March 3, 2021

The perks and dangers of the democratisation of finance

The GameStop / Robinhood saga has dominated the news over recent weeks and provoked some strong reactions across the industry. For FinTech as a whole, the scandal raised some intriguing questions the industry might have to address in the future. In this post, we explore some of the perks and dangers of the democratisation of finance.

The “democratisation” of finance

The FinTech industry is often characterised as disruptive, fast moving, providing innovative solutions and allowing easy access to financial services for consumers as well as businesses. Popular banking apps such as Chime and Monzo have allowed individuals to access a range of banking solutions through a simple click of a button. We have also seen the world of investment and trading opening up to the general public thanks to an array of players such as Revolut, SoFi or Ally Invest. Previously inaccessible financial markets and investment options are now attainable by just about anyone thanks to FinTech.

Companies in this space pride themselves on offering a tailored, personalised and convenient customer experience to users. MoneyFarm, for instance, pledges to “handcraft” investments for its customers, creating a unique profile per investor, customised based on individual investment goals and risk appetite, all the while claiming low fees and adequate protection.

The dangers of inadequate education

The GameStop / Robinhood saga showed us that the “democratisation” of investments through FinTech is not without its share of risk and implications. Opening such nuanced and often risky endeavours to the general public can prove catastrophic if not executed with the adequate knowledge and understanding it requires.

A chilling reminder of the dangers of reckless investment is demonstrated in an advert for online trading platform XTB. While the face of the brand, world-renowned football coach Jose Mourinho showcases the opportunities of online trading with XTB, the small print at the bottom of the screen warns that “79% of retail investor accounts lose money when trading CFDs with this provider”.

One example of the volatility of online trading is the case of high-tech vehicle brand Nikola. Following the hype that was going to make Nikola “the next Tesla”, the start-up’s value more than quadrupled within a couple of months last summer, only to lose most of its value by the end of the year. In this case, the power of internet and social media enabled inexperienced investors to help the company reach spectacular highs as well as lows.

The gamification of investing

In recent years, investment platforms and FinTechs have also increasingly presented customers with a gamified user experience. Interestingly, academics have found that the simplified user interfaces employed by popular “millennial investment apps” could easily compare to those seen in a game, and that users can have a game-like psychological experience when interacting with them.

In Robinhood’s case, a top layer of the app showing strongly performing stocks could entice customers to invest in them who otherwise may not have done so. Not only is investing becoming more “fun” and accessible, but it may also be becoming somewhat addictive for a portion of investors. The recent events surrounding the GameStop stock have illustrated the impact the influx of retail investors who have been attracted to this gamified experience can have on global stock markets.

Reddit’s /r/wallstreetbets community has for several years explicitly promoted treating options trading like a casino, recommending platforms such as Robinhood as an easy and fun way to gamble on the markets. The highs and lows of the GameStop story have likely encouraged many more people to try out investment apps for the first time, and it remains to be seen whether these new investors will fully embrace the riskier elements of /r/wallstreetbets-style day trading. The extent to which these newer customers fully understand that mistakes in this complex environment can have real world financial implications certainly remains unclear.

Striking a difficult balance

Despite the obvious risks involved and amidst the GameStop controversy, Robinhood reiterates its stance towards its principles of laissez faire investment. Its ad at this year’s Super Bowl confirmed to the audience that “we are all investors”, marching on in its quest for new customers. Web communities of the likes of Reddit encouraging group action via slogans such as “underdogs can accomplish just about anything” will have prompted many to get on board.

Amongst the more responsible investment platforms, eToro offers a comprehensive ‘Education’ section on its website, ranging from financial markets guides to blogs, podcasts and tutorials. This education piece is crucial in helping narrow the knowledge gap between Wall Street / City professionals and hobby investors. The option of setting up virtual accounts for users new to try the world of investing is another method of demonstrating the ins and outs of the industry. However, despite some investment platforms also caveating the risks, the emphasis very much remains on the opportunities investing can provide.

As FinTech continues to evolve it will continue to look for the right balance between the opportunities and risks it provides to its customers. The amount of new customers investment platforms continue to attract seems to suggest that they are satisfying a clear demand for such products. However, at the same time, setting up the right guardrails and offering adequate education and support to customers is increasingly important as these FinTech services move from niche to mainstream.

February 1, 2021

The state of FinTech: a recap of 2020 and a glimpse into 2021

2020 was a very challenging year for most industries, and FinTech was no exception. However, the FinTech industry seems to have weathered the storm that continues to ravage the globe. Below we discuss three of the main trends KAE identified as defining for the industry.

Maintained growth & consolidation

Following the outbreak of the pandemic, investment budgets were slashed in most industries as uncertainty began to overshadow strategic planning. Less so in FinTech. Investors seem to have retained their confidence in financial technology as global FinTech investment reached $44 billion in 2020 – an increase of 14% from 2019. Unsurprisingly, the US was the main catalyst of growth, attracting the largest share of capital with $22 billion – up by almost a third from the previous year. More surprisingly, although Brexit seems to have contributed to a 9% year-over-year drop in funding, the UK retained its position as the #1 destination for FinTech investment in Europe.

Consolidation has been an ongoing theme in the industry, and the new challenges of 2020 further accelerated this trend. While lesser known / emerging start-ups continued to struggle to convince venture capital investors, more established FinTechs secured investments of record high value. Visa’s $5.3 billion acquisition of data aggregation start-up Plaid (blocked by US regulators since) and SoFi’s £1.2 billion purchase of banking-as-a-service provider Galileo were prime examples of the high-value M&A activity that dominated the industry. Venture capital also continued to pour into FinTechs sitting at the top of the unicorn’s horn, with Stripe ($850 million), Chime ($700 million) and Klarna ($650 million) raising the highest amount of funding throughout 2020.

Going forward, with the growing size of such deals, regulators are likely to increasingly scrutinize direct takeovers – which could somewhat hinder the pace of consolidation. However, the industry seems to be ahead of the game, with some players focusing on incremental investment in their strategic partners (also referred to as “creep acquisition”) that are more likely to get the green light from regulators. The example of Visa’s ever strengthening partnership with and stake in Klarna is a template many other legacy players could try and emulate in 2021 and beyond, as they strive to maintain their stronghold over the industry.

Riding the waves of the pandemic

The accelerated pace of digitalization we saw throughout every aspect of our personal and business lives is one of the main reasons why the FinTech industry as a whole has withstood the challenges posed by the pandemic. As most of our activity defaulted to remote, FinTechs that cater to this new paradigm saw immense growth.

FinTechs offering online / mobile banking, payments, investment or lending to individuals and / or businesses saw record adoption rates and continued their shift from the periphery to the mainstream. In Europe, FinTech app usage grew by 72% in the direct aftermath of the pandemic outbreak, while the top seven digital banks in the US grew their cumulative user base by 39% throughout the year. Moreover, the boom experienced by e-commerce and m-commerce across the world also helped power the FinTechs that feed off these ecosystems.

While most of us will hope remote is not the new normal, digital is seemingly here to stay – offering a plethora of opportunities for FinTechs to capture. Payments start-ups Deserve and Plastiq, digital banks Upgrade and BlueVine, investment platforms Pagaya and EasyKnock and online lenders LendingPoint and C2FO are currently amongst the fastest growing FinTechs that are gearing up to challenge their more established peers as well as incumbents this year.

Logos sourced from relevant company’s LinkedIn page

Embedded finance

For some time now, offering financial services is not legacy banks’ prerogative anymore. However, businesses whose core focus is outside financial services, have traditionally relied on partner lenders / payment providers to satisfy their customers’ financial needs. Then came a new phenomenon: embedded finance, namely “nonfinancial companies offering financial products and services to their customers while retaining complete control over the customer experience” – a market tipped to be worth $7.2 trillion globally by 2030. So far, Amazon has spearheaded this space, recently extending its lending propositions to cater to not just its merchants but also consumers with its buy-now-pay-later offering. Shopify white-labelling Stripe’s payment acceptance engine is another successful business model others might want to follow. We expect BigTechs and other non-financial giants to join the game soon; and while payments and lending seem to present the clearest opportunities, other types of financial services are likely to be trialled too. FinTechs often have a niche technology that is superior to that of their partners, or offer a fitting complementary service. This represents a win-win proposition: software-as-a-service providers of the likes of Solarisbank, Railsbank, Modulr, Marqeta and Treezor will be more than happy to remain behind the scenes and capitalise on their partner’s vast customer base.

2020 was a tough year and 2021 did not exactly start off on the right foot either. Still, while the FinTech sector is likely to have its casualties, the industry will also produce winners. The flux caused by the pandemic is not just about its threats but also opportunities and their agility puts FinTechs in prime position to capitalize on these. 2021 is shaping up to be another interesting year for the industry.

May 4, 2020

Credit scoring: Going alternative

FinTechs are utilising alternative data to develop fundamentally new approaches to credit scoring

When assessing applicants’ financial reliability, lenders globally have traditionally relied on a limited range of data sources. In the U.S., Canada, the U.K. and Germany, creditworthiness is determined primarily based on credit scores provided by large credit reporting agencies (e.g. Experian, Equifax, SCHUFA). These scores are typically based on the applicant’s recent bank account and payment history, and his/her borrowing and repayment activity, with approval and the terms of the loan, including the loan amount and interest rate, closely tied to the applicant’s credit score. Some other countries, including Brazil and Australia, are also transitioning towards this system based on positive credit scores. In other countries such as France and Japan, lenders focus on employment history and corresponding regular income when determining applicants’ creditworthiness, while outstanding debt and featuring on negative lists tracking unpaid / missed payments often serve as detracting factors.

While these established credit scoring systems typically work well for the more financially active and well-off consumers, large segments of the population globally are unable to prove their creditworthiness through these metrics. For instance, in the U.S. system, those with a limited or no credit history, such as first-time borrowers and non-citizens / non-residents typically fail to build a sufficient credit history or reach a high-enough credit score. Similarly, in France and Japan, those who are not employed full time or do not rely on a single employer for their income (e.g. the self-employed, gig economy workers) might struggle to obtain a loan from their bank. Moreover, these credit scoring systems become significantly less inclusive when applied to developing economies, where large segments of the society remain un- or underbanked, or without official employment income – producing very limited traditional data for lenders to base their credit scoring on.

The accelerating digitalization of transactions is producing an increasing variety and volume of consumer data, extending the pool of information that lenders can potentially use to determine applicants’ creditworthiness. Moreover, the emergence of open banking infrastructures globally has helped facilitate data sharing between industry players, increasing the availability of consumer data. Utilizing machine learning technology, the increasing amount of data that is not necessarily related to applicants’ financial history is now increasingly used to build predictive models assessing creditworthiness.

Traditional lenders and credit bureaus have recently started to extend the pool of data their credit scoring systems rely on, with data such as utility and rent payment history increasingly included in credit reports. On the other hand, some FinTechs have developed fundamentally new approaches to assessing creditworthiness, incorporating a wider variety of data sources.

Improving credit scores through alternative data

One area where innovation has focused on is helping lenders improve loan approval rates by offering supplemental information about their applicants that lack sufficient traditional data.

For instance, U.K. PropTech firm CreditLadder has built a tool enabling customers to use their rent payment history to improve their credit score at Experian and Equifax. Using TrueLayer’s open banking APIs, CreditLadder connects with the applicant’s bank to access their rent payment activity, which is then incorporated into their overall score at the credit bureau.

Aire, another U.K. FinTech, connects with lenders via a real-time API integration, stepping into the online loan application process in case the applicant lacks sufficient data to prove his/her creditworthiness towards the lender. Through a virtual interview, Aire’s machine learning technology assesses the applicant’s financial situation, spending habits, professional background and lifestyle to produce a behavioural profile to support the lender’s decision making. By increasing approval rates without affecting the lender’s risk appetite, Aire has helped its partners distribute over US$10BN worth of credit.

Building alternative credit profiles

Other innovators are focusing on building a more complete profile of applicants that often serve as the sole source of their partnering lenders’ decision making process.

Singapore-based Lenddo uses non-traditional data to help consumers across South-East Asia, Africa and South America without a credit history build a credit profile. Lenddo uses thousands of data points from consumers’ digital footprints, including their social media activity, browsing behaviour, geolocation and other smartphone data to assess their creditworthiness. Since its launch 4 years ago, Lenddo has helped over 5M applicants in 15 countries to access credit from partnering lenders.

Credit Kudos, a U.K. based ‘challenger credit bureau’ enables consumers to utilize their open banking data to build an independent credit report incorporating a wide range of financial data, including the user’s day-to-day banking and payment activity. Following its recent partnership with AI technology firm Cybertonica, Credit Kudos will also be able to incorporate biometrics and behavioural analytics into its algorithms, making its credit scoring systems more robust.

Another limitation of traditional credit scoring systems is that they can typically only be applied locally. One FinTech which is tackling this obstacle is U.S.-based Nova Credit, which uses data from international credit bureaus to help international students and professionals from 8 countries globally to build a ‘credit passport’. Customers are then able to utilise Nova Credit’s partnership network in the U.S. (incl. American Express and IntelliRent) to apply for credit cards, student loans and other lending products.

Lending to the underbanked

While most credit scoring innovators use their algorithms to help other lenders better assess creditworthiness, some FinTechs are using their technology to provide loans directly to consumers.

For instance, U.S.-based start-up Tala offers short term microloans in Kenya, Mexico, India and the Philippines. Given the lack of traditional data in these countries, Tala’s credit scoring algorithms rely largely on the applicant’s phone usage patterns and online activity to decide whether and at what rate to offer a loan. Similarly, mobile app based microlender Branch relies primarily on data from its applicants’ smartphones, analysing their contact lists, GPS information, text and call logs, as well as their interaction with the Branch platform and customer service.

Although alternative lenders using non-traditional data are most widespread in developing countries, access to credit is far from universal in developed countries. Deserve, for instance, offers credit cards to consumers in the U.S. without a credit history or social security number. Instead, Deserve assesses creditworthiness based on the applicant’s bank account activity, with regular income (from any source) and regular on-time payment of bills/rent the main qualifying requirements.

Whether by supplementing traditional credit scoring data, building alternative credit profiles or providing credit directly, these innovative solutions are making credit more accessible and more affordable to previously underserved segments. At the same time, alternative credit scoring systems are also improving risk modelling for existing lenders, making their algorithms that previously relied on traditional data more robust. As machine learning technologies improve by processing more and more data, these predictive models will become increasingly reliable methods of assessing creditworthiness and are likely to be increasingly adopted by both incumbent and alternative lenders.

Written by: 
Matyas Fekete