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

September 26, 2019

Vantage: OakNorth

Tell us more about OakNorth including what makes your vision unique?

OakNorth is the next-generation credit platform that is redefining lending to lower mid-market businesses globally.

Historically, there’s been a massive focus on tech efficiency within the retail banking space, and a massive focus on people within the corporate and large business banking spaces.

As a result, the segment of the market that we focus on (the lower mid-market where loan sizes are typically between $1m-$25m) has been overlooked and underserved for decades.

The platform helps our bank and lending partners to more holistically and profitably cater to this market segment. It supplements the traditional method of relying on backward-looking historical data sourced from the borrower, and scenario analysis based on standard haircuts that are not necessarily linked to industry drivers (Level 1 and 2 analysis), with technology and massive data sets, to model a forward-looking view that’s informed by industry benchmarks, macroeconomic drivers, and scenario analysis specific to each business (Level 3 and 4 analysis).

Within the UK, we use the platform to do our own balance sheet lending (via OakNorth Bank), and throughout the rest of the world, we license it to other banks and lenders such as NIBC Bank in the Netherlands, so that they can replicate our success with SME lending in the UK, in their own markets.

Since its inception, the business has secured over $1bn from leading investors, including: Clermont Group, Coltrane, EDBI of Singapore, GIC, Indiabulls, NIBC, Toscafund, and SoftBank’s Vision Fund.

The business was founded by Rishi Khosla and Joel Perlman who were inspired to launch the business following the challenges they faced in securing debt finance from high street banks for their previous business, Copal Amba.

What have been the key drivers of OakNorth’s high growth trajectory over the past few years? 

A clear and focused proposition that genuinely addresses an unmet market need, a world-class team who believe in the mission and the vision and genuinely care about fixing lower mid-market business lending globally, and world-class technology (superficially the application of machine learning and big data)  to deliver that proposition, and of course, incredible support from both our investors and our customers.

How has OakNorth’s communication and PR strategy evolved as the business has scaled? 

Before we launched, had any clients, or had proven our proposition, our strategy was focused on promoting our strengths as a lender and highlighting how there is an unmet market need. So, we talked about our banking license, the strength of our board and executive team, our tech stack and why the SME lending market is ripe for disruption.

Once we launched and started to build our loan book, our focus moved much more to promoting the transactions we were doing with SMEs and how they were using the finance from us to scale. Over time, as we’ve transacted more and more loans, we’ve had to find ways to still promote them all. This has meant putting processes in place to ensure sign off is as quick and efficient as possible, that we start the PR conversation early and have a press release worked up and signed off so that it’s ready to be issued as soon as the deal closes.

The strategy now also includes promotion of the platform and how this has helped us to build such a successful bank in the UK.

OakNorth is currently in the process of establishing itself in several additional countries, including the US and Singapore. Which have been the most challenging countries to expand into, and why? 

For the Bank, we have offices in London, Manchester, and Gurgaon.

For the platform, we have offices in NYC, London, Singapore, Shanghai, Hong Kong, Gurgaon and Bangalore. Many of these are markets that our founders, Rishi and Joel, had operations in for their previous business (Copal Amba), so they understand the regulatory landscape well, know where to find the best talent, etc. Having experience in news markets or seeking advice from someone does is really important for start-ups to ensure that all bases have been covered before launch.

Everyone knows the positive multiplier effect of lending to SMEs who are the backbone of the economy. New jobs will be created, new homes will be built, and there will be more GDP growth. So, as a business that is helping banks to unlock some of that additional potential and lend to SMEs more effectively, the reception in each market we’ve expanded to has generally been very positive.

OakNorth places emphasis on its lending solutions being custom-built, which typically requires a more manual approach. How does OakNorth balance this with the need to maintain fast set-up times and low costs through automating processes? 

This is exactly what our platform enables us to do – incredibly robust and in-depth underwriting and credit analysis, so that we can structure bespoke debt finance facilities quickly. The platform uses artificial intelligence and machine learning to enable credit papers, the 30-40-page documents that banks’ credit committees use to make informed lending decisions, to be pulled together in days rather than the weeks it would normally take. The platform then proactively monitors the financial and operational data of every borrower in a bank’s portfolio, flagging up any potential issues to assist in reducing the likelihood of a late payment or default in the future.

What element(s) do you think will drive the most growth for OakNorth, and other digital only UK SME lenders, in the next few years? 

Historically, businesses have taken a one-stop shop approach to banking, typically getting all their ancillary products and services (credit cards, loans, savings products, etc.) from their current account provider. However, over the next few years, I think we’re going to see a greater shift to the model that we’re seeing in the retail space – i.e. where people shop around for the best provider for their needs and have products and services from multiple providers.

The key driver of this change is going to come from FinTechs maturing – a lot of SMEs are still reluctant to switch to a challenger brand as they’re less familiar with them, there may be a perception that they’re less secure, etc. However, as FinTechs evolve from the start-ups they are today to mature scale-ups with profits and proven business models, we’ll see more SMEs switching to them.

For OakNorth specifically, our growth in the UK is going to be in our loan book and outside of the UK, it’s going to be in licensing our platform to other banks and lending institutions.

What are some of the key trends that you see to be impacting the FinTech space more widely? 

Collaboration – between FinTechs, between FinTechs and large financial institutions, between large financial institutions and big tech, and possibly even between FinTechs and big tech one day if the FinTechs can reach a scale that makes them interesting enough for big tech to collaborate with.

What advice would you give to growing FinTechs looking to scale? 

Operate from a mindset of frugality and make sure you have a clear business model and path to profitability from the outset.

When a company has too much capital available upfront, it tends to be built on fundamentally bloated cost structures.  Spending more money than is necessary becomes a part of the company’s DNA and changing this is hard. Having little to no money forces businesses to operate from a mentality of scarcity, and these businesses end up operating much more efficiently. Our co-founders, Rishi Khosla and Joel Perlman, started their first business (Copal) with just £40k so even though it was much easier to raise capital to start OakNorth, they still took a very frugal approach, ensuring they didn’t spend a penny more than they absolutely needed to. That has remained their philosophy throughout the OakNorth journey so far and as a result, we’re one of the few unicorns in the world that is profitable.

Written by: 
Valentina Kristensen