financial APIs

ONLINE BANK: Just how are US incumbent banks using Fintech to future-proof themselves?

It's without a doubt that the global banking industry is undergoing a digital renaissance. Digitally native neobanks are serving customers at a third of the cost of incumbent banks, leveraging modern core technology architectures to innovate faster and operate more efficiently, and earning them a significant chunk of market share. Fintech companies are building solutions around lucrative niches in the value chain. A good example of this is payments unicorn Stripe, valued at a cool $22 Billion, recently announcing it will be offering loans to online businesses to support their growth ambitions. In contrast, incumbents are subjected to the limitations of their core architectures and the resultant slow rate of change to innovate and adopt operational efficiencies necessary to retain their market share.

In the US, incumbent banks are actively investing in Fintech companies as a means to "future-proof" themselves. By "future-proof" we mean three things: (1) increasing the potential for high returns in the short-to-medium term leveraging the benefits stated above -- take Goldman Sach's investment in digital lender Better Mortgage. (2) Gain exposure to emerging sub-industries, as well as, utilize new Fintech platforms to enable rapid scaling and less expensive development of ecosystems and ancillary services -- take Wells Fargo's investment in OpenFin, who is now used to help modernize the bank's software for front-and-back-office functions. (3) Lastly, reduce spending on IT by leveraging the structures of Fintech companies such as the removal of technical debt, leveraging the economies of scale of cloud-based services, and using development tools that support automation (DevSecOps).

We recently came across CB Insights' latest Fintech trends report which notes that in 2019 YTD, US banks have participated in 24 equity deals to Fintech companies -- approximately 54% of the record 45 deals in 2018. Unsurprisingly, Goldman Sachs, Citigroup, and JP Morgan Chase were noted to be the most active US incumbent bank investors in Fintech. Since 2016, Goldman Sachs has primarily invested in Real estate and data analytics Fintech companies which compliments their current strategy, Citigroup has focused on payments & settlements and Blockchain Fintechs providing evidence of a potential Banking-as-a-service platform in the near future, and lastly JP Morgan Chase has prioritized investment in capital markets and accounting & tax Fintechs in hopes of strengthening its payments play.

For those incumbents averse to Fintech partnerships, McKinsey outlines three options for replacing the core to their next generation platform. The costliest ($100M to $500M+) and most time consuming option being a full replacement of the core with "new" traditional tech platforms. Opposite to this is the cheapest ($50M to $100M) and arguably the most value-add option of migrating the bank's core onto a "greenfield" tech stack -- essentially a modular and API-first cloud-native architecture. RBS' Bó, National Australia Bank's launch of unsecured lending solution QuickBiz, and Goldman Sach's Marcus are all examples of the greenfield approach. As noted by the Economist Intelligence Unit, the greenfield approach was considered the most sought after bank innovation strategy by 36% of the 400 banking respondents, a close second was to invest in Fintech start-ups with 31%.

We have noted it before and we will note it again, greenhouse approaches are only effective when the incumbent acknowledges digital as more of a transformation strategy than a channel -- case in point is JP Morgan Chase's failed digital bank Finn. The financial initiatives of Chinese tech companies such as Alibaba and Tencent, for example, serve as a powerful representation of how a core tech chassis serving e-commerce can translate to the physical world leveraging a digital value proposition across its front, middle and back ends. This is why we still believe to see more Fintech mergers and acquisitions beyond the current industry aggregate deal value for 2019 -- more than twice the aggregate of the same period in 2018.


OPEN BANKING: PSD2's self-defeating requirements need addressing for true Open Banking to exist

We've noted before that the implementation of Open Banking (via the EU's Second Payment Services Directive or PSD2) may not be going according to plan. As a reminder, European legislation -- PSD2 is supposed to expose incumbent banking data via structured APIs to third party providers (TPPs) that want to build upon banking information and money movement. In theory, this lowers the stickiness of bank accounts, allows data to travel safely into aggregators and apps, and lays the groundwork for financial bots and agents that make shopping decisions.

Surely, neobanks would benefit from the ability to see and move these traditional assets. Well, maybe not. According to a new report by Fingleton and the Open Data Institute for the Open Banking Implementation Entity (OBIE), "The narrow focus of the Open Banking APIs limits their potential to drive wider competition in the financial sector, for example by helping customers shop around for better interest rates on savings accounts or cheaper mortgages." Additional examples of where the PSD2 mandate failed TPPs included (1) the lack of refund functionality, and (2) the lack of functionality for customers to pre-approve payments to a merchant -- similar to a subscription debit -- instead of a customer having to manually authorize each payment,

The remedial actions for the OBIE included (1) mandate "variable recurring payments" making it cheaper for merchants to receive customer payments, (2) revised customer consent rules to remove the need for customers to re-authenticate with each TPP through their bank every 90 days, and (3) the extension of Open Banking -- beyond current accounts -- to a more diverse range of products such as mortgages, insurance, pensions, and savings accounts. Subsequent to the report's publication, the OBIE announced the initiative to create "Premium APIs" that provide a commercial incentive for banks to address the above listed failures. Those are going to need to be some considerable incentives to get the incumbents to budge. Hopefully, if the TPPs trying to build experiences don't want to deal with incumbent infrastructure, there is always Bitcoin. 


Source: ODI & Fingleton (Open Banking Report for the OBIE)

BIG TECH & CYBER SECURITY: Every cloud has a surveillance lining

Let's be honest here, before the turn of the 21st century, if a stranger asked to keep our photo in exchange for a funny caricature, or a supermarket had asked to put a microphone in our homes, or a train company had asked our whereabouts in the station, or physical education teacher had asked us for our step count and sleep data every day, we would have said no. Now days, we upload multiple photos to Russian-based FaceApp, buy Amazon Alexas, use London Underground’s free WiFi, and track our activity on Garmin watches. And still manage to sleep well at night...well some of us at least. We recently learnt that both Amazonand Google admitted to having employees listen to recordings from their smart speakers. Whilst Facebook argues that its "users have no expectation of privacy" on their posts. These big US internet companies — Amazon, Apple, Facebook, Google and Microsoft — have all, to some degree, failed to protect their users' data and establish a base level of security. Controversies about how Facebook -- who received a $5B fine by the Federal Trade Commission -- shared user data with developers such as Cambridge Analytica and foreign governments earns them the lowest marks on security and data privacy, while Apple's strong emphasis on adopting considerably better policies than its more data-hungry competitors, might earn it the highest marks among the five. Other examples worth noting can be found in a previous newsletter entry here.

Relatively, there are more sophisticated means to retrieving user data without the target always being aware that it is happening. One of these was revealed by the Royal Melbourne Institute of Technology, who used various native sensors — such as the accelerometer — found in smartphones to predict the personality traits of its user. Similarly, yet more terrifying, a recent story published in the Financial Times, noted how most internet companies are equally at risk from a mobile phone spyware suite called Pegasus -- produced and sold by Israel-based “Cyber Warfare” vendor The NSO Group. The same spyware implicated in a breach of WhatsApp earlier this year. Private agencies and governments have long used Pegasus to successfully harvest private data — such as passwords, contact information, calendar events, text messages, and live calls — from the mobile phones of targeted individuals. 

Shockingly, the story focuses on the recent evolution of the spyware to infiltrate the data residing in the cloud used by the targeted individual. Such data can contain a full history of location data, archived messages and/or photos, emails, sensitive passwords, and financial records. The way it works is rather smart as it allegedly copies the authentication keys used by services such as iCloud, Google Drive, Facebook, Box, and Dropbox, among others, from a corrupted mobile phone. The keys are what these services use to verify an individual's identity, and thus provide them with access to the data on the respective cloud server. Put simply, these keys allow for an attacker to impersonate the target's phone in order to gain access to the data stored on the cloud, bypassing 2-factor authentication and login notifications. Notably, the NSO Group denies having spyware that can hack such cloud applications, services, or infrastructure.


As noted in the first entry above, the world is shifting to a more digital and decentralized form of finance and commerce, whether it be Wealthfront or Betterment roboadvisors assisting you in facilitating your wealth management, or using Robinhood's mobile app to enact stock trades. The truth is that most of this data flows through the cloud services of internet companies. And so long as hacking tools like Pegasus exist, coupled with our willingness to brazenly share our data with attention platforms, such sensitive data is subject to surveillance. But don't delete your Facebook profile just yet, as "good tech companies" — such as CrowdStrike, Cylance, and SentinelOne — are coming to our aid to fight and protect us against such cloud-native surveillance tech. Earlier this month, shares in CrowdStrike — the cyber security company that uncovered Russian hackers inside the servers of the US Democratic National Committee — jumped 97% in their trading debut on the NASDAQ, valuing the California-based cyber security group at $6.8 Billion. Since then, quarterly reports indicate revenues have risen 103% year-on-year to $96.1 Million, primarily due to the growing demand for its expertise in combating malicious cyber hacks. In any case, stay vigilant, as what we deem most crucial to our privacy in everyday life is what surveillance tech seeks to exploit (Read more here).


Source: Tom Gauld (New Scientist), CitizenLab (Hide and Seek Report), Financial Times (NSO Group Technologies), Pew Research Center (Security & Surveillance Report 2015), Pew Research Center (Americans & Cybersecurity)

INTERNET OF THINGS & APIs: The Internet of Things wasn't really a thing

Look, we love our buzzwords as much as you do, but this one has gone on long enough. The Internet of Things (IoT) is one such buzzword that is synonymous with product design, connectivity, infrastructure, and the future. Pretty broad right? To enforce this point, IoT can be simply defined as a network of interconnected digital devices in order to exchange data. Doesn't this sound like the definition for the internet? Effectively the Internet of Things is purely a term of scale, in which the "things" are any device that can be connected to the internet. The issue of scale has resulted in a mass of tech companies -- such as GoogleAppleLGSamsung, and Huawei -- each building and protecting their own IoT solution vertical with which they compete. An example of such verticals that fall into the scope of IoT include automated temperature, lighting, and security controls for your home, or fleet tracking and driver safety controls for a logistics company. For a consumer, having multiple apps to control the functions of their home is no better than using the analogue controls IoT sought to replace. For regulators, ensuring the safety, reliability, standardization and efficiency of each solution has massively hindered the deployment of IoT across the globe.

The assumption that the future of technology relies on faster, better, newer, and more hardware is debatable. Something that big tech companies like Apple are starting to realize. Rather, the future of technology should be centered around machines working together to make magic. How this is achieved is via the gatekeepers enabling the solutions -- Application Programming Interfaces's (APIs). Essentially APIs store and dispense both data and services for hardware and software. Enabling the data source(s), the data consumer(s), and the tech manufacturer(s) the opportunity to compete within the foreign land of tech platforms (i.e., App stores and e-commerce). This generally means prices fall and economic rents go to fewer winners that have strong APIs, integrations, and a nimble balance sheet. Consumer facing services such as ZapierIFTTT, and Signalpattern form part of an emerging segment, allowing for consumers and businesses to connect devices and services together to build truly innovative solutions. Similarly, payments Fintech InstaReM launched an API-based digital B2B platform enabling companies to create their own branded credit cards. Via APIs to InstaReM's card-issuing platform, customers are said to have greater control over the creation, distribution and management of card accounts -- a Visa-supported parallel to Brex.  

For the network of interconnected digital devices in order to exchange data to succeed device manufacturers need to open their APIs, like items on a menu, and users assemble them together into the perfect meal. The level of inter-connectivity we are talking about here is, for example, when the machinery in a factory stops operating whenever a maintenance person swipes into the main floor, or your car's navigation depended on your calendar, financial well-being/budget, and personal well-being (taking scenic routes when stressed). That is truly an internet of API-enabled things. READ MORE.


Source: Nordic APIs (APIs power the Internet of Things)

FINTECH & PAYMENTS: BBVA launches a product that will ‘live’ within a third party’s platform & Uber’s new move looks to restaurants-as-a-service

Three weeks ago, we wrote a story on how Fintechs such as Square and Stripe are prime examples of digital startups that have used their enrolled bases of small merchants to cross-sell other services. Additionally, ride-hailers are starting to take note by replicating this model -- using their extensive base of both drivers and riders to build out their own ecosystems. See here for a refresher.

Turns out we could have been closer to the truth. As a new alliance between car-hailing giant Uber and digital bank BBVA seeks to leverage the potential of open banking to enhance financial service provision to Uber's Mexico-based drivers and delivery partners and their families. Essentially, the Uber application becomes the interface through which the aforementioned users can open a BBVA digital account linked to Uber's worldwide 'Driver Partner Debit Card,' allowing family members to receive instant access to earnings made by the driver, without the need of costly international money transfers. Additionally, the benefits of offering a centralized and aggregated platform to drivers and their families means the collected data can be used to offer financial benefits such as loans and insurance, as well as, non-financial benefits such as loyalty rewards, discounts, and subsidized purchases. A smart move if you ask us, especially knowing that Uber is currently incurring card processing fees of around $749 million (2017) to get paid and pay its drivers.

On another note, this last week Uber announced the launch of a dine-in option to its UberEats app – this feature lets users order food ahead of time, go to the restaurant, and then sit down inside to eat. Adding Dine-In lets Uber Eats insert itself into more food transactions, expand to restaurants that care about presentation and don’t do delivery and avoid paying drivers while earning low-overhead revenue. And now that Uber Eats does delivery, take-out and dine-in, it’d make perfect sense to offer traditional restaurant reservations through the app as well. This move pits the on-demand food app directly against OpenTable, Resy and Yelp. Similarly, instead of focusing on a single use-case of on-demand food delivery -- exposing the company to the risk of heavy competition -- appealing to a niche demographic requiring such services, Uber Eats’ strategy is to own the digital service aligned to the impatient and hungry customer.

By changing gears to offer its drivers more perks and job security through the BBVA partnership, as well as, embedding functionalities that promote customer, user, and employee experiences, it’s only a matter of time before Uber launches a fully functional financial suite allowing for users to make payments, customers to maximise profits, drivers to maximise earning potential, and the incentives across the application to cater to a wider demographic as its competitors. It's always better to be a product than a feature.


Source: El Sol De Mexico (website), Techcrunch (Uber dine-in)

ROBOADVISORS & DIGITAL WEALTH: Artificial intelligence battles in financial markets but conquers in cryptocurrencies

It has become commonplace for users of online platforms to expect that their attention i.e. time spent using the platform, converts to loyalty -- in the form of an artificial intelligence algorithm that knows them better over time e.g. auto-populating search fields, recommending preferred clothes to wear, books to read, or food to eat. Yet, when it comes to applying such sophisticated algorithms to financial markets, why aren't such quant funds always outperforming the market?

Artificial Intelligence is most useful where the problem set is narrowly defined, i.e., it is well known what is being optimized and how, and where the fuzzy data needs the structuring at scale that AI provides. A narrowly defined problem may be – given this particular set of personal characteristics about a person, should they be allowed to borrow this particular amount of money based on prior examples. A poorly defined problem may be – predict the price of a stock tomorrow given thousands of inter-correlated data points and their price history. It all boils down to the reliance of quant investment strategies reliance on pattern recognition: models look to correlate past periods of superior returns with specific factors including value, size, volatility, yield, quality and momentum. Such approaches have several fundamental weaknesses: (1) hindsight bias — the belief that understanding the past allows the future to be predicted, (2) ergodicity -- the lack of a truly representative data sample used in the model, and (3) overfitting --  when a model tries to predict a trend in data that is too noisy i.e. too many parameters or factors. Logically, over time the anomalies that these quant strategies are relied upon to exploit should dissipate, given the swift pace at which technology, competitors, and data moves to correct such anomalies. This is not stopping the likes of augmented analyst platform Kensho (acquired by S&P Global for $550 million), crowdsourced machine learning hedge fund Numerai, and the industry-leading quantamental funds of BlackRock. There is an inherent contradiction in that the approach exploits inefficiencies, but requires market efficiency to realign prices to generate returns.

With Cryptocurrencies, the strategies are different. Native Cryptocurrencies i.e. Ether and Bitcoin, are considered unconstrained assets, with limited correlations to other assets. Additionally, the data sets and factors that need to be considered when trading Cryptocurrencies are far fewer — many of which are speculative and co-dependent, resulting in far more predictable patterns than in financial markets. Because most of Cryptocurrency trading is autonomously and algorithmically driven, patterns are more easily discernible and human trading behavior often sticks out in stark contrast to established market behavior.The issue of course is not the opportunity to profit — it’s the magnitude of such profits. Currently, Cryptocurrencies simply do not have the volume and liquidity necessary for autonomous trading strategies to be deployed in large quantums. Percentage returns for algorithmic Cryptocurrency trading may be significant, but beyond certain volumes, especially when assets under management start approaching the hundreds of millions of dollars, traders need to get far more creative and circumspect in deploying funds as the opportunities are far fewer at larger order sizes.

For now at least, AI and machine learning are still some ways away from consistently beating the financial markets, but with a bit of tweaking they may be a lot closer to beating the Cryptocurrency markets. Evidence of this is already beginning to show -- in 2018 Swiss asset manager GAM's Systematic Cantab quant fund lost 23.1 percent, as well as, Neuberger Berman is considering closing their factor investing quant fund over poor performance. All this whilst Cryptocurrency quant funds returned on average 8% over the same period. While the prospect of searching for phantom signals that eventually disappear could dissuade some people from working in finance or Cryptocurrency trading — the lure of solving tough problems coupled with the potential to dip into the $200 billion opportunity means that there will always be more than enough people who will try.


Source: Autonomous NEXT Keystone Deck (Augmented Commerce), PWC (2019 Crypto Hedge Fund Report)

PAYMENTS: E-Commerce sales growing at a "solid" 12.4% vs. Retail's 2%. What is driving this?

Last week was made great by the release of Mary Meeker's Internet Trends report. If you haven't seen the 2019 version yet, what are you waiting for? Time to read 334 slides in 30 minutes. The key takeaway we remember from last year was the broad digitization of commerce, with E-commerce living in the web and in our mobile apps, plus the augmentation of the physical space with embedded digital commerce. See entry 1 above. 

Ecommerce is still very much a highlight of this report. Specifically, the fact that US ecommerce sales growth is noted as being “solid”, reaching 12.4% year-on-year growth in Q1 of 2019, up from 12.1% in Q4 2018. Similarly, physical retail sales are noted as “solid”, albeit growing more conservatively at 2%. Additionally, customer acquisition costs were found to be rising to unsustainable levels.

What we found most interesting about the reported ecommerce growth in 2019, is its sources where not only from the expected channels i.e., offline sales shifting to online, or search-directed sales on ecommerce websites. Rather, Meeker’s report tells a story of retail becoming a feature that is integrated into apps and services of every kind, and ecommerce reaching new communities and demographics: (1) Social apps -- like Kakao, Line, and Instagram are increasingly integrating transaction and ecommerce features. The monetisation of features embedded in large scale attention platforms makes sense.(2) Ecommerce platforms are making delivery a focal point of their offering. Much of the friction on these platforms lies in the delivery phase of the customer's journey with either cost or time creating negative experiences. Data-driven and direct fulfilment is growing rapidly with agile and low cost third-party platforms -- such as Rappi -- helping to remove such friction points. Enabling local merchants to expand their online presence, and improve access of their ecommerce platform to customers in entirely new and traditionally inaccessible markets. (3) Online grocery formats in China are competing for consumer wallet share. Here, Meeker showcases the sheer variety of grocery retailers competing using different formats for customers to access them i.e., digital-only stores, physical stores with a native digital app, digital-only stores that leverage a franchised community of retail partners to provide the goods and deliver.

It's always good to know we were right. As our 2019 predictions state "customer acquisition costs will rise and the digital model will become more competitive as servicing costs commoditize at a cheaper price point. What we mean is that if everyone -- including large operating businesses -- will understand how to market to and serve Millennials, driving away the arbitrage opportunity Fintech companies have had to date". We'll take that!


DIGITAL WEALTH: Schwab abandons desktop wealthtech as industry moves to open banking and investing platforms

We weren't planning to write about traditional wealthtech, but man, it's hard to pick your jaw up from the floor after reading this. Schwab Advisor Services, a $1 trillion assets under custody business, is selling its desktop portfolio management technology PortfolioCenter (which manages 2,300 advisory firms) to Envestnet for an "immaterial" price. The cost to Schwab of trying to pull those users into the cloud from desktop was higher than giving away the business, which generates about $10 million in revenue. Schwab retains its cloud version of the software, PortfolioConnect, as part of confusingly named AdvisorCenter. Reminder that one of the larger Envestnet shareholders is BlackRock, both a competitor to and manufacturer for Schwab's offering.

Fidelity paid up $250 million to buy eMoney, a cloud-based chassis for digital wealth management in 2015. The industry's conclusion was that custodians were going to be providers of technology in a freemium model, giving away tech and making money on capital. The independent wealthtech software houses (Orion, Black Diamond, ENV, AdvisorEngine, SigFig) could be in trouble. The Schwab sale of its client base given the cost of management legacy tech is enlightening. At the core, custodians are horizontal financial product platforms, enabling brands (e.g., RIAs, Cryptofunds) to deliver services to their customers. Sounds a lot like the other things happening in finance, which is open banking and data aggregation platforms building API-first layers. Can't be API-first with a desktop executable file!

So then what does a real platform look like in 2019? One take is something like Plaid, but we've discussed it before. Instead, take a look at Cambr. A joint venture between a community banking private equity firm (Stone Castle) and a core processing company (Q2), deposit products into tech apps are one integration away. Another version of a conceptually similar play is DiFi -- Digital Financial, previously Market76. Or, if we go one level down, every single bank participating in European open banking initiatives is becoming a financial product platform. See the awesome ranking Innopay has done of these below. And last, Apple itself. The hardware maker owns a massive attention and payments footprint, and is enabling none other than Goldman Sachs to launch a credit card. Apple is the platform, Goldman is the brand. We can see why Portfolio Center isn't super exciting. 


Source: RIA Biz (Schwab sale), Schwab website, Fintech Platforms (CambrDiFi), WSJ (Apple & GS), Innopay

ONLINE BANK: Lessons from Monzo's annual report and £33M losses

We love unfair comparisons, but there's a reason behind the madness. Crypto currency exchange Binance is on track to print $1 billion in profits this year, while neobank Monzo has a £33 million loss to show for its £109 million in venture funding. Here's another one: Coinbase now has about $20 billion in addressable (custodied?) assets, while Monzo has £71 million (<£150 per account). One way to think about these companies is (1) store of value in crypto currency, vs (2) facilitating payments and commerce via fiat. And in this way the comparison evens out. The crypto companies to date have failed in making BTC a medium exchange, instead choosing to take economic rents through capital markets. The neobanks have hit the wall of trying to get profitable at scale, though Monzo's 750,000 users and £2 billion in facilitated payments transactions points the way. Looking at Revolut, we see about 2.2 million users and $18.5 billion of transaction volume. That's a medium of exchange story.

Two more thoughts on neobanks. The burn should slow down and economics seem likely to improve. On the revenue side, consider that most of the neobanks (Monzo included) started out as pre-paid cards that you load, with a nice mobile interface. That's pure cost, because the Fintech has to pay a third-party for each card while making no revenue of any kind. So Monzo's conversion from pre-paid card to current account under a banking license matters, because they can actually make spread revenue on deposits. On the cost side, the neobank claims to have reduced the cost of maintaining an account from  £65 to £15 -- pretty good operating leverage, but for the upfront cost of acquiring the customer. Since the market is crowded (Revolut, Starling, N26, B Bank, Finn, etc.), we expect venture funding to continue fueling the turf war.

And second, the implementation of Open Banking may not be going according to plan. As a reminder, European legislation PSD2 is supposed to expose incumbent banking data via structured APIs to third parties that want to build upon banking information and money movement. In theory, this lowers the stickiness of bank accounts, allows data to travel safely into aggregators and apps, and lays the groundwork for financial bots and agents that make shopping decisions. Surely, neobanks would benefit from the ability to see and move these traditional assets. Well, maybe not. According to blog Open Banking Space, major barriers stand in the way erected by incumbents: "(1) lack of rich data or functionality on the account information APIs, (2) a regressive method coupled with very poor authorisation journeys on the banks’ platforms, (3) technical challenges such as that posed by a lack of immutable transaction IDs’, and (4) the absence of any bank-provided, data rich testing environments." Who will get blamed for this end of the day? The apps trying to build experiences, not the incumbents. But if you don't want to deal with incumbent infrastructure, there is always Bitcoin. 


Source: Problems in Open Banking, Monzo (current accountsAnnual Report), Coin Telegraph (Binance), Treasury XL (PSD2)

ARTIFICIAL INTELLIGENCE: Machine Readable Regulations


We started with two difficult entries to highlight how the major platform shift technologies, blockchain and AI, are bringing out some of the worst impulses in human beings to take advantage of each other. And further, these tendencies become enshrined in software -- from decisions learned out of data, to bots endlessly begging to steal your money. From this perspective we pivot to Regtech, and in particular to projects that we think could be antidotes for the malaise.

The first is an effort by the FCA to explore offering regulations in a machine readable format. That means that a regulator would provide standards and perhaps even executable code that could plug into Fintech software stacks. Imagine Python's Django, but with a regulatory module that pre-packages data formats for compliant reporting. Similar ideas have been floated by self-regulatory organizations in Crypto, looking to build into tokens the ability to determine regulatory requirements, like accredited investor status or KYC/AML. But to do this at the level of the regulator is far more meaningful because (a) there is way more law that needs to be translated, which relates to real rather than imagined economic activity, and (b) this regulation is a result of an established governance process, which is still immature in decentralized communities. Imagine putting all of the FCA on Github and satisfying requirements through something like the Digital Asset Modeling Language. Compliance costs would actually become trivial.

But now is a moment of transition. Case in point, last week we attended the fifth London cohort of the Barclays Techstars, where a RegTech startup called Audit XPRT introduced their automated audit and compliance solution that uses machine learning to extract structured rules from unstructured paper documents. The aspiration is to reduce compliance-related costs ($270 billion) by 90% and achieve 5 months of work in 5 minutes. Another example is Governor, which creates dashboards of real-time tracking across Risk, Compliance and Corporate Governance. Or take Suade, which tags existing data with an overlay that maps to regulatory requirements and provides apps out of the box against which the data can be checked, no disruption to the bank’s current architecture. It may feel slow, but the law's getting digital.


Source: Github (Ethereum proposals), FCA (machine readable initiative), Digital Asset (DAML), Thomson Reuters/Tabb Forum (Infographic), SuadeGovernor (infographic), AuditXPRT

REGULATION: Wells Fargo Forbidden From Growing by Federal Reserve

Source: CNN Money

Source: CNN Money

In the legal tradition, civil courts can do one of two things: (a) make a party pay damages for injury resulting from a particular action by that party, or (b) prevent the party from taking an action in the first place through an injunction. Meaning, they can make you pay for your mistakes with money, or put you in time-out. The Federal Reserve has just put the entirety of Wells Fargo in time out by forbidding it from growing until it fixes the mistakes that led to its scandals (like opening 2 million fake accounts, aggressive sales tactics, etc). Wells has already paid $185 million in fines, so this is a cherry on top. The firm can add no more assets over the level it had at end of 2017.

This move is a potent reminder of sovereign power, and how it could be effectively used. All this noise about scams, fraud, crypto, and Ponzi schemes -- all this can hit a wall. Every exchange can be shut down. Every bank can be unlicensed. Sovereigns have teeth, and they should not be afraid to use them (for the right reasons of course). This is far easier to do with well regulated centralized entities, like one of the world's largest public banks; decentralized crypto may survive even such an attack. Other examples of sovereign power can be seen in the transformative European legislation of PSD2GDPR and MiFID II. These regulations force open bank data into accessible APIs that support fintech, create a personal right to be forgotten that forces a company holding your data to delete it, and separate investment research from trading to prevent inducements. 

Similar force could be used to deal with propaganda bots and the overreach of the big tech companies. We know that GAFA are dealing with millions of fake accounts (not unlike Wells). But these accounts manipulate information, public opinion, commercial outcomes and financial investment. From this point of view, Facebook's block of crypto-related ads is self protection, trying to prevent the system from being coopted for financial manipulation and regulatory response. See how the New York state Attorney General is going after the firm that manufactured fake accounts. We can also look at the healthcare alliance between Amazon, JP Morgan and Berkshire in this light -- a way to start remedying social unrest resulting from automation and increasing concentration of wealth, a first step to universal income.

One solution is fairly simple. Until Facebook, Google/Youtube and Twitter get their social news problems under control, they could be restricted from adding new accounts over the level of 2017 year end. Now that would be one way to fix the attention economy.

OPEN BANKING: Regtech as Point of the Spear

Source: Latham Watkins, IFLR

Source: Latham Watkins, IFLR

We really enjoyed the International Financial Law Review conference on Fintech in Europe. It was refreshing, surprisingly, to hear about innovation from the point of view of the lawyers, who focused much more on the nuts and bolts of deploying technology in a highly regulated market. Knowing the Fintech sandbox can save years of wrong-headed effort. We highly recommend you review the notes from the sessions.

A couple of conversations stuck with us. First, you are likely familiar with PSD2, which is forcing banks in Europe to adopt an open-API approach to customer payment data and access. But, although PSD2 would enable Fintech companies to get data from APIs, it impedes screenscraping and requires data protection. This could be a net loss for startups according to Davis Polk and neobank Monzo. Separately, everyone agreed that Regtech as a category will only be successful if its startups solve real problems, and that those startups should be led by a team that has industry experience and knowledge, and not just hustlers. Lastly, the conversation around intellectual property that startups own pointed to a key issue in Fintech. How many startups that focus on customer experience actually have a patent? Are they missing out, or do they just not have any valuable intellectual property (and are therefore not defensible in the long run)?