How to Assess the Quality of Good Alternative Data Source | CredoLab
April 2, 2020
CredoLab's Chief Data Scientist on How Banks and Consumer Lenders Can Leverage Data Analytics for Business and Social Impact
This article is a reiteration of Alternative Data and the Unbanked published by Oliver Wyman. The credit for any value brought by this article goes solely to the original authors, Peter Carroll and Saba Rehmani of Oliver Wyman.
Over the last several years, industry participants have searched for additional reliable data sources that can provide information on a consumer’s ability to honour their financial commitments. Alternative data shows significant potential to improve the status quo by enhancing the accuracy of existing scores (by achieving better risk separation), and by rendering visible many of today’s credit invisibles. Progress will come about through the private sector efforts of established lenders and credit bureaus, as well as the innovations of FinTechs, alternative data vendors and big data analytics firms, operating in the free market. There may also be a limited role for regulatory and/ or legislative initiatives. The end result will be better and fairer access to credit for individuals, with macro benefits for the whole economy
Alternative data may provide additional financial payment information on consumers or otherwise provide information with predictive power; some of the sources of such data are:
- Utilities (gas, water, electricity)
- Telecom (TV, mobile, broadband)
- Property/asset record: including the value of owned assets
- Public records: beyond the limited public records information already found in standard credit reports
- Alternative lending payments (e.g., payday, instalment loan, rent-to-own, buy-here-pay-here auto loans, auto title loans): including both on-time and derogatory payment data
- Demand deposit account (DDA) information: including recurring payroll deposits and payments, average balance, etc.
Why Alternative Data?
Having more alternative data is only valuable if it results in real incremental benefits; in this case, the benefits of using alternative data in addition to traditional bureau data, beyond just technical improvements to the credit score, should flow to both consumers and lenders.
Some of the key benefits that stand out for businesses include:
- Many newly scoreable consumers should ideally now be part of a sufficiently accurate risk-separation pattern that a fraction of them also become lendable. That is, they have to have a score above the cut-offs used by most lenders.
- The increased number of profitable loans to be made consistent with a given risk appetite
- Reduced transaction costs (additional borrower information could reduce the need for manual processes) and lower aggregate credit losses
- A more complete picture of prospective borrowers allowing them to offer competitive interest rates
What makes a great Alternative data source?
The value of alternative data varies by source. Data like rent payments have been shown to be predictive and may be available on many consumers with no credit file (although many landlords now demand credit scores for new tenants!) But the rental market is very fragmented and data are not uniformly reported. Therefore coverage is low. Public records data are available on even more people than those with files at the credit bureaus, so their coverage is very wide. However, since the information contained in public records is not explicitly focused on payments, it is not as predictive as credit bureau data; nevertheless, it also proves to be additive in scores developed from combined data sources.
The main characteristics of a good source of alternative data are these:
- Coverage: An alternative data source should have broad and consistent coverage.
- Specificity: The source should provide information specifically about the individual.
- Accuracy and timeliness: Alternative credit data must be accurate and current or frequently updated.
- Predictive power: The information from the source should be relevant to the behaviour being predicted.
- Orthogonality: Ideally, alternative credit data should complement traditional credit bureau data.
- Regulatory compliance: Alternative credit data sources must comply with existing financial regulations.
See how CredoLab’s smartphone metadata-based digital scorecards fares against each of these characteristics.
Looking Ahead: Embracing Alternative Data
According to a TransUnion survey, 34% of lenders already use some types of alternative data to evaluate both prime and nonprime borrowers. The use of alternative data is most prominent in credit card, auto loans, and consumer finance, as well as in the FinTech world but there are also signs of early adoption in the mortgage industry. 66% of lenders surveyed reported that they were able to lend to additional borrowers in their current markets and 56% reported access to new markets by using alternative data.
Major credit bureaus (Experian, Equifax, and TransUnion) are already starting to incorporate alternative data within their databases, through acquisitions and/or partnerships. Being a free market, lenders and data sources will surely work towards more widespread use of alternative data—after all, it opens new profit pools for both parties. However, the social benefits of using alternative data may be significant enough to warrant the use of legislation to accelerate the pace of adoption by mandating the reporting of selected alternative data.