We find ourselves in an era of widespread financial exclusion.
More than half of Americans are effectively shut out of the financial system because they have a credit score that is considered subprime. Why do we continue to think it is acceptable to turn a blind eye to over half of our country, instead of rethinking decades-old processes?
The black-box algorithms that compute credit scores incorporate hundreds of data points. But as an industry, we seem to have accepted that a lot of predictive data is left out. We applaud that VantageScore 3 and 4 and FICO 9 include utility payments and rental payments in their algorithm (when available) in consumers’ traditional credit files. Yet there are still instances where some rent, mobile phone and utility payments histories are excluded from scores, even though these can be some of the largest and most frequent payments a person will make today.
So, if a credit score is meant to be indicative of someone’s creditworthiness — and if it’s one of the primary pieces of information upon which the financial industry makes lending and credit decisions — it stands to reason that more of consumers’ regular and typical payment obligations ought to be considered.
For half of America, the fact that this information is not reported is not an issue — they pay these regular bills via credit card anyway, meaning these expenses are already reported to the bureaus and impact their scores. But what happens for the other half of Americans who pay in cash or might not have a credit card? It is no surprise that the exclusion of readily available data from today’s traditional credit score calculations is a direct contributor to financial exclusion today — the reason half of Americans are shut out.
But thankfully, modeling capabilities and machine learning are becoming more accessible and acceptable, and they can easily support the use of multiple data sources.
Some lenders, particularly fintechs, are supplementing traditional data with new data sources to make more informed lending decisions. And the bureaus have taken notice, too. For example,
And that’s just the tip of the iceberg. Lenders and the credit bureaus should consider another worthy data point: short-term loans.
Recently, a leading credit bureau simulated credit scores, using LendUp data, to study the impact that including repayment history for short-term loans could have on a consumer’s credit score.
The results were compelling. The research found that 85% of people would have a higher credit score if short-term loan repayment data were included in credit reports. In fact, 15% would go from having subprime scores to near-prime scores.
This is a huge market that financial institutions are leaving on the table to further financial inclusion and expand their borrowing base, and it represents a sizable opportunity for the credit bureaus to expand their data offerings to financial services clients.
At the same time, we asked our borrowers whether they would want their short-term-loan repayment history included in traditional credit scores, and 72% said it should.
From this vantage point, it appears to be a rare and clear win-win-win: good for borrowers, good for financial services providers and good for the credit bureaus. And as digital financial services proliferate, it becomes simpler for the bureaus to accept this kind of data. Meanwhile, newer alternative data credit bureaus that focus more heavily on nonbank credit histories can provide a broader view for lenders and creditors — and help greatly expand financial inclusion.
But until more data sources providing nonbank payment information become part of traditional credit score calculations, consumers will continue to pay their debts on time without an opportunity to increase their scores. Consumers with poor credit scores who need credit will continue to be limited to fewer choices for their financial services, while banks and lenders miss out on creditworthy borrowers.
The reality is that the more this data is reported and included, the more confident lenders can be in their underwriting. And, more important, incorporating additional data can help provide the 56% of Americans with subprime credit scores with the opportunity to improve their credit and access more affordable credit options.
