretically accrue to its owner rather than the platforms that currently collect it (Google, Facebook, Amazon.) Governments have acknowledged that “data has value, and it belongs to you” with California Governor Gavin proposing a “digital dividend” that allows consumers to share in the profits of tech companies that have been “collecting, curating and monetizing” their users’ personal data⁶. However, this approach doesn’t allow for commensurate compensation and equates to little more than a tax on Big Tech companies, evenly distributed to individuals. Instead, blockchain technology allows for a more dynamic system in which users control their own data and can directly monetize access to that data, commensurate to the level of access they choose to provide.
There are several blockchain companies, in various stages of usage and development, that aim to create marketplaces for users to monetize their own data. BAT is an example of one such platform. BAT stands for Basic Attention Token and is an ERC-20 token that serves as a utility token traded between advertisers, publishers, and users within a blockchain-based digital advertising platform. In the system, advertisers grant publishers BATs based on the measured attention of users. Users also receive BATs for participating and they can choose to donate them back to publishers or use them within the platform. In the future, advertisers could participate in a system where a user receives one BAT in exchange for being served one ad. Zinc is another blockchain-based platform with a similar goal. Likewise, Vetri is a blockchain-based data marketplace through which users can sell anonymized data to marketers in exchange for VLD tokens that can be used to purchase gift cards within the platform.
Source: Basic Attention Token
Other examples of such marketplaces include Fysical and Steemit. Fysical is creating a platform for the exchange of location data and currently publishes over 15 billion data points from more than 10,000,000 mobile devices every month, according to the company. Steemit is a platform that allows users to monetize Reddit-style, user generated content by earning tokens when their contributions get upvoted.
Unintended access to data can also occur during data exchange, even when that data is anonymized. This is problematic since data exchange is necessary for continued innovation. Sharing medical and genomic data across medical institutions could accelerate the discovery of new treatments, conducting data analytics across financial institutions could avert financial crises, and sharing of driving data is likely imperative to the development of autonomous vehicles⁷. While blockchain technology can facilitate the exchange of data between untrusting parties, this data exchange still remains susceptible to privacy issues. Luckily, there are several blockchain companies focused on building privacy-focused networks from the ground up so that data can be exchanged in a way that prevents unintended access to underlying identifiers.
Oasis Labs is one such company. Oasis Labs is taking a full-stack approach to privacy, utilizing trusted execution environments (secure enclaves), secure multi-party computation, zero-knowledge proofs, and differential privacy. This limits the parties that have access to data at the protocol layer and limits data leakage of anonymized data at the application layer. Enigma is another project focused on creating a scalable privacy protocol, utilizing similar privacy techniques.
Ownership Rights: While the idea of an individual controlling access to, and thereby monetizing, their own data sounds appealing, in practice it can be challenging. One issue with creating a marketplace for the exchange of individual data is that data property rights have yet to be defined. Once data is shared with a third-party it is very difficult to define ownership and to prevent a secondary market for this information from forming once the information is known.
Valuation and Willingness to Pay: It will also be difficult to determine the value of different data or the willingness to pay for privacy initially, especially since users have been giving their data away, practically for free, for years. Furthermore, it is unclear if the $/month an individual might make from personal data monetization will be enough for the average consumer to offset the current user experience friction (key management, etc.) and uncertainties.
Recourse: Recourse in the case of abuses is also unclear in decentralized data exchange. In a recent video interview, Mark Zuckerberg spoke about researching ways to replace Facebook Connect, the social media giant’s single sign-on (SSO) application, with a more distributed system. However, he also posed some of the same questions raised above, asking “The question is, do you really want that? Do you have more cases where, yes, people would be able to not have an intermediary but there’d be more instances of abuse and recourse would be much harder?”
Still, the need to securely exchange data in certain industries is imperative to the viability of the business (autonomous driving, for example) and therefore the value proposition to enterprises is more likely to be high enough to offset any pain points in user experience and/or more active management.
Now that identities are digital, identity is inextricably tied to data. In light of the advancement of technologies that rely heavily upon this data, it is increasingly important to protect and own the data that comprises our digital identity. We need blockchain technology to help us regain control of our data, and as a result our digital identity, and this is more important now than ever as unintended access can lead to unforeseen consequences. Society reflects the tech we build it on…. we need to keep building.
How to not lose your crypto with novel cryptography.
By: Leland Lee (Independent) and Dev Ojha (UC Berkeley / ex Tendermint)
Figure: Sometimes we need multiple signatures to get things done
It is ironic how some multi billion dollar cryptocurrencies do not natively support multisignature. Where m-of-n signers are required to authorized a transaction. We’re not ones to judge because maybe it’s by design to only have one private key. But that is not the world that we want to live in, because who wants to lose millions of dollars due to a faulty smart contracts or lost private keys?
Today we will examine various multisignature schemes for transaction signing in blockchains that are applicable to both UTXO and account based models. Please note that some of schemes are still being actively researched and that there are multiple constructions with differing attributes (communication over head, signing time, etc). And if there’s too much technical content jump to the trade off space section.
In the status quo, existing blockchains have pursued several different systems to have multiple owners control the same set of coins: smart contract based (Ethereum) to native scripts (BTC’s P2SH).
In order to send a valid transaction on any blockchain several steps must be taken.
Construction a valid transaction
Sign the transaction with the corresponding private key of the account or UTXO
Submit the signed transaction to network
A miner verifies the transaction and signature
The transaction is placed into a block and relevant blockchain state is updated.
Non Cryptographic Techniques and Their IssuesSmart Contracts
Although smart contract based multi signature accounts offer much flexibility (daily allowances, infinite customization) they historically have suffer from bugs in both the code, language, virtual machine and compiler. Hundreds of millions have been locked up in perpetuity due to human related errors.
Unlike smart contract platforms, Bitcoin has a more primitive scripting language. The differences are stark: not Turing complete, not compiled, no virtual machine and no concept of “state”. Whether this makes the cryptocurrency less useful is a debate to be held elsewhere. But more importantly there are specific op_codes for operations such as multisignature. In Bitcoin and Bitcoin related forks, there is a special script known as Pay-to-Script-Hash which is used to create multisignature accounts. An in depth explanation can be found here.
Both Bitcoin’s multisignature addresses and Ethereum’s multisignature wallets require on chain submission of all relevant signature for a transaction to be sent. Some of the schemes we will explore today only require one signature to be submitted, saving valuable onchain space and potentially making the address indistinguishable from single private key addresses.
Here we explore various techniques to add multisignature to blockchain protocols. None of these are the silver bullet, as each method has various trade offs that need to be explored thoroughly before determining which technique is optimal for particular situations.
Note depending on what lense we apply to these class of cryptographic constructions they all look the same from high up enough, we’ve taken a distinct balance to highlight some of the key technical differences without diving to far into the technical weeds.
Shamir’s Secret Sharing (SSS)
Note this is not a multisig in a classical sense, nonetheless it is discussed here to provide a counterexample to other forms of cryptographic multisignature.
Here a private key is used to derive n shards, where m are required to reconstruct the private key. This scheme is often used for key recovery, if a user loses the private key it is possible to to reconstruct the original key using the shards the user has distributed to various friends. However it is not apt for multi signature as:
The private key must be generated to derive the shards.
The private key must be reassembled from the shards before a transaction can be signed.
Nonetheless there are some unique features of SSS that should be noted, it is possible to create as many distinct set of shares without modifying the underlying secret / private key. Thus if Alice originally has 10 secrets and unfriends Bob, a secret holder, Alice can regenerate 9 secrets and give it to the remaining trusted parties (who hopefully destroy their old shares, rendering Bob’s share useless).
There are some libraries out in the wild for Bitcoin (SplitKey) and Ethereum, however they function as key recovery systems.
In threshold ECDSA, we remove the vulnerability of Shamir’s where there is a preimage / existing private key. Here we describe a recent construction pioneered by Steven Goldfeder in his ECDSA MPC paper, which surpasses previous ECDSA work in terms of efficiency for both the key generation and signing.
Using a distributed key generation (DKG) scheme, all key holders participate in an interactive process that generates both a private key for themselves and a single public key. This ensures that no party ever learns the true private key. Before this construction key generation would only be practical using a trusted dealer as the computation time would be too great for parties greater than two.
An issue with ECDSA is that due to the intricacies of the signing algorithm, threshold signatures are complex. However for other signatures schemes such as EdDSA (Edwards-curve Digital Signature Algorithm), and particularly with curve Edwards25519 whose signature scheme Ed25519 has relatively more efficient and straightforward threshold signatures. Users generate their own keys and then have an aggregation step to create a single public key and transaction signing has a three round interactive protocol.
Kzen Networks has implemented a reference library for Ed25519 threshold signatures; Stellar, Near Protocol and Cosmos use the same curve but do not to implement cryptographic threshold signatures.
In Bitcoin, Schnorr signatures are a form of signature aggregation. Instead of using P2SH which grows linearly to the number of keys, signature aggregation allows for constant size signatures. And the verifier does not need to know the individual public keys of the signers, increasing privacy. Blockstream is helping pioneer this technique in Bitcoin.
There are several ways to implement m-of-n multisignature in Schnorr (section 5.3) with various trade offs, in some schemes users provide their own keys, whereas in others there must be a DKG ceremony. In general there is at least one round of communication for key generation and transaction signing, transaction signing also does not scale well with large a large m or n.
Short for Bohen-Lynn-Shacham signatures, they work very well for large signature sets. Meaning we can have a 2 of 10 or 2 of 1000 multisignature scheme with barely any difference in set up and signing times. For the setup phase the only thing necessary to do is generation of membership keys for each private key, this only requires one round of communication. Because users supply their own private keys it is possible to use techniques such as HD Derivation for easy management of multiple keys. Users sign transactions offline and a single aggregator adds up the signatures and submits it.
This particular construction using membership keys is fairly new, another method is to leverage Shamir’s Secret Sharing (used by Dfinity and Dash) however either a trusted dealer or a DKG is necessary. A downside of BLS lies in the weeds, where finding an optimal pairing is inefficient, meaning signature verification is slow, a magnitude slower than ECDSA. Dive deep into BLS here.
Trade off space
When observing these techniques from a distance it seems that some on paper are superior to others. Unfortunately that is not the case when we dive into the trade off space. Some techniques are preferable for larger groups of signers, others more apt for low bandwidth environments. Here we explore a non exhaustive list of attributes to analyze the various techniques from above.
Preimage: Is there a private key that must be split?
Trusted Setup: Is there a single entity that generates the keys or can there be a distributed key generation scheme?
Detect Multisig: Can a viewer of the blockchain determine whether a particular address is a multisignature address?
HD Derivation: Is it possible to have hardware deterministic keys for the associated cryptographic process? (Can users use techniques like BIP32 so they only need to remember their seed rather than a bunch of private keys)
Weight: Is it possible to assign different weights to particular private keys? (ex: 1 of 2 multisig, where key holder A has a weight of 2 and key holder B has a weight of 1, meaning A does not need B to sign but B always requires A).
Privacy of Signers: Can a viewer of the blockchain determine who were the particular signers of a transaction
Signature size: Do multi signature transactions require more on chain space, does the amount of space vary depending the number of signers?
Key generation time: How long does it take to generate the keys, does key generation time increase based on the number of parties?
Key generation rounds: If key generation is interactive, how many times do participants need to interact with each other.
Verification time: How long does it take to verify a signature
Signing time: How long does it take to sign a transaction
Interactive: How many rounds of communication are required to sign a transaction
Curve Efficiencies: Even though some of these techniques work for all curves it is necessary to consider things such as curve efficiencies and cofactor selection.
Figure: The trade off space for the schemes discussed, note that there are several constructions for each scheme which leads to different attributes.Future Developments
Although there are many different techniques that enable multisignature accounts for blockchains we must be cognizant of the design considerations in a protocol. Some of these techniques require changes to the underlying protocols, while others do not. Protocol designers should be aware of the implicit trade offs in both user experience and future proofing for advance in cryptography.
Now that you know more about cryptographic multisignatures here are some questions to ask yourself when deciding what kind of signatures scheme you should choose when implementing a protocol.
Are there use cases where one wants to be able to differentiate between multisignature and single signature accounts on chain.
Threshold cryptography provides the property where the individual key signers are unknown, where can this be beneficial or detrimental?
Is it possible to have a signature scheme that allows for selective disclosure, where some transactions reveal the signers and other transactions do not?
Is it possible to have a signature scheme that can reveal only a subset of the signers but not all?
Is it possible to have a scheme where the signing parties are not able to determine who are the other signers in the interactive step?
How does key management work when it is not possible to have HD wallets?
For BLS one can use HD keys, however it is necessary to generate additional membership keys. What should protocol be when the user loses their membership key?
Should multisig lie entirely in the cryptographic realm or should one there be a balance between smart contracts / scripts and cryptography
Are there instances where signature size does not matter at all because signature are tossed or there is a novel form of compression?
 Technically all blockchains do have a form of native multisignature assuming there are cryptographic signatures. However finding an efficient threshold signature scheme for any arbitrary signature algorithm can be rather difficult.
 Grin unique among cryptocurrencies to use a cryptography based multisignature, it is similar to Bitcoin’s confidential transactions. A downside of their approach is that it is custom to their protocol and hard to generalize.
 Monero only supports n-of-n and n-1-of-n schemes, the former being very similar to a splitkey.
 Stellar has multisignature but does not implement it in cryptography, instead it is achieved by using their scripting language.
 Note for UTXO models there is a one time interactive step for the generating the public key which is necessary for the unlocking script when users want to spend.
Thanks to Tarun Chitra, Joyce Yang, Dan Robinson, Jeremy Rubin, Jeremiah Andrews and countless others for review and explanations of various cryptographic techniques.
What could distributed ledger technology mean for unbanked and underbanked populations? In particular, how might distributed ledger technology revolutionize the Microfinance industry? Is the Microfinance industry even in need of change?
These are questions that I’ve been asking myself repeatedly over the last 18 months. Rather than sit in my bedroom and ponder, I decided to spend a few months doing some research. I interviewed a selection of modern-day Microfinance institutions (MDMFIs) that have, in recent years, issued a combined $750m in micro loans to over 4.5m customers in emerging economies across the globe. First, I assessed MDMFI performance and impact. Second, I examined how Blockchain technology could increase the scope of impact of MDMFIs. Third, I explored the key challenges to Blockchain adoption.
Summary of Key FindingsPerformance and impact
MDMFIs have shown that they are adept at using mobile phone data to draw signals and inferences about the behaviors that drive loan repayment. They have achieved, on average, repayment rates of over 90%, and their loan acceptance rates of 50% are significantly higher than those of traditional financial institutions.
With loan decisions made in mere minutes, MDMFIs algorithmic data driven approaches have acted as a catalyst for greater financial inclusion, allowing millions of un(der)banked individuals to grow their businesses or smooth their income streams.
Opportunities for Blockchain technology
Blockchain technology has the potential to foster growth in Microfinance and provide more effective solutions in four key areas:
offering a new and innovative way of verifying a borrower’s identity
creating shared and trusted credit histories
enabling the sharing and maintenance of sensitive data in more secure ways
allowing for cheaper and quicker flows of capital to and from borrowers.
Challenges to Blockchain adoption
Despite offering improvements to the Microfinance business model, Blockchain technologies face a number of challenges to become a viable solution. These include:
a lack of interest from relevant stakeholders and an inability to change processes due to legacy contracts and infrastructure
the infancy of the technology and the absence of integrated and interoperable solutions that can be easily incorporated into existing operational models
the significant regulatory uncertainty, particularly relating to public accessibility of sensitive data (e.g. GDPR).
BackgroundA history of the Microfinance industry and the rise of MDMFIs
Microfinance institutions (MFIs) have been around for a long time. Initially coined in 1970s following the success of the Grameen Bank of Bangladesh, the basic objective of an MFI is to enable traditionally unbanked individuals (and businesses) to obtain access to capital through the provision mini or micro loans. MFIs seek to achieve financial inclusion through developing solutions that a) seek to find innovative ways to address the challenges of nonexistent credit history, and b) build partnerships with a broad range of organizations, from governments through to non profit foundations to source and secure capital flows.
Whilst the mechanics of how micro loans are provided differ based on the relative sophistication of financial systems in different locations (e.g. traditional cash vs. mobile money vs. peer to peer lending), and the specific client base (e.g. unbanked, SMEs, social enterprises, underbanked), the essence of what a MFI does has remained unchanged for decades:
assess creditworthiness and provide capital to the underserved.
Historically, MFIs were operated as quasi-nonprofits. Backed by organizations such as the World Bank, the IMF, international foundations, in addition to national governments and global nonprofits, their main goal was to provide access to credit. There was no inherent need to generate the high Return on Investment (ROI) required by commercial credit providers because MFIs’ key funders did not hold investment returns as their primary objective. Rather, they were concerned with social good. Borrowers were sourced through intimate knowledge of local communities, using information obtained through interviews and experimentation, with limited focus on the benefits of using recordable digital data.
Over time, MFIs have innovated and become more akin to traditional profit driven providers of credit, lending at market rates of interest. Traditional MFIs are now widely accepted as having contributed significantly to global financial inclusion by serving an estimated 200m borrowers. However, MFIs face significant criticism for often charging high interest rates to borrowers, something that is widely accepted to be a consequence of an operationally heavy and labour intensive business model.
Modern-day Microfinance institutions
Modern-day MFIs (MDMFIs), in the context of this post, are MFIs that use alternative data, specifically mobile phone data from smartphones, as the underlying source and foundation of their credit solutions. MDMFIs have lower operating costs and are digitally native, allowing them to offer cheaper and more efficient credit solutions to borrowers.
It is estimated that two thirds of the world’s unbanked have mobile phones. Through the use of data generated from a device that has now become ubiquitous in both the developed and the emerging worlds, MDMFIs are able to assess creditworthiness of potential borrowers in a manner that is automatic, automated, and driven by big data.
I interviewed a number of MDMFIs, which combined, serve over 4.5m customers in emerging economies across Africa, LATAM and Asia, and have issued over $750m in loans over the last few years.
How the MDMFI model works
Whilst there are variations in the loan process depending on geography and the particular MDMFI, a simplified model of the typical customer process is as follows:
Borrower installs the MDMFI’s smartphone app. This app gives the MDMFI complete access to the borrower’s mobile phone (from call duration records through to words included in a SMS).
Borrower uploads relevant ID documents through the app. This allows the MDMFI to create a unique record under which, the mobile phone is associated to a specific borrower, and local Know-Your-Client obligations are satisfied
The MDMFI analyzes the borrowers mobile phone data and, if possible, any available credit data from local credit bureaus based on the borrowers ID, to assess credit worthiness.
Upon the borrower’s request for credit, the MDMFI uses algorithms to analyze mobile phone data in order to generate a probability of repayment score. The MDMFI then offers, within minutes, a line of credit to the borrower. This line of credit is often for 60 days or fewer and typically for less than $350.
The borrower’s repayment of the loan (or lack thereof) in addition to mobile phone usage and habits are analyzed repeatedly by the MDMFI and used to inform the MDMFI’s algorithm.
Key data points assessed
MDMFIs typically gather between 1,200 and 2,000 mobile phone data points to generate a probability of repayment score. This includes mobile phone usage data (e.g. regularity of phone usage, regularity of phone charging, times of day that the phone received SMS messages), mobile phone geosensing data (e.g. where the phone was physically used, variation on location of usage, consistently of location over time), and borrower psychometric data (e.g. how long it took borrower to complete loan application, answers on loan application etc), which are grouped and analyzed within the context of 3 main buckets:
Own data — data “controlled” by the individual borrower. This focuses on the borrower in isolation.
Inferred data — data on the social interactions and social networks that the borrower is associated with.
Relative data — data on the borrowers “metrics” relative to the rest of their cohort and relative to all other borrowers on the MDMFI’s platform.
Whilst not all of the 1,200 to 2,000 data points that comprise these three buckets have equal levels of importance, when considered in aggregate this data has predictive qualities. The core to an MDMFI’s success is an ability to use mobile phone data points to identify the particular behaviors or behavioral traits that offer the most accurate and consistent predictive signals about an individual borrowers likelihood to repay credit.
Anecdotal examples of mobile phone data that provide stronger and more robust predictive signals about a borrower’s likelihood of repaying loans, include the following:
Borrowers who include both first name and surname when saving a contact to their mobile phone address book offer higher repayment rates
Borrowers who maintain their phones fully charged for longer, offer higher repayment rates
Borrowers who have fewer gaming apps than productivity apps on their phones offer higher repayment rates
Borrowers who request credit between the morning hours of 5am — 8am, offer higher repayment rates
Traditional MFIs and banking institutions do not consider or analyze mobile phone data to this level of granular detail when assessing risk. Rather, an individual’s income, history of recorded credit repayments and residence address are determining factors.
Whilst income levels and history of recorded credit repayments are, of course, strong predictors of repayment, mobile phone data has been found to be more effective than credit bureau methods at predicting those who are more likely than not to repay funds. The assessment of the day-to-day interactions, in addition to the psychological and sociocultural context of borrowers is where MDMFIs have created a great niche. Given that mobile phone data is real time, MDMFIs can also assess quickly the impact that changes in borrower behavior are likely to indicate about the ability to repay, and adjust their credit amounts accordingly.
Progress towards meeting objectives
MDMFIs core lending businesses have been exceptionally successful using mobile data to assess a borrower’s ability and willingness to repay in a low cost manner. Given the lack of brick and mortar branches and low fixed overhead, the marginal cost of adding an additional borrower is minimal. This has allowed MDMFIs to offer loans to new and larger populations of borrowers. In particular, to individuals who operate in the informal economy, are geographically distant from traditional lending options, or cannot afford the interest rates offered by traditional MFIs.
From those MDMFIs that I spoke to, the following headline numbers were identified:
Typical MDMFI repayment rate is over 90%
More than 50% of MDMFI loan applicants receive a line of credit
Interest rates are typically materially cheaper that those from comparable payday loans or traditional MFIs
Loan approval occurs in mere minutes
These results show that commercially, the MDMFI model is working. MDMFIs are allowing a greater number of people to access credit, smooth their income and obtain cheaper working capital (through lower priced short term loans) in the process. However, they have faced many criticisms, particularly, for creating an increased dependence on debt, given the relatively low proportion of first time borrowers (typically around 7%) and high proportion of repeat borrowers (typically 90%+). This is particularly pertinent given widespread reports of individuals using loans from one MDMFI to repay loans obtained from another MDMFI.
If MDMFIs really want to deliver on their core goals of financial inclusion they will need to offer products, such as savings, investments or planning, that help borrowers think to the future.
Blockchain or Distributed Ledger (DLT) technology is, at its core:
A shared database / ledger of chronologically recorded transactions, secured by cryptography;
That is immutable and tamper-resistant, allowing users to append and record data, but not delete or edit;
With no central owner and, instead, run by a network of distributed computers, each holding a copy of the database / ledger of transactions;
Where the network reaches consensus on the true state of database / ledger through a predefined consensus mechanism.
In more simple terms, Blockchain/DLT allows the creation of a shared database held and controlled by a network of distributed computers, where data can only be added to the database, and the database’s veracity is secured by complicated cryptography.
Use cases given research observations
Based on my interviews, MDMFIs see Blockchain technology as something for the future. That being said, practical use cases for Blockchain technology based MDMFI pain points include:
Credit histories — Whilst many MDMFIs create “probability of repayment” scores based on mobile phone data and then record borrowers’ payment histories on the MDMFI’s own individual platform, this information is not publicly shared across platforms in such a way that a borrower is able to develop a global verifiable history of credit repayments.
Blockchain’s immutable ledger offers the ability for a borrower’s repayment history to be permanently recorded to a public database that all potential lenders can access. This could cover all “credit like” repayments and would enable MDMFIs to implement risk based pricing to all borrowers through the aggregation of data across providers (many MDMFIs do not currently offer risk based pricing and instead offer flat interest rates to all applicants). The credit history could be linked to a digital ID (see below) with the solution implemented in conjunction with local credit bureaus. Such a partnership with local credit bureaus would ensure that borrowers are able to eventually access the traditional financial system (both locally and internationally) using MDMFI data (i.e. using proven and verifiable evidence of debt repayment, which is what traditional credit providers require). Existing Blockchain solutions that seek to blend credit history with digital ID include The Kiva Protocol, Bloom, BanQu, and Colendi.
ID verification — A common challenge for MDMFIs is obtaining valid ID documents when seeking to identify their borrowers, particularly in locations where more than one form of ID document is issued.
Blockchain solutions such as uPort, Civic, CULedger or those developed by the UN backed ID2020 Alliance, have attempted to address this issue, either through digitizing paper based records, or creating digital passports. These decentralized digital IDs could be linked to an individual’s biometric data or unique public-private key pairing, and would be more easily transferable, sharable and accessible. This would enable to MDMFIs to onboard a greater number of borrowers more quickly and effectively.
Disbursements and collection — MDMFIs work with local payment processors and telcos to distribute and collect funds. Given that most well funded MDMFIs operate in a number of jurisdictions, funds need to be regularly moved across international borders to disburse to borrowers, leading to associated FX risks. MDFIs use the existing financial infrastructure, which is slow, does not not offer real time information and often requires nostro accounts to be held at correspondent banks when transferring money across borders.
Blockchain based payments systems such as Stellar and Ripple seek to increase the speed and information associated with cross-border payments, in addition to eliminating the need for tying up funds in nostro accounts, and reducing FX risk through the use of stable coins (digital assets pegged to the value of non-digital assets) or atomic swaps. As MDMFIs disburse increasing amounts of capital each day to borrowers, having greater control of cash in real time and reducing reliance on telcos and payment processors will become imperative to continuing to offer cheap services.
Data sharing and protection — MDMFIs obtain and share data from/with partners (e.g. Android, telcos) in order to create and develop their algorithms and improve machine learning. This requires data sharing agreements with a broad range of parties across the globe. Privacy considerations are often the main concern of companies when it comes to sharing data. Currently, this data is held in centralized servers or cloud providers (e.g. AmazonAWS, Microsoft Azure, Google Cloud).
Blockchain providers such as Enigma, Oasis Labs seek to create solutions to allow privacy-secured sharing and storage of data. This will allow MDMFIs to identify and track who has access and has accessed which pieces of data at all times, ensuring that only the relevant people have access to sensitive information.
Challenges to use cases
Whilst Blockchain technology could facilitate the scaling of MDMFIs, there are a number of challenges, both practical and technological that will need to be addressed.
Adoption — Many of the solutions require the acceptance of new blockchain based infrastructure by multiple parties. Given the diversity of stakeholders, including regulators, governments and businesses, with conflicting objectives (e.g. maximization of profits vs. improving social cohesion vs. ensuring consumer protection), wide scale adoption may be difficult to achieve.
Additionally, the technical stack required for Blockchain technology to be feasible for all day to day transactions is still a way away from being fully built out. That being said, we are now seeing companies develop blockchain based mobile phones (for example, HTC and Sirin labs) which would enable seamless integration between mobile phone data and blockchain based technologies (for example, ID verification and credit histories), albeit that these phones are way outside the price point of the average MDMFI borrower. As the cost of blockchain based smartphones decrease, adoption of the underlying technology is likely to increase.
General Data Protection Regulation (GDPR) — Blockchain technology’s core benefit is that the data stored on the chain is immutable. Once it has been recorded, it cannot be deleted. This is contrary to the rules of the GDPR, which requires that businesses can delete data sorted on their customers, if requested by customers.
To the extent that local or national governments across the board introduce similar legislation, this could create regulatory challenges when using Blockchain technology to record data.
Technological — To create a system that covers credit data, ID, payments and privacy will require Blockchain interoperability and scalability. Interoperability is the area where Blockchain technology remains most in its infancy. Therefore, until this has been resolved (organizations such as Cosmos are intending to build a solution), the technology will struggle to achieve high levels of adoption, as integration into existing MDMFI operational models remains impractical.
MDMFIs have shown that they are adept at using mobile phone data to draw signals and inferences about the behaviors that increase an individual’s likelihood to repay loans. As a result, they are able to provide cheap credit funding to millions of un(der)banked individuals who otherwise would have no reasonably priced access to the loan funding required to grow their businesses or smooth their income streams. In this way, MDMFIs are clearly continuing the work of their MFI predecessors of assessing creditworthiness and providing capital to the underserved.
A major criticism of MDMFIs is that they encourage the use of credit where it otherwise wouldn’t be required, drawing people into a cycle of debt dependency. Given that over 93% of borrowers repay loans, however, it is possible that the cycle of debt claim may be overstated.
Blockchain technology has the potential to foster MDMFI growth and provide more effective solutions to larger client bases through a) offering a new and innovative way of verifying a borrower’s identity; 2) creating shared and trusted credit histories; 3) enabling the sharing and maintenance of sensitive data in more secure ways; and 4) allowing for cheaper and quicker flows of capital, both to and from borrowers. However, challenges for the implementation of Blockchain technology are abound, particularly those relating to technological infancy, regulatory uncertainty.
Bosun Adebaki is a Business Consultant at Blockchain at Berkeley and an MBA student at UC Berkeley’s Haas School of Business. He believes in using FinTech to create a more accessible financial system.
Central Bank Digital CurrencyBosun Adebaki is a Business Consultant at Blockchain@Berkeley and an MBA student at Berkeley-Haas
A Business Consultant for Blockchain@Berkeley and a second year MBA at Haas, Bosunwill be carrying out research into the Merits of Central Bank Digital Currency (CBDC).
For a number of years, central banks have been examining the extent to which digital currencies may be used to increase competitiveness and enhance efficiency (see cases such as M-Pesa). Whilst the development of central bank use cases have increased pace in recent years, there is a lack of detailed analysis into the viability of CBDC, with particular focus on the challenges of the 2.5bn underbanked.
Bosun’s research will seek to understand and explain CBDC use cases, particularly those that focus on increasing economic inclusion for the financially underserved. It will consider the relative success of CBDC pilot studies carried out by a number of central banks across the globe, and will seek to provide clarity on the impact that CBDCs may have on existing monetary systems.
Blockchain For The Energy Sector
A first year MBA and Business Consultant for B@B, Kate will be researching applications of blockchain within the energy sector.
While working as a wind turbine engineer in China, Kate realized that current infrastructure and markets are holding back our transition to a decarbonized and decentralized energy grid. Over the last few years, a number of energy blockchain start-ups (including Electron, WePower, LO3 and PowerLedger) and increasingly, established utilities, have started investigating applications in this space, from wholesale electricity trading to EV charging and green credits.
Kate’s research will seek to evaluate these use cases, and dive deeper into the specific challenges of financial reconciliation, hardware integration and data sharing as they apply to the energy sector.
Blockchain@Berkeley Consultant, Sara, will continue to develop the reach of She(256), a movement to increase diversity and break down barriers to entry in the blockchain space that she co-founded.
Blockchain@Berkeley is the largest university-based ecosystem for blockchain technology. It drives innovation by educating the community, conducting protocol-level research, and helping companies benefit from blockchain technology by building POCs and integrating functioning solutions. Blockchain@Berkeley is comprised of 100+ diverse undergraduate and graduate students from UC Berkeley, with advisors from both industry and academia.
Left to right: Jocelyn Weber Phipps, Director, Sutardja Center, Berkeley Engineering; Ding, Tianyu, Sr. Blockchain Architect, Hyperchain; Rhonda Schrader, Exec. Director, Berkeley Haas Entrepreneurship Program; David Roebuck, Sora VC; Luke Kowalski, Co-Director Blockchain X-Lab SCET & VP, Oracle; Tess Hau, Venture Advisor; Kartik Mehrotra, Xcelerator Program Head & Head of Business Development, IOTW; Karin Bauer, Program Manager, Haas Blockchain Initiative; Gloria Zhao, President, Blockchain at Berkeley; Liam DiGregorio, Head of Business Development, Blockchain at Berkeley; Professor Ikhlaq Sidhu, Founder and Chief Scientist, Sutardja Center, Berkeley Engineering; Avneet Saini, Xcelerator lead for Blockchain at Berkeley; Chuck Ng, President & CMO, Project PAI; Sanil Rajput, Head of External, Blockchain at Berkeley; Li, Qilei CTO, Hyperchain; David Chang, Vice President of Shanghai Blockchain Association, Hyperchain Advisor, X-Fund GP
The University of California, Berkeley has just announced the formation of a new blockchain-focused accelerator, the Berkeley Blockchain Xcelerator. The new accelerator will help entrepreneurs pursue new ventures in the blockchain space, tap into the vast resources of UC Berkeley and Silicon Valley, and receive expert industry guidance to create high-value blockchain startups.
The effort was launched as a joint venture between Berkeley Engineering’s Sutardja Center for Entrepreneurship and Technology, Blockchain at Berkeley, and the Haas School of Business. This is the first initiative of its kind that brings together different groups from UC Berkeley to work toward the common cause of building a blockchain and technology ecosystem to further our mission of education and mentorship in the blockchain space.
“UC Berkeley, Silicon Valley, and the Bay Area have become the worldwide hub for the development of blockchain technology,” said Professor Ikhlaq Sidhu, founder and director of the Sutardja Center for Entrepreneurship and Technology. “Currently, there is a lot of hype in the space, but we believe that this new accelerator will give innovators the tools they need to separate hype from reality and pursue ideas that solve pressing business problems and create valuable new ventures.”
The goal of the Xcelerator will be to support early-stage projects in blockchain by providing knowledge and connections to industry experts and resources to entrepreneurs and founders.
The program application opens today for founders globally, and will typically be comprised of a 12-week accelerator experience, taking the founders through crucial elements of building a technology startup. UC Berkeley’s network of serial entrepreneurs, alumni, faculty, seasoned investors and capable students will be available as mentors and advisors for the selected portfolio companies to guide them through the program and prepare them for demo day. Portfolio companies will also receive access to office space, funding and partnership resources.
“With such a nascent technology as blockchain, we see that a lot of subject matter experts and people making an impact in the blockchain space are students,” said Gloria Zhao, president of Blockchain at Berkeley, the first and most-established student-run blockchain organization. “Blockchain at Berkeley strives to foster the entrepreneurial spirit in our students, so we are excited to help lead this initiative and assist the next generation of blockchain innovators.”
The Berkeley Blockchain Xcelerator, an educational program, has been sponsored in part with generous support from the Berkeley X-Lab Fund, a unique venture capital fund focused on making strategic investments in UC Berkeley’s blockchain ecosystem and associated emerging technology initiatives.
UC Berkeley is the world’s #1 public university and ranks as the #2 university for startups and entrepreneurs according to Pitchbook. UC Berkeley has been at the forefront of innovation in emerging technologies, such as blockchain and cryptocurrency. The SCET Blockchain X-Lab was established to provide the UC Berkeley community with technical expertise and knowledge resources to develop industry shaping projects for the blockchain space.
The Sutardja Center for Entrepreneurship & Technology is a global innovation hub headquartered at UC Berkeley’s College of Engineering, where aspiring entrepreneurs take deep dives into the world of technology entrepreneurship and embark on the path to developing exciting new ventures. The Center researches emerging technologies in its labs and offers a suite of courses and programs for students, executives, and global innovators. The Center has recently launched new labs focused on innovation in data science, artificial intelligence, blockchain, and meat alternatives. Additionally, academics from around the world visit the Center to learn about the Berkeley Method of Entrepreneurship, a unique innovation pedagogy that focuses on mindset training for innovators and entrepreneurs.
Blockchain at Berkeley is the largest university-based ecosystem for blockchain technology that drives innovation by educating the community, conducting protocol-level research, and helping companies benefit from blockchain technology by building and integrating solutions. Blockchain at Berkeley members are comprised of 100+ diverse undergraduate and graduate students from UC Berkeley, with advisors from both industry and academia. Blockchain at Berkeley has designed and taught free, popular for-credit courses about blockchain and cryptocurrencies, with over 70,000 students members signed up online. The Consultancy has trained skilled developers and consultants and built POCs for various Fortune 100 companies. The organization promotes a culture that drives innovation; members have produced various research projects, some of which have spun into startups such as FourthState, Mechanism Labs, and PartialF.
Within UC Berkeley’s Haas School of Business, the Berkeley Haas Blockchain Initiative, housed within the Institute for Business & Social Impact in collaboration with the Master of Financial Engineering Program, links to the rich array of expertise, courses, research and other activities related to blockchain, cryptocurrency, and digital payments underway across the Berkeley campus. These links include strategic collaborations with Ripple’s University Blockchain Research Initiative. Also joining this effort is the Berkeley Haas Entrepreneurship Program that integrates entrepreneurial thinking into the Haas student experience and assists students in launching new ventures.
To put it short — 2018 left a lot to be desired. Any planned trip to the moon had to be canceled and the drive back from the airfield was in an Uber. When the hype train of 2017 came to a standstill many investors felt that crypto is over. But is that really true?
To find out we crunched numbers of 178 digital asset exchanges* worldwide and arrived at the following key findings:
Fueled by a record Q1/18, 2018 global trading volumes are still twice as high as in 2017,
2018 digital asset volatilities are considerably lower than in 2017 but remain high compared to classical markets,
In Q4/18, USA’s global market share dropped below 7% and is now behind the UK and Japan; Asia now makes up 81% of the global digital asset market,
Crypto-to-Crypto trading is rising; Tether USD (USDT) trading now 2.5 times higher than USD.
US’s Market Share Dwindles
On a global level, the average digital asset trading volume more than doubled from $2.4B/day in 2017 to $5.0B/day in 2018. However, in the US, trading volume declined from $800M/day in 2017 to $750M/day in 2018.
Looking at the change from Quarter to Quarter, the picture is even grimmer for the US. In Q4/2018, the US only accounted for 7% of global digital asset trading making it the 6th biggest market in the world. The significance of this drop becomes clear when looking at Q2/17 when the US had a global market share of over 50%. This declining impact of the world’s biggest economy in global digital asset trading leaves the prices of Bitcoin and other cryptocurrencies at the mercy of non-US countries and is likely to put the remaining hopes for a quick approval of a Bitcoin ETF to rest.
While the US’s market share is dwindling, exchanges originating from China were able to increase their market share from 6% in 2017 to 22% in 2018. The world’s biggest digital asset market by volume is now Hong-Kong with a market share of 29%. South Korea, one of the former powerhouses of crypto, lost 9% of its market share from 2017 to 2018 but is showing strong signs of recovery in the last quarter of 2018.
Top10 Biggest Exchanges All Outside the US
Looking at individual exchanges, the picture looks all too familiar. Except for one exchange, HitBTC, all of the Top10 digital asset exchanges (by volume in Q4/18) are based in Asia. US’s biggest exchange Coinbase only comes in 12th. In comparison, just little over a year ago, US-based exchange Poloniex held the pole position both in Q1/17 and in Q2/17. Today, Poloniex merely comes in 31st. The full ranking across all 178 digital asset exchanges is available here.
A striking property of the ranking is the great mobility across ranks. Only one of today’s Top10 exchanges even existed at the beginning of 2017 and even in Q3/2017 only four of the Top10 exchanges reported any trading activity. Binance and OKEX are two examples of exchanges that were just founded little over a year ago and quickly rose to the very top.
Volatilities And Prices Declining
From January 1, 2018 to January 1, 2019, the prices of all major digital assets saw a dramatic decline. Bitcoin (BTC) and the relatively new EOS fared the best with a decline of “only” 65–70%. The infamous last rank holds Bitcoin Cash (BCH) with a decline of 93%. This sharp decline can be attributed to the “hash war” between Bitcoin ABC and Bitcoin SV fought in mid-November 2018. Even when accounting for the split coins, Bitcoin Cash holders still faced an annual loss of 90%. Ether (ETH), Ripple (XRP) and Ether Classic (ETC) all lost about 81% and are thus right in the middle of the pack. Privacy centered coins Monero (XMR), ZCash (ZEC) and DASH saw considerable losses ranging from -85% to -92%. Generally, smaller cap alt-coins saw a proportionally bigger loss than more established currencies such as Bitcoin signaling that investors sought safety in those currencies during the bear market.
In 2018, daily volatilities of all Top10 digital asset trended lower compared to 2017. Specifically, Q3/18 saw new all-time low volatilities for almost all digital assets. In the last quarter, volatilities saw a slight increase but are still considerably lower than in 2017. With around 3% daily volatility in Q4/18, Bitcoin (BTC) remains the most stable digital currency. Nonetheless, compared to classical markets, such as S&P 500's (1.5%), digital asset volatility remains high.
Korean Traders Most Adventurous
After a hiatus in Q3/18, trading in South Korea seems to be back in full swing and, as in previous quarters, Koreans are by far the most adventurous traders in the world. In any other reference currency, Bitcoin (BTC) is by far the most traded digital asset and Ether (ETH) comes in second with considerable distance. In Korea however, every quarter a different cryptocurrency seems to be trending. In Q4/17, Bitcoin Cash (BCH) was particularly popular, in Q1/18 the attention shifted to Ripple (XRP) and in Q2/18 EOS was able to outshine Bitcoin. In Q3/18 Korean trading slowed down but still saw EOS and XRP activity on par with Bitcoin trading. Finally, in Q4/18 Zcash (ZEC) and Monero (XMR) were en vogue.
Considering only /BTC markets reveals an interesting finding. If we were to live in a world with Bitcoin as a reference currency, then 2018 was a great year for digital asset trading with global volume increasing from ₿130k/day in Q4/17 to ₿170k/day in Q4/18.
Put differently, trading crypto for fiat (KRW, USD, EUR, JPY, GBP and RUB) is becoming increasingly unpopular. Instead, direct trading from other cryptocurrencies such as Tether USD (TUSD), BTC or ETH are on the rise.
Just one year ago, Tether USD (TUSD) played an insignificant role in global trading. However, during the course of 2018, it gained quickly in popularity. After overtaking USD for the first time in Q2/18, it never looked back. In Q4/18, TUSD was 2.5 times as popular as USD.
Frankly, 2018 was a disappointment for anyone invested in the digital asset space. Prices declined 70% or more and crushed the dream of Lambos for everyone. If HODL was the strategy for 2017, then SELL ASAP should have been the one for 2018.
When considering total trading activity, things already look considerably better. Despite the falling prices, 2018 saw a two-fold increase of global trading volume compared to 2017. After a phenomenal all-time high of trading activity in Q1/18, trading slowed down in Q2 and Q3/18 but is showing an upward trend in Q4/18.
Putting aside prices and trading, on a fundamental level, 2018 reached several important milestones towards permanent crypto adoption. The SEC clarified that neither Ether (ETH) nor Bitcoin (BTC) are securities meaning that trading them was not, it is not going to be, illegal for US investors. Google and Facebook (partially) reversed their bans on crypto-related advertising allowing legitimate blockchain companies to grow. Furthermore, crypto custody is constantly improving and, for the first time, deposits at major custodians are fully insured. Not at last because of these improvements large university endowments (Yale, Harvard, MIT and Stanford) started to invest in the digital asset space and classical brokerage firms such as BlackRock, Fidelity and Goldman Sachs are showing interest in adding crypto to their offerings.
In hindsight, it is more than clear that the hype of 2017 was unsustainable. Neither the technological nor the legal infrastructure was ready for the storm and once mass media jumped on-board to get each and everyone on the crypto ship the downfall was inevitable. As bad as this fall may have been for new investors it was a necessary and important step to gain enough attention from government, industry, media and academia to bring this technological revolution back on track to becoming a story of success.
*Data Acquisition and Data Analysis
All data has been obtained from cryptocompare, saved as an sqlite database, queried with pandas/SQL and visualized with infogram. All charts are interactive and can be customized by (un-)selecting items. When hovering over data points additional information is displayed. Selecting different tabs shows additional data sets. We excluded exchanges that reported unrealistic values.
Cover Photo: Evolution of quarterly trading volume.
Oftentimes the evolution of the blockchain industry is compared to the evolution of the Internet. This comparison is apt, and provides a guideline for the adoption curve of a transformational technology. However, the Internet is not the only industry that can provide a guideline for the pace and shape of development in the blockchain industry.
Below we take a look at a wide range of industries and the ways in which they developed to draw parallels to the blockchain industry that extend beyond the often cited comparison with the Internet.
The Pace of Industry Development
Many people believe that the blockchain industry is at a stage similar to that of the Internet in the early-to-mid nineties. This causes them to stand waiting for the development and release of a “killer app” akin to the Mosiac Browser. Some are frustrated that after ten years of existence this “killer app” for blockchain technology hasn’t yet been developed. This frustration may be mitigated by looking beyond the traditional comparison with the Internet, to the development of other transformational technologies.
Let’s look at Artificial Intelligence. As explained in the book Machine, Platform, Crowd, the industry has been evolving since the early 1960’s. Early on, the AI community split into two camps, those that believed “symbolic” or rules based AI would prevail and those that aimed to build statistical pattern recognition systems. However, repeated failures of both approaches caused an “AI winter” to all but stop the development of the technology in the 1970’s. Even still, some researchers continued to work on the problem throughout the 1980’s, building systems with back-propagation capabilities. Despite these advancements, wide spread applicability was still constrained by limited computing power and limited data.
In other words, AI wasn’t held back by lack of a “killer app”, its progression was constrained by the pace of development of complementary technologies. The popularity of video games resulted in wide spread usage / production of GPU units, which are well suited to the parallel processing required by machine learning, in the late 1990’s. The cost of computing was then driven down by Moore’s Law and the proliferation of cloud computing (AWS launched in 2006.) The proliferation of Big Data (Hadoop was created in 2005) was equally important in the development of the AI industry. It was only after these developments that AI applications became truly viable on a large scale.
Avoiding a debate about the directionality of the infrastructure — app cycle, let’s consider the possibility that, scalability and other technical issues aside, the constraints on the blockchain industry are more akin to the constraints on the AI industry prior to the progression of complimentary, emerging technologies. Many of the specific use cases blockchain is well suited to address rely on integration with other technologies. Supply chain use cases, for example, require IoT integration, M2M communications, and in many cases 3D-printing technologies. Stable coins and tokenized assets require technologies that allow us to better bridge the physical and digital worlds without relying on a third party. The use cases of the future may require technologies or inputs that we haven’t yet heard of or capabilities that have not yet been developed. AI lay in wait for decades before complementary technologies were able to support it.
Increasingly, as the pace of technological innovation accelerates, what seems to be needed in order for any / all of these technologies to succeed is their convergence.
While some lament the pace at which the industry is evolving, whether you consider it to be progressing quickly or slowly is directly related to your frame (industry) of reference. However, there are elements of the blockchain industry that are not comparable with the industries that have developed thus far. The instances in which blockchain technology makes sense are by definition the use cases in which there is a low level of trust and coordination and a high level of fragmentation.
Therefore, unlike other technologies which merely require an MVP (minimum viable product), blockchain technology requires an MVE (minimum viable ecosystem), which is clearly a much higher hurdle to clear.
Blockchain technology also enables interaction to occur in such a fundamentally different way that enterprise adoption may require a mindset shift. This could mean that enterprise adoption occurs more “generationally” than other technologies, constrained until those in decision making positions are ready to embrace an entirely new way of thinking. In other words, this transition will take time. The industry will develop gradually. The development of similarly transformational technologies indicates that it will be worth it.
The Shape of Industry Development
Now let’s look across industries to assess whether or not the industry will develop “vertically”, where value and usage accrue to a select few blockchain platforms, or “horizontally”, where value and usage accrue to many unique blockchains which are used for specific use cases. Many prominent industry figures have opined on this topic. Let’s look beyond the blockchain — specific arguments that can be made for one path versus another and instead draw insights from parallels with other industries.
We will look at specific industry examples in more detail below, but at a high level, the evolution of many industries can be divided into three stages: platform fragmentation, product proliferation, and aggregation.
Platform Fragmentation: Once broad product-market fit is established and core market adoption is achieved, industries tend to fragment as they target more users via specialization. Example: Cable Networks — MTV.
Product Proliferation: As the industry fragments, barriers to consumption are typically reduced which causes supply to increase to accommodate this incremental demand. Example: OTT Content — Netflix.
Aggregation: This oftentimes generates a need for an industry player that can provide cohesion to the fragmented system as user search costs and or / friction increases along with fragmentation. Example: Different OTT Content Platforms Become “Apps” on Entertainment Operating Systems — X fininty1.
In the past, these players have been “aggregators”, aggregating the fragmented ecosystem onto one platform through which users can compare / contrast / access all the disparate offerings within an industry. In our current world, where the trend is towards decentralization (proliferation of edge / mesh networks, popularity of crowdfunding, visions of Web 3.0, etc.), the “aggregation” stage would be better described as the creation of an interoperability or connectivity mechanism.
An “aggregator”establishes relationships between fragmented product offerings while allowing them to exist independently and to thrive. This is in stark contrast to “consolidators,” which by definition centralize power. Whereas industry value tends to accrue to “aggregators,” consolidation usually results in a “conglomerate discount” to valuation.
In the Media industry, fragmentation occurs down to the smallest unit that can be consumed in a process referred to as “unbundling.” Generally, as content “unbundles”, it is enabled to reach a wider audience as monetary barriers to consumption are reduced. Supply increases to meet the increased demand as more participants enter the market. Let’s look at some specific examples:
News: Newspapers began as a bundle of print content. Digital news platforms such as Yahoo or CNN.com increased distribution and also allowed for the consumption of smaller units of content (a single article, for example.) This in turn led to a proliferation of specialized digital news sources (TechCrunch, Bloomberg, etc.) This became overwhelming to consumers, which turned to aggregation platforms such as Google or Twitter to organize all this content, lower search costs, and, in some cases, to create a more personalized “newspaper” (ie. newsfeed)
Music: Albums began as a bundle of songs. As music became digitized, platforms began to emerge to digitally distribute songs (Napster, LimeWire, iTunes, etc.) which reduced the minimum unit size of consumption. Increased distribution channels also lowered the barriers to entry for musical artists. This caused a proliferation of content and overwhelmed consumers. Aggregation platforms such as Spotify emerged to organize all this content, lower search costs, and create personalized playlists (re-bundling.)
TV: Media began with broadcast networks which aimed to reach large swaths of viewers. Networks naturally developed to allow for more segmented targeting by appealing to sub-segments of viewers. The production of digital content (OTT) began to proliferate, which lowered minimum consumption costs to ~$10 / month. As demand increased with lower barriers to consumption, an explosion in content creation followed. Platforms such as Netflix and Hulu, themselves aggregators in a way, began to provide personalized viewing experiences. As the number of these OTT content platforms also proliferated, it required an “aggregator of aggregators” (Amazon, Xfinity1) to allow viewers to organize, search, and access all of this digital content from one place.
While the main parallel relates to fragmentation and re-aggregation, another important component of the media industry’s evolution is the impact that “unbundling” has on consumer economics. “Unbundling” increases accessibility for consumers by lowering monetary barriers to consumption (i.e torrenting is free, the price of an OTT subscription is less than a cable subscription, etc.)
The consumer economics of “unbundling” are not dissimilar from those that can be achieved by applying blockchain technology to inefficient or rigid processes.
Blockchain technology can reduce the cost of entry and enable broader participation in activities such as fundraising, access to credit and /or social services, and international payments. If the above model holds, the first step will be that the blockchain industry fragments (more on this below.) Then as it “unbundles” more services, enabling broader participation in these activities, supply should also increase in order to meet this incremental demand.
The parallel does not hold on the economics of production, however, as one of the main enablers of the unbundling / fragmentation of the above mentioned media industries is the zero-marginal cost of digital distribution. This property does not extend to the blockchain industry where the initial costs of developing a new protocol are currently high.
*** Many of the ideas expressed above rely on and expand upon the ideas of my former colleagues at Barclays Capital, particularly Kannan Venkateshwar, Head of U.S. Media, Cable, and Satellite Equity Research.***
Parallels to the Blockchain Industry
Whilenone of these industries are directly comparable, if the development of these industries serves as any indication of the way in which the blockchain industry will develop, the industry will fragment into use case specific blockchains. As explained in greater detail below, meaningful value will accrue to the companies that can create a way for fragmented blockchains to communicate and connect (ie. “aggregators”.)
Phase 0: The blockchain industry began withtwo dominant platforms, Bitcoin and then Ethereum.
Phase 1: We are now seeing a fragmentation of the ecosystem to meet the needs of specialized use cases, which should continue at least until the trade-off between decentralization, privacy, and scalability is no longer required. Given the constraints imposed by this trilemma, it makes sense that different protocols would be needed to accommodate different use cases. It also probably doesn’t make much sense to expect the same platform to support a country’s digital identity system while also supporting applications such as CryptoKitties. The reasoning extends beyond scalability issues. As highlighted by Cosmos, “ Much like communities, companies and nation-states, each existing cryptocurrency is born with the seed of some cultural ideal.” In order for these companies to express those ideals, they will create protocols that grant them the flexibility to do so. From all lenses, it looks unlikely that there will be “one blockchain to rule them all.”
Phase 2: As rigid processes and closed systems are “unbundled”, wider spread usage and adoption will occur across these multiple blockchains. This will increase friction and transaction costs for consumers. As the number of blockchains increases, so does the complexity of managing a number of different tokens and assets siloed within disparate ecosystems that have no way to communicate or connect.
Phase 3: Companies that can create common standards or mechanisms for interoperability and / or connectivity between blockchains will occupy a central role in industry development (more below.) There are many projects currently working on becoming this “aggregator” or “Internet of Blockchains” including Cosmos , Polkadot, and FourthState Labs.
The idea of interoperability in the blockchain industry is not new. However, looking at other industry evolutions makes it seem clear that the blockchain industry will continue to fragment into specialized blockchains and that as this happens, value will accrue to the platforms that facilitate interoperability, communication, and connectivity between chains.
As the blockchain industry fragments, new entrants will need to offer defensibly differentiated value propositions if they are to disrupt established network effects. An “aggregator” or connectivity mechanism will be crucial to further development of the industry. Let’s now look at several industries where multiple networks have had to compete and co-exist side by side.
E-commerce and Social Networks
While Amazon and Google are perhaps the two platforms which best exemplify network effects, they have also both failed at incentivizing users to join new networks at one time or another. Amazon was not initially successful in its attempts (Amazon Auctions, zShops) to compete with eBay. Amazon failed at competing with eBay (selling used goods) until it realized that it couldn’t compete by trying to be “ a better eBay.” With the introduction of the Single Detail Page, which gave Amazon customers the option to view new or used versions of a product, the company began targeting Amazon’s own customers instead of eBay’s. This then offered eBay sellers a more compelling value proposition to join Amazon’s network as it opened up a new market to them (Amazon’s customers.) This was enough to start the flywheel needed to develop a network of both buyers and sellers.
Prior attempts failed because they tried to create a marginally better, copy-cat network. This requires all network participants (buyers and sellers) to overcome the “gravitational inertia”of their current network and move to a new network together as the value of an incremental feature will never offset the magnitude of switching costs for an individual user.
Google+ also failed with its attempt at a “me too” social network. Again, this effort failed because it wasn’t defensibly different from other, more established social networks (Facebook.) It’s much easier for an established network to copy a competitor’s new feature than for a new entrant to create network effects from scratch.
While there are valid reasons for creating specialized protocols to accommodate differing use cases, blockchain platforms that focus on making marginal improvements over existing networks are unlikely to succeed. Instead, new networks must offer a value proposition compelling enough to justify switching and unique enough that competitors can’t easily replicate it.
One exception to this rule is if a player is willing to add a feature that the incumbent is not willing to add. This is how TaoBao beat the already established eBay in China. TaoBao introduced direct messaging between buyers and sellers, which eBay wanted to avoid since side channel communication between buyers and sellers increased the likelihood that transactions would be conducted outside the eBay platform. eBay would then forego the associated transaction fees.
Blockchain networks are doing exactly this, adding features (trust, transparency, immutability, and direct P2P interaction) that the incumbent platforms are unwilling to add.
While new blockchain networks will have to offer strong value propositions in order to compete with established blockchains, blockchain networks in general should be able to beat out traditional networks.
***This section summarizes and expands upon the ideas of former Amazon and Google engineer, Steve Yegge.***
Once the industry has fragmented, these disparate networks will need to communicate with each other. The telecom industry is a prime example of an industry that requires the bridging of networks.
Due to capital and regulatory constraints, it is not feasible to build a global telecommunications network. Therefore, cross-country communication often requires cooperation among carriers. Sometimes this occurs in the form of roaming agreements. Other times it has required agreement upon global standards. Pre- 4G LTE, Europe operated according to GSM standards while some U.S. carriers (Verizon and Sprint) operated according to non-compatible CDMA standards. Without compatibility, a Verizon customer traveling in Europe wasn’t able to use their phone while overseas. This obviously created a high level of friction for consumers. Telco companies again realized that they had to work together to develop a mechanism to allow consumers to hop from one network to another more seamlessly while moving outside a given carrier’s coverage zone. The 4G-LTE global standards were designed and excepted by all major carriers with this in mind.
Issues with compatibility across geographic networks can be compared to managing multiple native tokens across multiple blockchain ecosystems that can’t easily communicate with each other. This currently requires conversion into other currencies via an exchange (sometimes multiple times) before being able to use assets in another ecosystem.
Like the telecom industry, the blockchain industry is a network of networks and will need to continue to set standards aimed at facilitating more seamless communication between these networks.
Telecom is also a highly regulated industry and differences in regional regulations have caused the industry to develop very differently in different geographies. For example, the European Telecom industry is much more competitive (harsher anti-trust enforcement) than its U.S. counterpart, with +10 different major carriers relative to ~3–4 in the U.S. In the U.S., operators tend to lease cell towers from third-parties while a higher percentage of European operators still own their tower infrastructure. In other words, regulatory and regional differences have created a less restrictive operating environment for U.S. telcos relative to their European counterparts. As the blockchain industry fragments, regional regulations and adoption patterns may heavily influence which projects succeed.
60 different stablecoins are currently under development across geographies. Source: https://www.blockchain.com/research
The mechanism by which these networks connect to and communicate with each other is of central importance to an industry. Comparison with the networking infrastructure industry illustrates this point clearly.
With the advent of cloud computing, enterprises have shifted from on-premise data centers to third-party colocation facilities. These third-party facilities have traditionally been divided into two models: wholesale, custom built dedicated facilities also called “server farms,” and retail facilities that focus on interconnection via direct fiber cross connections between customers. These retail focused companies have created a neutral, third-party location for companies to directly connect to each other, to peer or exchange traffic and /or data securely and rapidly.
The infrastructure providers that have built their business on being a facilitator of connectivity between disparate enterprises, ISPs, and telcos have accrued the most industry value, historically..
Blockchain’s Battle with Financial Inclusion — Part 1Photo from Oradian
“We can fix it with Blockchain” — that was one of the first things a Silicon Valley Impact Investor said to me at a Financial Inclusion roundtable a few weeks ago. Blockchain would be the panacea! As someone who is deeply passionate about driving social change through distributed ledger technology, I reflected on where we currently stand in the evolution of our ecosystem and what we need to do for my optimistic Silicon Valley friend to be right.
The question I repeatedly asked myself is — Can Blockchain really overcome the multitude of factors that prevent a truly financially inclusive world and solve the “access to finance” gap?
As a bit of context, it is widely reported that over 2.5bn adults across the globe, from Berkeley through to Lagos, London and Mexico City, now comprise the global un(der)banked. This is an unbelievable statistic given we’re now living in a world where mobile phones and internet access are ubiquitous. Undoubtedly, macroeconomic, geopolitical and cultural policies spanning decades, if not centuries, have been and continue to be the biggest drivers for the creation of the disparate and inequitable financial system we see today. That being said, in many cases, the fundamental barriers to financial services can be grouped around three, seemingly straightforward to resolve, obstacles:
Obstacle #1: a lack of formal identification for individuals,
Obstacle #2: the absence of a verifiable credit history for individuals, and
Obstacle #3: a lack of access to cheap and accessible flows of capital
When one begins to think about the systems underlying identification, credit history and capital flows, it’s hard to not be immediately be blown away by the potential that a permissionless, tamper-resistant ledger has for increasing the transparency of, and ease of access to, vital information. All three obstacles are the result of interdependent central stores of information held by a myriad of parties, each with their own incentives. Governments are the gatekeepers of formal personal ID documents, private companies are generally responsible for maintaining credit history, and global financial institutions determine the cost of moving capital. Trust amongst the various parties is extremely low, as represented by the increasing number of quangos and regulatory bodies we see worldwide.
Applying Wesley Graham’s “A Simple Guide to Blockchain Use Cases”, financial inclusion use cases should be easy to come by, given the involvement of various parties (political and non-political) who need to coordinate across borders and trust the validity of interdependent transactions. So, why does it appear we have seen such little progress in resolving the three obstacles that prevent a level the playing field for the global un(der)banked?
From where I sit, the clear answer is that it’s currently hard to create a blockchain based system that simultaneously satisfies the properties needed for decentralized identification, verifiable credit histories and capital flows. Instead, we see multiple parties attempting to solve each of these problems in relative isolation. Without sufficient thought given to the need to ensure interoperability, we’re at risk of repeating the same mistakes of the past by creating another siloed financial system. Should we really be solving for decentralized identification, credit histories and capital flows independently?
Let me start the discussion with obstacle 1: a lack of formal identification for individuals:
Obstacle #1: A lack of formal identification for individualsPhoto from Jean Marie Altema
The fact that you can’t open a bank account or touch the conventional financial system if you don’t formal ID documents in hand (this applies even when you’re using digital money such as M-Pesa, bKash or Venmo) is at the core of Obstacle #1.
Yes, anti-money laundering (AML) and know your client (KYC) regulations help to prevent illicit flows of capital, however, if you’re in a country where government issued ID is difficult to get hold of and maintain, have fled your homeland due to conflict, or simply don’t have access to the physical pieces of paper (and plastic) that represent human “identity” in the eyes of the law, you’re out of luck.
Solutions such as uPort, Civic, CULedger or those developed by the UN backed ID2020 Alliance have all tried to solve aspects of the ID conundrum. Some have focused on digitizing existing paper-based ID documents, and others on giving users more control over what information is shared and with whom.
Whilst we have seen some success across the globe, particularly in Estonia (check out this post from my good friend, Justine Humenansky, for a deeper dive into the state of play for digital identity), on the whole, existing solutions have not yet dealt with the one of the most fundamental stumbling blocks (no pun intended) that we need for an effective system — Blockchain’s Decentralized Identity Trilemma. As publicized by Maciek, this trilemma concentrates on the (in)ability of decentralized ID solutions to be:
Privacy-preserving — meaning that any individual can obtain and use a decentralized ID without needing to reveal personality identifying information such as name or date of birth in the process (i.e. getting hold of a decentralized ID without having to provide your personal information to the ID issuer).
Self-sovereign — meaning that an individual can create and control as many identities as they choose independent of involvement from a third party (i.e. creating a decentralized ID without the need for a centralized 3rd party)
Sybil-resistant — meaning that identity is subject to scarcity (the key here being that creating more identifiers cannot be used to manipulate a system)
Many solutions use existing KYC processes to prove the existence of an individual — this creates scarcity but at the cost of privacy and self-sovereignty. Other solutions based on Web-of-Trust principles and Decentralized Identifiers (DIDs) provide for self-sovereignty but are susceptible to sybil attacks. No solutions currently solve for all three.
If Blockchain really is to fix the financial system for those 2.5bn who are excluded, the concept of individual identity may well need to be developed and maintained in a truly Blockchain native way (whatever that means). Additionally, it should focus on the practical and economic constraints often faced by the un(der)banked, rather than looking towards limitations imposed by current banking frameworks.
With a blank piece of paper, what would a true “we can fix it with Blockchain” solution really look like?
Given the practical challenges around validity, acceptability and key management for decentralized ID solutions, I often ask myself whether it truly is possible to live in a world where identity is digital and “central gatekeepers” are not necessary. My heart tells me yes. My head tells me there’s still much work to do.
Assuming we will indeed create a world where the decentralized ID trilemma is solved and formal identification is accessible for all, we still need to think about credit history and capital flows. In the next article I’ll talk about how blockchain technology is dealing with Obstacle #2: the absence of a verifiable credit history for individuals, and Obstacle #3: a lack of access to cheap and accessible flows of capital, as part of its promise to enable a financially inclusive world.
Bosun Adebaki is a Business Consultant at Blockchain at Berkeley and an MBA student at UC Berkeley’s Haas School of Business. He believes in using FinTech to create a more accessible financial system.
We all have a human right to identity, commencing the moment we are born, according to Article 8 of the UN’s Convention on the Rights of the Child. At its most surface level, identity consists of one’s first and last name, date of birth, nationality, and sometimes a national identifier such as a SSN — data points that are recorded on birth certificates, passports, and state issued IDs. The problem is, these forms of identification require the maintenance of physical artifacts in an increasingly digital world and are completely reliant upon the central authorities that issue and validate them. As a result, according to the UN, 1.1 billion people worldwide don’t have a way to claim ownership over their identity. Without a valid form of ID, one can’t own property, vote, receive government services, open a bank account, or find full-time employment. More importantly, without control over one’s identity, it is easy to become invisible, to be relegated to the role of spectator, unable to participate in society simply because one can’t prove that they are who they say they are.
Based on graphics from ID2020
How Can Blockchain Help?
Trustworthy digital identification has been “one of the main challenges facing the internet ever since it was invented, because none of the traditional, offline means of verifying that someone is who they say they are apply¹.” Furthermore, digital IDs can raise questions about central points of failure and surveillance states if these IDs are created, stored, and managed by a central authority.
Merely creating a digital identity is not sufficient, there are specific properties required for a digital identity to fulfill its potential and maximize its social impact. ID2020 has created a framework outlining the properties of a responsible digital ID. These criteria conveniently map to properties of blockchain technology, illustrating how blockchains can help create a better digital ID. Blockchain systems also reduce dependence on third-party intermediaries and can survive disasters that might wipe out or compromise more centralized record-keeping systems (including breaches.)
However, as expressed by BanQu founder Ashish Gadnis, “Identity on blockchain is old news. The real value of blockchain is its unmatched ability to create and secure an economic identity for the world’s billions living in extreme poverty today…..this is truly a revolutionary opportunity⁹.” In other words, blockchain technology doesn’t just allow for the creation of a better digital ID, but rather presents an opportunity to create a “self-sovereign” identity.
The need for a physical ID creates obstacles, which could be solved with blockchains, for two populations in particular.
1.) The Homeless Population
For the homeless population, digital identities registered on the blockchain could reduce the burden of maintaining physical copies of ID (which are easily lost, stolen, or ruined in inclement weather while homeless) and eliminate the need to procure duplicates (one usually needs a valid ID in order to replace a lost ID….) These digital IDs would not only allow users to quickly and easily verify their identities, allowing them to access more services, but would also build a profile of transactions that could be shared across service providers through a permissioned blockchain. This is a vast improvement over the current system which involves service providers relying on word of mouth as to an individual’s history or trying to piece together fragmented data from multiple, disparate agencies in an attempt to assemble an individual’s medical or financial history like a “jigsaw puzzle².”
MyPass Austin: After participating in the 2018 Bloomberg Philanthropies’ Mayors Challenge, the City of Austin, Austin-Travis County EMS, and the Dell Medical School at the University of Texas are running an identity management test pilot targeted at the homeless population. MyPass Austin runs on a permissioned Ethereum based network utilizing software provided by BanQu, a blockchain-as-a-service company, and was piloted with 30 to 50 individuals who each possessed an SMS-enabled cell phone. BanQu is planning to roll out similar platforms in five more U.S. cities. After piloting the program for the last seven months, MyPass Austin now aims to provide every resident of the city “simple, secure and convenient” access to essential services, such as emergency care, employment programs, or housing².
The UN’s Sustainable Development Goals include target 16.9 which aims to “provide legal identity to all, including birth registration, by 2030.” However, there are >20M refugees worldwide, many of which no longer have access to their legal identities³. Not surprisingly, the UNHCR has been evaluating ways to use blockchain technology to aid refugees and to help them to regain the legal identities that they lost when forced to flee their homes.
The UN and the WFP: The UN and the World Food Program (WFP) recently piloted a program, called Building Blocks, aimed at better tracking aid from the WFP. The U.N. agency launched the one-month pilot in May, involving 10,000 of the more than 50,000 inhabitants of Jordan’s Azraq camp. In this pilot, refugees accessed their accounts via biometric eye scans, allowing them to receive food. Following the initial pilot, the UN and the WFP aim to expand the pilot to reach +100,000 refugees across multiple camps in Jordan by the end of the year⁴. The initial Building Blocks pilot ran on a private, permissioned blockchain using the Parity Ethereum client with a Proof-of-Authority (PoA) consensus algorithm (more on related trade-offs below.) While Building Blocks was aimed more at tracking aid than creating digital identities per se, Caroline Rusten, head of U.N. Women’s humanitarian unit, has identified the potential of blockchain technology to improve identity management for refugees. Particularly, Rusten highlighted that “blockchain could be used to create a secure, paperless record of skills and education that refugees can carry with them, to which information can be added as they are on the move, [allowing] people to be appreciated for who they are and the qualifications they have and not just seen as refugees⁴.”
Validity and Voting
Creating a digital ID with blockchain technology could also allow for greater voter participation. Blockchain systems have the potential to create an electronic voting system that allows for auditing while preserving anonymity of an individual’s votes and that prevents record tampering. That means people could securely vote from mobile phones, which could increase voter participation and reduce obstacles for those attempting to vote by absentee ballots from overseas.
Zug, Switzerland: Zug recently conducted an e-voting pilot as part of a wider initiative to create a single electronic identity for its citizens. In 2017, the city of Zug began creating digital IDs for its citizens, which can be accessed by downloading the Uport mobile app and registering their Uport ID on the Ethereum blockchain. Zug then used this system to run a small scale trial (72 out of 240 potential participants chose to participate¹²) of e-voting between June 25 and July 1 of this past year. Polling information and residents’ IDs were stored on the Ethereum blockchain. The e-voting system was developed by Luxoft, a software company based in Zug, in partnership with the city and the department of computer science at the Lucerne University of Applied Sciences⁵.
West Virginia: In May, West Virginia partnered with technology firm Voatz to pilot a mobile voting app for deployed voters in two counties. Following a successful audit, the pilot will be offered to eligible voters across 55 counties and a mobile voting pilot will be expanded to absentee ballots for overseas military service members⁶. The mobile-voting app requires one to take a photo of their ID and film a short video of themselves moving their eyes. This essentially ties facial recognition to a private key, allowing for voter verification via mobile phone. Nearly 140 West Virginians living abroad in 29 countries voted via mobile device in the recent U.S. midterm elections¹³.
Nasdaq: In partnership with Chain, Nasdaq launched a blockchain-based e-voting PoC with four web-based user interfaces in Estonia, in the context of shareholder votes.
In addition to the pilots and projects outlined above, blockchain digital identity pilots have taken place in Dubai (ObjectTech), Malta, Moldova (digital ID for anti-trafficking), Antwerp, Finland (MONI), and other countries across the globe.
However, distinct, one-off pilots will not be enough to create a truly “self-sovereign” digital identity. Coordination between all the organizations running these pilots will be needed. In the end, central authorities, public institutions, and private organizations will have to agree to accept these digital IDs as valid and to work together to create standards for interoperability. Technological solutions and UI/UX must continue to develop as well.
The current implementation of disparate identity projects worldwide often results in siloed solutions. Source: ID2020
Social Coordination and Integration
Coordination is needed not just between the public-private sectors but also across institutional and geographic borders. Integration with legacy systems is important as well. For example, during the Harrison County pilot, paper copies of the blockchain ballots were created in order to scan the votes into the vote tabulators, since the votes were not automatically recorded into the election recording system⁶. This clearly defeats much of the purpose of the pilot. Major institutions recognize these issues and have created initiatives, alliances, and partnerships that aim to conduct research, fund pilot programs, set open standards, and enable multi-lateral collaboration and integration.
The World Bank has created the ID4D initiative, which operates across the World Bank Group. ID4D consists of units working on digital development, social protection, health, financial inclusion, governance, gender, and legal issues. The initiative also focuses on integrating digital ID systems with civil registration (documenting life events such as birth, marriage, adoption, death, etc.) and vital statistics. ID4D also plans to launch the Mission Billion Challenge in November 2018, sponsored by the Omidyar Network, the Bill and Melinda Gates Foundation, and Australian Aid.
The ID2020 Alliance is a public-private partnership dedicated to solving the challenges related to identity through technology and aims to “finance projects implementing secure, digital ID solutions, to set standards to facilitate interoperability, and to enable multi-stakeholder collaboration.” As part of the Alliance, last summer Microsoft collaborated with Accenture and Avanade to create a blockchain-based identity prototype on Microsoft Azure.⁷ This prototype was designed to be interoperable with existing identity systems so that personally identifiable information can reside “off chain.”
The World Economic Forum also launched a shared Platform for Good Digital Identity at the Sustainable Development Impact Summit 2018 in New York this past September, with Omidyar Network committing a three-year grant to support the platform⁸.
Evernym and the Sovrin Foundation have launched the Identity for Good Initiative, opening up Evernym’s Accelerator Programme to non-profit organizations. The hope is that with access to tools, technologies and expertise in decentralized identity models, these organizations will be better able to advance their missions.
These digital identities will also need to be accepted as valid by state authorities in order to reach their full potential. Named “the most advanced digital society in the world” by Wired magazine, Estonia is one of the furthest along in this regard.
Based on graphics from e-Estonia
e-Estonia: Through Estonia’s e-identity program, all citizens receive a secure digital ID card (powered by a blockchain-like infrastructure and utilizing 2048-bit public key encryption) that allows Estonians to access public, financial, and medical services, to pay taxes, vote, and get prescriptions online, to provide digital signatures, to drive, and to travel within the EU¹⁰. This digital ID card replaces most of the physical artifacts that one carries in their wallet, from driver’s licenses and passports to insurance cards and subway passes. The program runs on an open-source backbone called X-road, and utilizes K.S.I., developed by Guardtime. K.S.I. is also used by NATO and the US Department of Defense¹⁰. While Estonia’s solution still requires a physical artifact (physical digital ID card), this level of support from state authorities is what will be needed across nations for many of the above highlighted initiatives to succeed.
Key management is commonly cited as a challenge with digital identity systems that leverage blockchain technology. Obviously, if an individual has had difficulty holding on to their ID, they may also have issues holding on to their private keys. Some suggest that private keys could reside in a smart chip on a key fob or something resembling a credit card, or could be held in a secure enclave within one’s phone. This is the most secure option. However, if the item storing an individual’s private key is lost, stolen, or damaged, they will not be able to access their account. Alternatively, keys could be stored with a central authority, although that defeats much of the purpose since decentralization is compromised.
There are several ways to attempt to balance the tradeoffs between security and decentralization. The MyPass Austin system allows two additional verified users, such as a service worker or an emergency-care provider, to be added to a homeless individual’s account in the event that they lose their private key.Similarly, uPort has created an identity recovery mechanism that lets the user select people from their contact list and with a quorum of these contacts, connect their persistent ID to a new device. With uPort, transactions are sent from a mobile device (which stores a user’s private key) through a Controller Contract to a Proxy Contract (which is tied to a unique identifier) which then interacts with an Application Contract. The Controller Contract maintains a list of “recovery delegates,” and in the event that a user loses their private key, a quorum of delegate signatures would allow the user to connect a new device to a new private key. However, the user still maintains access to their records since the new device is linked to the persistent identifier held on the Proxy Contract (the 20-byte hexadecimal string defined as the address of the Proxy Contract.)
A useful digital ID necessarily includes sensitive information such as personal identifiers and medical records, and oftentimes requires a private key to be tied to biometric data in order to prevent the creation of multiple or fraudulent accounts. The MyPass team realized that people “have major concerns about the use of biometrics” and is looking for secure alternatives, including requiring participants to use a combination of a QR code and password in the future². Regulatory compliance (HIPAA, etc.) will also need to be taken into account when these systems are designed. David Dill, a professor emeritus of computer science at Stanford University and founder of the nonprofit Verified Voting, points out that while blockchain technology solves some problems related to e-voting, it “doesn’t deal with authenticating the voters before the election … or the security problems on the voters’ devices⁶.”
The Typical Trilemma
The digital identity use case faces the same trade-offs between scalability, decentralization, and privacy present in many other blockchain use cases. Many of these pilots have chosen to sacrifice some degree of decentralization to ensure better privacy and security. Most of these pilots are being run on permissioned blockchains, utilizing smart contracts to further control access to and preserve confidentiality of sensitive data. Building Blocks initially launched on a public blockchain but ran into scalability issues, finding the public version to be “too slow and too expensive¹⁴.” The ability to scale is also a challenge when considering the viability of e-voting on a national level. Depending on assumptions about platform, txn/s, and how many votes would be included per block, it could take up to two weeks to process a nationwide election with 60% voter participation in the U.S.¹¹ However, using multiple, region-based blockchains could address this issue in the short term while longer term scalability solutions are more fully developed.
When one regains control over their identity, they can begin to reclaim control over their life. As part of a solution requiring coordination and participation from a wide variety of institutions, nations, and organizations, blockchain technology can help individuals to reclaim this control. While blockchain technology can create dramatic improvements in digital identity, as acknowledged by Yoshiyuki Yamamoto of the U.N., “It can’t be done overnight, we are still at a very early stage⁴.”