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How AI Can Help to Hit Outstanding Debts in the Booming BNPL Industry

The growth of Buy Now, Pay Later (BNPL) providers has been phenomenal in recent years. Initially perceived as just a revamp of the traditional point-of-sale (PoS) loan, these platforms are now being recognised for their unique approach to fee calculation and their ability to benefit both merchants and consumers alike. Integrating BNPL as a payment option at checkout promises to improve the customer experience and bring a new perspective to the payments industry. According to Juniper Research, the number of BNPL users is projected to soar to over 900 million by 2027, up from 360 million in 2022.

Despite the increasing popularity of BNPL, the post-Covid survey found that two-thirds of consumers consider it “financially risky.” This perception may be due to the fact that BNPL can lead consumers to overspend, creating a cycle of debt. As of 2021, 60% of consumers reported using BNPL, with clothing, electronics, and furniture as the top three items financed. However, 57% of users regretted their purchases because they were too expensive. On average, consumers using BNPL services owe $883 in debt, and more than half reported falling behind on payments. Given the current financial climate, many people are struggling to manage their finances, which makes it difficult for them to take on more debt.

This situation is a potential concern for the BNPL industry because it could lead to reduced usage and profitability, particularly if borrowing costs increase.

Klarna Has Fuelled Fears About BNPL’s Future

Despite Klarna’s recent 85% down-round, which saw its valuation drop from a peak of $46 billion to a ‘measly’ $6.7 billion, the BNPL industry is far from dead, contrary to what the pessimists estimate. Moreover, the first months of this year show that it’s thriving, with new partnerships and developments emerging and new players entering the game.

Just look at Frasers Group’s announcement of their BNPL product, Frasers Plus, with the support of Tymit, or the first global B2B BNPL solution by Allianz Trade, Two, and Santander CIB, aimed at multinational corporations. And this is in addition to the numerous BNPL providers that secured investments in January to bolster their operations, like Tranch, Tabby, and The demand for BNPL solutions is clearly there, both in the consumer and business sectors.

Yet, despite all the promise and potential, the BNPL industry is still facing its fair share of challenges. In February, the Australian BNPL operator Openpay declared bankruptcy just a few days after reporting a record quarterly profit. This case demonstrates how BNPL players are currently experiencing the full consequences of decisions to raise interest rates and facing negative outcomes as a result of the global economic downturn. To survive, the industry must focus on the basics: product, placement, price, and profit. The latter has been neglected for far too long, and it’s high time BNPL providers put it front and center.

Bad Debt Is Worse Than Stricter Regulation

One of the main challenges the BNPL industry faces is high default rates among consumers and a lack of transparency regarding the actual amount of outstanding debt. Last year, almost a third of UK BNPL consumers said repayments on the loans have become “unmanageable”, and more than 40% borrowed to make repayment. This collective distress is becoming a massive issue for the UK economy. The BNPL customer base in the US is expected to grow by 27% between 2022 and 2025, and their outstanding debt is estimated to hit $15 billion by this time.

Most players use already outdated credit risk assessment methods. So, using Gross Merchandise Value (GMV) as a measure of risk can understate bad debts by as much as 25%. For example, a $100 purchase means that $25 is paid upfront by the borrower – so it should not be measured as a risk. The real loan is $75 over 14-42 days, which is what can go bad. A more accurate method would be to measure net charge-offs as a percentage of average loans outstanding in a given quarter.

Furthermore, incumbent banks also face potential risks from their exposure to the BNPL sector, as they may fund deteriorating books or invest in BNPL-related bonds. It is also possible that BNPL borrowers have a higher propensity to default, but banks lack the data to assess this risk.

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The situation is changing, but not quickly. In December 2021, US agency  Equifax announced its plan to include BNPL loans on credit reports, and Experian and TransUnion followed suit. But credit scoring models (like FICO and VantageScore) are still researching how to incorporate that data into credit scores best.

Meanwhile, regulators are already starting to take notice. A few months ago, the European Union approved new rules to the Consumer Credit Directive to ensure improved assessment of a customer’s ability to repay. The US and other countries are moving in a similar direction. Increased regulatory oversight should be welcomed by the sector as a way to help it grow in a more sustainable way. However, it does not mean that BNPL players must be regulated like banks. This might simply result in a cramped ability to innovate, worse customer experiences, and perhaps even higher costs for borrowers.

AI May Give Way to “Thicken” the Files

Rather than waiting for a regulator, BNPL providers need to take proactive steps to improve their risk assessment processes and implement strict underwriting standards.

Some market players are already turning to fintech partnerships to pursue more efficient and technologically advanced credit scoring methods, including those powered by AI and machine learning. Such data enrichment solutions that allow collecting anonymous behavioural patterns to predict the likelihood of repayment have already emerged on the market.

Despite AI credit scoring solutions advancements, it largely remains the “black box” for traditional banking and lending. This hesitation stems from concerns about the explainability of the results. For instance, lenders in the US and UK may harbour reservations about a credit score that is even partially generated by AI, particularly if it may bring bias to the general model in terms of ethnicity, gender, or even ZIP code.

Consumers who are denied credit have the right to know why their application was rejected and to request that any incorrect or outdated data be amended, which may have contributed to their rejection. For example, if the latest payment of a loan was made but not recorded, a customer can request that TransUnion update their records. However, in the case of AI lending models built on alternative data (including, for instance, digital footprints), customers cannot correct their data if they have taken too many selfies or downloaded too many apps in the gambling category. Some fintech companies already offer solutions to such challenges. For instance,  Zest AI has built an entire business around explaining the results of AI-built models and ensuring that there is no bias embedded.

To effectively address such concerns, lenders, technology providers, and regulators should work together to assess the benefits of introducing models that can be explained from a statistical point of view. Without checking or processing any personal data, AI-driven credit scoring solutions can mitigate the issue of “thin files” and enable the fair evaluation of creditworthiness. It is crucial for demographics such as younger borrowers, migrants, gig-economy workers and other groups who are often marginalized and excluded from traditional credit scoring practices due to limited or non-existent credit history.

The Outlook Seems to Be Optimistic

2023 is shaping up to be a year of significant change for financial services companies, including BNPL providers. The economic landscape is uncertain, and companies have to adapt to changing market demands to succeed. Despite the challenges, the future of BNPL looks promising. Their success depends on their ability to manage risk, improve their products and optimise their unit economics. Those focusing on these key areas will have a better chance of weathering any economic challenges.

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