State of play: the future of credit
Each month, Philip Benton, Principal Fintech Analyst at Omdia, explores a new topic and assesses the “state of play”, providing an analysis and understanding of the market landscape.
Alternative data sources are going to be fundamental in ensuring the future of credit is affordable, inclusive, and accessible
This month, Philip takes an in-depth look at the future of credit.
I’ve touched upon alternative credit solutions in the past with a deep dive on buy now, pay later (BNPL) in a previous column, but I wanted to take a broader approach for this month’s ‘state of play’ and discuss the importance of alternative data in relation to the future of credit.
Credit cards dominate unsecured lending
Credit cards have been the dominant method of unsecured lending for decades, and according to the Bank of England, credit cards typically represent three quarters of total consumer lending in the UK.
However, credit cards still exclude many customer segments from accessing credit, which has forced consumers to seek out alternative means of borrowing through ‘shadow credit’ (also known as unregulated credit), which historically was payday loans and the like, but more recently is BNPL.
The emergence of BNPL, for all its criticism, has forced banks, regulators, and the wider ecosystem to reassess what the future of credit should look like and how to ensure accessibility and inclusivity while growing economies into prosperous and sustainable societies.
Flexibility and inclusivity are fundamental to the future of credit
Flexibility of credit is key both in terms of the type of credit that is given and how it is priced to the consumer or business. Long gone are the days when banks were incentivised to profit from consumers getting into unmanageable debt cycles (charging high fees for overdrafts or revolving credit-card balances, for example). It is in everyone’s interest to support customers in challenging macroeconomic situations, and they will repay your trust with loyalty in the good times. Retail banks tend to agree as flexible loans was the top-ranked product development priority for 20% of respondents in Omdia’s 2024 Retail Banks IT Enterprise Insights study.
The popularity of BNPL has brought into question the relevance and accuracy of credit models and credit scores in existence today and highlighted that some consumers and businesses are unfairly rejected in their credit applications because of a lack of traditional credit history. As well as the BNPL sector, which has brought a new perspective into the world of credit, there has been an emergence of new challengers in the credit card space that are utilising alternative data sources to offer credit to an untapped segment of the market.
Pillar, yet to officially launch, is targeting the immigrant community, who typically find it difficult to build up their credit scores when setting up in a new country, with credit score data not easily shared across geographies. Similarly, US start-up Petal, which was acquired by Empower Finance earlier this year, reimagines a user’s credit score using their banking data and by considering other data points to offer credit to those who are often overlooked by legacy banks – it claims that more than 40% of new members approved for a Petal card in 2021 were first denied credit by a major bank.
Alternative credit requires alternative data
As well as surprising the regulators, the rise of BNPL has also surprised traditional credit bureaus, which have only recently started to factor BNPL payments into their credit reporting. Credit reporting and credit scoring vary hugely around the world and how BNPL is recorded is not consistent either, with a new type of model required to calculate BNPL’s impact on credit scores.
The quality of data submitted varies, and not all BNPL providers report to every credit reference bureau, with short-term, no-interest loans not broadly reported. Only larger-value and longer-term BNPL loans are consistently reported and appear on consumer credit reports as revolving or installment lines of credit according to Equifax, as reported by Payments Dive.
Affirm, the US BNPL provider, announced a partnership with data analytics company FICO to build a “first-of-its-kind” credit scoring model that would enable BNPL loans to be consistently and transparently factored into credit and lending decisions to be reported to the credit reporting agencies. Affirm has yet to share more details until the new scoring model is ready, but it’s a step in the right direction if consumers’ full debt history is to be factored into all credit lending decisions.
UK open banking-powered start-up BuildMyCreditScore says users have seen an average 52 point increase in their credit scores in their first few months since using its debit card. While the debit card works instantly like a regular bank card, the money – up to a daily cap of £30 per day – is collected via Direct Debit by BuildMyCreditScore around two working days after, allowing it to be reported to credit reference agencies. As a result, cardholders are able to build their credit score by demonstrating their ability to manage rolling outgoings and repay credit promptly.
AI is key to the future of credit
AI has been influential in credit decisions for many years. Machine learning (ML) models can now quickly incorporate internal, alternative, and credit bureau data, credit attributes, and other scores to give you a more accurate view of an applicant’s creditworthiness. ML models can also use additional types of data to score applicants who do not qualify for a score from traditional models.
For example, credit bureau TransUnion has unveiled a cloud-based, AI-powered data and analytics platform, OneTru, which connects separate data and analytic assets built for credit risk, marketing, and fraud prevention and connects them in a single-layer unified environment. OneTru’s AI capabilities will enable graphs that improve identity resolution for fraud use cases by linking structured data, like traditional offline identities, and unstructured data, like behavioral information and device properties.
Aside from credit scoring, loan origination is also a prime use case for AI. US fintech Cascading AI launched Casca, its AI-native loan origination system, which can automate much of the loan application process—traditionally a manual-intensive process. The fintech employs an AI loan assistant, Sarah, who can guide applicants through the entire application process. Cascading AI claims Casca is already showing results by achieving nearly three times higher conversion rates and reducing manual effort in the back office by 90% compared to traditional methods.
Similarly, Australian start-up Rich Data Co (RDC) launched an AI decisioning platform for bank business lending. Founded in 2016, RDC uses explainable AI to give banks deeper insights into borrower behavior, enabling more accurate and efficient business lending decisions, with Westpac as a marquee client. Harnessing alternative data sources, RDC’s AI decisioning platform provides insights into borrower behavior beyond traditional credit sources.
Like fraud detection and mitigation, the complexities and potential negative implications of using GenAI for credit scoring and loan analysis mean that predictive AI is still the dominant use case. Omdia forecasts AI software revenue for credit scoring and loan analysis to reach $409 million by 2028, with a CAGR of 16% over the 2023–28 period.
Reimagining credit in the ‘open data’ era
Credit, like many areas of financial services, was imagined at a time when the process was highly manual with static lending rules. It’s clear that credit scores and affordability need to be re-imagined through a combination of open banking, AI, and transparency. The main issue with BNPL is the frequency of payments – a typical customer may only use BNPL 10 times a year, whereas a credit card could generate hundreds of transactions, so there is much more reliable data to pull and assess the liquid frequency of a customer and conduct affordability checks.
As we embrace a new world of open finance where data is more freely available, alternative data sources are going to be fundamental to unlocking new segments of the market and ensuring the future of credit is affordable, inclusive, and accessible.
About the author
Philip Benton is a Principal Fintech Analyst at Omdia and writes analysis on the issues driving technological change in financial services. Prior to Omdia, he led consumer trends research in retail and payments at strategic market research firm Euromonitor.
In this column, Philip will discuss the technological implications and consumer expectations of the latest fintech trends.
You can find more of Philip’s views on fintech via LinkedIn or follow him on X @bentonfintech.
