Experian says things “are moving in the right direction,” but 2 of 3 lenders note challenges, like a struggle to have the right technology, data and talent.

COSTA MESA, Calif. – A new study by Forrester Consulting for credit-scorer Experian finds that “financial inclusion” – a goal to more fairly serve historically disadvantaged homebuyers – is a top priority, in part because many lenders see it as a way to generate more income.

However, a number of lenders said they face challenges achieving that goal. While over two-thirds of the lenders surveyed said they’re implementing financial inclusion strategies, two-thirds also said they don’t have the right technology, data and talent in place yet to fully execute the program. In addition, 56% said they need greater internal education about the benefits of diversity and inclusion.

The study reinforces the role data plays in order to increase access to fair and affordable credit: 62% said additional data sources can improve consumers’ access to credit and 60% plan to use advanced analytic technologies, machine learning and AI in their credit decisions.

“We believe this research confirms our industry is heading in the right direction, and that financial inclusion is a top priority for lenders across the U.S.,” says Greg Wright, executive vice president and chief product officer, Experian Consumer Information Services. “Leveraging data and technology to drive financial inclusion is job number one for us.”

While “financial inclusion” is often viewed as a way to end discrimination and get otherwise qualified buyers into a home, many lenders view it as a way to engage new audiences. Recently developed programs primarily focus on people new to credit (46%), followed by low-income consumers (41%) and small businesses (40%). Secondary targets are customers with no or thin credit files (38%) and the unbanked/underbanked (34%).

Data that drives inclusion

The study also asked lenders about their most valuable data sets for risk assessment since 62% use or plan to use expanded data to improve risk profiling and credit-decision capabilities. Top responses include:

  • 64%: banking data
  • 57%: cash flow data
  • 52%: employment verification data
  • 51%: asset, investments and wealth management data
  • 51%: alternative financial services data
  • 36%: telecom and utility data

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Author: kerrys