Despite some market turmoil, 2016 has shown several positive signs of economic growth: The Fed’s December decision to raise interest rates took effect without major backlash, the unemployment rate dropped to 4.9 percent, and Q1 saw consumers loosen their wallets. But behind the scenes, the banking industry is still reeling from the Great Recession, desperate to find efficient ways to function under more stringent regulatory guidelines.

This is especially the case with income verification. Besides the various protections put in place after the sub-prime mortgage crisis, regulators continue to discourage banks from using income prediction models, citing concerns that models may provide an inaccurate understanding of a borrower’s true income picture which may lead to consumers burdened with more debt than they can handle, and result in a safety and soundness concern for banks.

In turn, banks face a difficult dilemma, left with two options to process loan applications: 1) take consumer-reported income at face value and use that number for loan decisions and underwriting, or 2) go through a long manual process of collecting W2s, tax returns, and related documents to verify income.

The first option includes more risk. But the second is costly, inefficient, and slow, incapable of supporting a quick credit card, auto loan, or credit line increase decision. With limited resources, banks are forced to pursue option one.

Recognizing how valid data could improve this process, Powerlytics developed its True Income Suite of products, featuring income verification and estimation products to support loan decision-making and marketing. It’s not a model – it’s a statistical distribution of actual income data. Rather than use an algorithm to guess consumer income, Powerlytics can fact-check against a database of actual (anonymized) income data for over 144 million households to verify an applicant’s income claims.

How often do loan applicants really stretch the numbers? A study from the IRS comparing income tax data to census data found that households, on average, overstate their income on census surveys by 30 to 60 percent. Similarly, a Powerlytics team member with a long work history at a major credit bureau found consumers overstate income by an average of 30 percent on auto loan applications.

Such statistics underscore the need for an efficient, trustworthy way to calculate ability to pay. Powerlytics does that by automating the risk assessment process – assigning confidence scores based on accurate and comprehensive income data and giving banks critical insight into a borrower’s likelihood to pay back a loan. In blind tests with some of the top U.S. banks, the Powerlytics products proved more accurate than any previously used models.

How can banks use it? While mortgage applications still require manual income verification, lenders can use Powerlytics data as the first line of screening to determine if a borrower’s income is even in the ballpark of what they will approve. Other uses include assessing opportunities for credit line increases and making decisions on small consumer loan applications such as credit cards and auto loans. A marketing opportunity also exists, as banks can use the data to determine which products should be targeted to which customers.

Protecting both banks and consumers, Powerlytics’ data gives banks immediate decision-making capability in a way that’s safe for both lenders and consumers. Unfortunately, the Great Recession necessitated more stringent requirements to use products to ascertain the accuracy of reported income. Until recently, there were no solutions that could assist banks’ move away from inaccurate income prediction models. That has changed with Powerlytics’ income verification and estimation products which leverage actual income data to produce reliable verification scores and income estimates that help ensure banks are safe, consumers are protected, and regulators are happy.

Leave a comment