What is “alternative data”?

Alternative data is defined by what it is not. It is essentially any dataset on a consumer’s spending, borrowing and savings habits which falls outside of the historically tracked credit information that would show up on a credit report.

This definition of “alternative data” includes BNPL transaction data. Although pay later or pay-in-four models have been around for a long time, the information on these transactions has been disparate and hard to track. Since BNPL fintechs have established a foothold through the expansion of e-commerce, and made it easier for consumers to access this method of payment, BNPL data have become a key indicator of everyday consumer behaviour.

Why is it useful?

The insights into spending behaviour that come from BNPL transaction data are in many cases superior to those that can be gleaned from traditional credit sources:

The wide adoption of BNPL across different segments of the population, including consumers with a thin credit file, distinguishes BNPL transaction data as particularly useful for illuminating credit behaviour across social demographics.

The high frequency and recency of BNPL transactions reflect a consumers’ true and fluctuating financial position more accurately than "big ticket" spending (such as credit card usage for flights or holidays, or mortgage and autofinance repayments).

Who is it useful for?

Information on BNPL transaction history is most useful for BNPL lenders, as it is a direct comparison for the type of loans that they would offer to a consumer (in other words, how a consumer repays their BNPL loans is of greater relevance than how a consumer repays their car loan or mortgage). However, it also offers powerful insights for other lenders. A richer dataset for lenders, which includes a payment history for consumers with a thin file, provides a clearer understanding of how a consumer’s spending could impact their future ability to pay. And not to be forgotten: policymakers and consumer protection advocates who need to understand how BNPL is being used in the economy, which is particularly important now that BNPL represents a growing share of a consumer’s credit usage.

What are other insights and benefits of BNPL transaction information?

• Accessible and trustworthy reporting of BNPL transaction data will address the fear surrounding “phantom debt” - a popular name for BNPL debt which is not visible on a credit report. Better transparency regarding BNPL spending histories will benefit policymakers and lenders alike.

• BNPL transactions are instalment loans, but they give daily spending insights. BNPL data show fluctuations in spending behaviour in far more useful detail than traditional instalment loans, which are predictable and recurring. A deeper understanding of how consumers want to spread their spending can be gleaned from BNPL usage. BNPL data is a key indicator of a consumer’s spending habits and financial position, and can also provide insights into discretionary spending behaviour and debt levels.

• This information can cut through otherwise inscrutable demographic data on thin file consumers who have not met the high hurdle of establishing a robust credit profile. With BNPL, spending data is readily available for analysis after only a few weeks or months.

• In scoring, a recent FICO study was reported to show that alternative data improve the performance of credit scoring algorithms: the combination of both alternative and traditional data allowed for more accurate scoring than the use of traditional data alone.

Of course, for any of the above benefits to materialise, the BNPL dataset must be trustworthy, accurate and up-to-date. Qlarifi is building a platform to aggregate and organise this data so that it can unlock BNPL spending insights for lenders, policymakers and consumers alike.