Part 2: Alternative Data – Casting a Wider Net to Unleash Improved Credit-Scoring by Ron Whyte
Opening up credit scoring to a wider and more diverse set of data improves decision making on many levels. When basing decisions on a more complete picture, the data is required to be inherently more timely and accurate. When looking to alternative data sources, one needs to look at the speed at which the data is reported. Lags in reporting can create gaps. By automating the collection through network-sourced data, lenders can get data in real time. Moreover, new data sources may come with a potentially richer array of attributes.
In addition, there is also a strong security aspect to sourcing data from multiple sources in real-time. That’s because data remains dispersed rather than centrally consolidated where it could be exposed to a breach. Maintaining a decentralized ecosystem does not eradicate hacking, but stealing data one query or one provider at a time is less attractive to fraudsters.
Open-up to Sharing
Migrating to an automated data collection and analysis methodology will require firms to adopt new processes. Constructing a network of data sources, cross-referenced with consumer permissions, will require broad consensus among many players – banks, lenders, fintech innovators, consumer advocates, and legislators. While some financial institutions have shown reluctance to open their records to third parties – even with their customer permission – legislative and customer demands may force their hand. In Europe, initiatives like the second payment services directive (PSD2) and GDPR are forcing institutions to provide standard interfaces, accessible through open APIs (application programming interfaces). The United States is coming on board, and this is carefully being monitored to understand how clients can adopt new rules.
There’s no doubt that efforts to establish the ground rules for this kind of data sharing will be complicated. Such transformations are not without risk, but the underlying benefit of improved credit underwriting from more inclusive data sources is just too valuable for lenders and consumers to miss.