Helping Lenders Fund More Loans and Improve the Borrower Experience

Our mission is to help lenders fund more loans and streamline the lending process for borrowers. For too long, lenders have required applicants to jump through hoops because a small percentage of applicants fabricate or misrepresent data about themselves on loan or credit card applications. Fortunately, the combination of consumer risk data availability, artificial intelligence (AI) and machine learning techniques, and cloud-based technology advancements are being used to ease the applicant’s journey.

Are you still using paycheck stubs to verify income?

Our team looks at using paycheck stubs to verify income like we look at fax machines – they’re antiquated! These days it is so easy to go online and create a fake paycheck stub that it’s hardly worth your team looking at them. They are just not reliable.

The purpose of validating income, of course, is to determine if a borrower can afford the payment on a new credit instrument. Traditionally, there are a few ways to accomplish this:

  1. Query an HR/employment database. This approach comes with two significant disadvantages. First, because it relies on employers contributing data, it can have a low match rate and not cover even half of your applicants. Second, it’s expensive, adding as much as $25 to your cost to process an application.
  2. Use an authentication service. This approach creates friction. Each applicant must provide consent for the lender to access their online banking data, which is a hurdle your most trustworthy applicants won’t want to be subjected to.
  3. Good old fashion documentation. We’ve already mentioned that documents can be forged, but this also adds inconvenience for trustworthy applicants and costs for your employees to review the documents. There’s also repetition bias. When employees are tasked to review hundreds of documents and more than 90% of them are valid, it becomes increasingly difficult for them to spot the ones that are altered or even completely fabricated.

Use an automated approach. We have a continuously growing data repository of consumer risk data that includes information on income and employment for more than 56 million U.S. consumers. We use this data, which comes from historically reported salaries, IRS income data, Census data, and many other sources to automate income verification and model income values based on geography, occupation, and employer. We use this data with AI-powered models to easily identify when a stated income is likely to be inflated by 15% or more.

Does that applicant work for a legitimate employer

Did you know that there are thousands of fake employers listed on loan and credit card applications? Some of these fake employers have a phone number where someone might even answer a call and “verify” an applicant’s employment, but it’s all a ruse designed to deceive lenders.

Our proprietary data repository of consumer risk data includes millions of employers and more than 6,800 employers that are confirmed to be fraudulent or non-existent. We have seen, for example, the same fake employer listed on more than 1,200 loan applications coming from borrowers in 22 states. These fake employers are recycled over and over again until lenders catch on. Now, lenders can stop them much faster.

Power more automated decisioning

Let us help you leverage artificial intelligence (AI) and a repository of consumer risk data to make more FCRA-compliant automated approval and decline decisions. Accurately identify low-risk applicants eligible for a streamlined approval process, favorable pricing and/or other favorable credit terms or credit-based incentives. Likewise, we can help you identify applicants you choose to decline based on a high risk of default due to fraud or misrepresentation.

It comes down to trust

The vast majority of your applicants are trustworthy. We conducted a study of sub-prime auto loan applicants that found that approximately 3% of prospective borrowers were untruthful on their applications. Why should the other 97% bear the burden of suspicion and delays for identity, income, and employment verification, which also drive up a lender’s cost of origination?

Don’t risk losing hundreds of valuable customers to catch a few suspicious applicants. We help you spot the few who need additional scrutiny while everyone else flows right through your origination process.

Point Predictive helps lenders:

  • Eliminate traditional income verification using paycheck stubs
  • Make more FCRA-compliant, automated approval and decline decisions
  • Leverage a unique source of consumer risk data to improve the experience of legitimate applicants
  • Fund loans faster while taking on less risk and reducing operating cost

Let us help you complete loan funding faster without increasing your loss exposure. Contact us to learn more.