BNPL and Point-of-Sale Lending

There are over 82M US adults who used buy now, pay later (BNPL) loans in the past 12 months, representing about a third of the credit-active population¹. Many of these consumers use these loans frequently, generating valuable data to help lenders assess risk and expand access to credit.

 

BNPL and slightly larger point-of-sale installment loans are transactional (like a credit card swipe), but they’re underwritten as individual unsecured installment loans. Therefore, a consumer using BNPL or point-of-sale loans could originate several loans per year, which most existing credit models likely view as risky behavior. 

 

TransUnion quickly recognized credit models will most likely need to be updated to treat these trades as a new type of credit obligation — not as multiple, small unsecured installment loans. As traditional scores cannot yet take into account this new form of purchase financing, underwriting models will need plenty of time to adjust to a new product type (the industry hasn’t seen a new product type in recent history). 

 

BNPL and point-of-sale data should provide valuable signals to enhance lending decisions — particularly for relatively younger, often non-prime consumers who use these products. 

 

At this time, with limited and incomplete data, the impact to scores outside of the TransUnion environment (FICO^®, VantageScore^®, generic and custom models) is yet to be determined. However, TransUnion has taken a thoughtful and flexible approach to how point-of-sale data can enter the credit ecosystem to benefit both consumers and financial institutions.

 

By using unique tags and a filtering mechanism within the core credit file, TransUnion will enable point-of-sale data availability on the credit report — but will prevent the tagged data from affecting TransUnion credit scores or attributes within the environment (e.g., VantageScore^® 3.0 and TruVision Trended data) to avoid unexpected or unintended impacts on consumer credit scores.

 

Default delivery of the core credit file will not include any BNPL or point-of-sale data, whether that data is going into generic scores or lenders’ custom models. Current FICO^® Scores and VantageScore^® models will see no impact until these scoring providers choose to incorporate these data after additional analysis. Individual TransUnion customers will each decide when and if they’re ready to incorporate the data into their custom models.

 

Lenders that are ready to use the data can choose to turn “on” the TruVision^TM Point-of-Sale Solution Suite. Lenders with the service “on” will receive TruVision Point-of-Sale Tradelines and/or Point-of-Sale Attributes on their core file delivery, tagged clearly so their models can identify and treat them differently.

 

In the interim, lenders can leverage new TruVision Point-of-Sale Attributes built from the BNPL and point-of-sale data to round out their understandings of consumers’ financial positions with actions like incorporating the number of positive payments into inclusion criteria or including a consumer’s BNPL or point-of-sale balances in debt-to-income calculations.

 

The data will be reported in the Metro 2^® format and follow specific updated guidance published in the Metro 2^® Credit Reporting Resource Guide (CRRG^®) via the Consumer Data Industry Association (CDIA).

 

To maximize the potential financial inclusion impact of these valuable data, the long-term plan is to transition them to the mainstream credit ecosystem. This is TransUnion’s goal, but it will take some patience.

 

For the data to become a default part of the core credit file, key stakeholders must agree they’re ready: FICO^® and VantageScore^®; lenders and others that use models leveraging the credit file; and point-of-sale lenders. Realistically, this may take a couple of years. 

 

TransUnion is committed to clear communication well in advance of this change so all users of our data can prepare.

 

TransUnion has built the unique tags and filtering mechanism — which are ready to use the minute we have critical mass of BNPL data reported. Our TruVision Point-of-Sale Solution Suite includes over 100 attributes we developed to help lenders understand consumers’ BNPL activities.

 

We’re working directly with large, point-of-sale lenders that are committed to furnishing data in a way that helps consumers build credit. Many of these lenders have not reported before and need time to stand up both furnishing and disputes processes. It’s important to get these processes right to better ensure accuracy and protect consumers.

 

We’re excited some BNPL lenders have publicly announced their intentions to report very quickly, and others are not far behind, but a change of this magnitude takes time.

 

 

VantageScore: “Buy now, pay later (BNPL) is helping many consumers access short-term credit for shopping at a time when prices are rising rapidly. BNPL has given access to credit to those consumers who would otherwise not have access through traditional methods. We think adding this data to credit scores may help drive broader financial inclusion and are working rapidly to incorporate this into VantageScore models,” said Silvio Tavares, President and CEO of VantageScore.

 

FICO: “FICO is committed to financial inclusion and expanding credit access by leveraging more data where available and supported by empirical analysis,” said Sally Taylor, Vice President and General Manager of FICO Score. “These are top priorities at FICO, and we look forward to working with TransUnion to determine the best approach for inclusion of BNPL data in the credit file considered by the FICO Score family of products.”

 

TransUnion: “BNPL loan data could be the key to one of the most important financial inclusion opportunities in a generation, helping the 60 million people in the US who have slim or non-existant credit files build credit responsibly. But how the credit reporting industry collects and treats this data may matter more than the data itself,” said Liz Pagel, TransUnion’s SVP of Consumer Lending.

 

 

¹Insider Intelligence, “eMarketer”, June 2023