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Lenders Should Use Data to Decide Who to Lend to and When

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By Moshe Abudarham

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Data is the currency of the digital world, and banks and non-bank lenders have a tonne of data. The question is, how effectively are they using it? When it comes to mortgages, both types of lender can leverage data they already have access to in order to determine whether a customer is ready and eligible for mortgage products. And for lenders who sell loans on to the secondary market, they can build a digital footprint with data they did have access to, be that financial data, or property data gleaned from MatterPort.

There are four levels of data analytics lenders can aim for:

  • Descriptive: Seeing what happened
  • Diagnostic: Understanding why it happened
  • Predictive: Assessing what will happen
  • Prescriptive: Working out how to make something happen

We recently wrote about the Six Key Criteria for Mortgage Approvals, namely credit, income, assets, employment, valuation, and title. Banks have a head start over non-bank lenders, because although they may not have the full picture, they know more about a customer’s income, assets, and employment just from receiving a regular paycheck in a customer’s checking account and the balance of cash in the customer’s checking and saving accounts. If a direct deposit is coming in every two weeks, the bank knows the customer’s main income, and their employment history and status.

Further, although both bank and non-bank lenders can easily make a soft pull on a customer’s credit report, banks can look at other spending patterns based on debits and credits moving in and out of a customer’s accounts. In our inaugural quarterly Mortgage Mic Drop forum, Kristy Fercho, Head of Wells Fargo Home Lending, explained how banks can take all the information they know about a customer, and use that data to create a ‘know me’ experience that feels more personal, and how all it takes is filling in the gaps of the data they already have access to. Kristy’s colleague, Mike Weinbach, CEO of Consumer Lending at Wells Fargo, agrees, suggesting that banks should move towards a model where they can already approve a customer for a mortgage before they even apply. There are still some aspects of the process that need to be updated to make that a reality for most lenders.

Mike explained that the strategy is to build up the right data repository, get the right data feeds, and invest in APIs that can pull data in real time, perhaps with a certain level of artificial intelligence. The important thing is to put the customer at the center of the experience, and to be thoughtful about the information you want to capture and how you’re going to use it. With the customer at the center of your tech architecture, you won’t need to ask the customer for information you already know. Mike also suggests that bank and non-bank lenders need to shift their focus from Loan Origination Systems, but instead should focus on getting the touchpoints and tracking the data around every single interaction with consumers. The more interactions a lender creates, the greater understanding they will have of the consumer and how their behavior is shifting.

Whereas a bank can build out a picture of a customer’s behavior to understand when they might be ready for a first mortgage, non-bank lenders can do similar for existing mortgage customers to see when they might be ready for a refinance. As Willie Newman, CEO of Homepoint, explained in a conversation with States Title CEO, Max Simkoff earlier this year:

“Once a customer kind of gets into the mortgage ecosystem, I think the next mortgage that they do will be so simple, straightforward, and data-driven that a lot of the infrastructure that’s been built to process loans and to handle the flows of information associated with physical information, gathering, and collation, I think that all goes away.”

For a refinance, not only can a lender assess the credit-worthiness, consistency of income, assets, and employment of a customer, they also have a good idea of the valuation and title of the underlying asset. They can access valuation data streams such as Clear Capital to see if the property has increased in value, and assess if any new liens or other claims on title have been applied to the property since the homeowner purchased the property. If interest rates have dropped, as they have consistently in 2020, it’s a good bet that the homeowner would be interested in refinancing, and the lender can be proactive before the homeowner goes searching for a lower rate at a competitor.