Data Analytics Essential As New Alternative Credit Scoring Models Emerge
Alternative Data for Credit Scoring
Emerging credit scoring big data models are giving financial services firms an opportunity to reach new audiences. Historically, banks and credit unions have relied heavily on traditional credit scores to assess the risk associated with accepting loan applications. The problem is that many people don’t have credit scores. In some cases, it is because individuals are so young that they haven’t used enough credit to have a score. In others, an individual may have had a negative credit past and stopped using credit as they have regained financial strength. Either way, these potential customers are often difficult for financial services firms to engage with.
According to a report from The New York Times, the Consumer Financial Protection Bureau has opened an official inquiry into using alternative data for credit scoring, and some scoring organizations have already begun using new methodologies.
Establishing more nuanced credit scores
Online and automotive lenders are among the leaders in adopting more nuanced credit score models, the Times explained, with approximately 100 companies already using or testing new methods. In these cases, the companies are finding that they can approve approximately 20 percent more applicants within their risk parameters than they would have with prior systems.
Alternative Credit Scoring Models
As new alternative credit risk scoring structures and models emerge, financial services firms have a key opportunity to take advantage of emerging methodologies to gain a competitive edge. One rising option is psychometric testing. Business Insider explained that psychometric testing uses consumer behavior and personality in order to generate a credit score. This allows organizations to gather publicly accessible consumer data to get an idea of what kind of risk a loan applicant presents.
“3 billion people have never borrowed from a financial services firm.”
Business Insider said that FICO believes there are 3 billion individuals around the world who have never borrowed from a financial services firm and, therefore, have no credit history. Introducing new forms of measurement can turn those users into customers. The key, however, is to gather a wide enough range of data and evaluation methods that target specific demographics to avoid ending up in a situation where biases built into psychometric tests become problematic. Psychometric testing isn’t the only alternative credit scoring method rising on the market, and Business Insider said we are currently entering what will likely be the most disruptive period of change in financial institutions since the 1970s as new systems gain momentum.
Getting and using the alternative data for credit scoring
Taking advantage of new alternative credit scoring models, not to mention being able to adjust as new market patterns emerge, depends on strategic fintech innovation. The big data movement has laid the groundwork for financial services firms as they gather large quantities of information from a wider range of sources. From there, dedicated risk management and credit scoring systems can analyze the raw data and present it to users in a digestible, actionable format. This allows decision-makers to quickly identify risk associated with loan applicants even though they are making those choices based on a wider range of data that is often unstructured in nature.
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With technology and alternative data, the unbanked population may have more options