Preparing Risk Tools for 2020 ― Today

canstockphoto19346690In auto finance, the concept of risk management boils down to creating profitable ― not perfect ― predictions about whether consumers will repay their car loans. With data availability increasing at a rapid pace, and advancements in decisioning and pricing algorithms constantly being developed, lenders must prepare for a highly analytical decade in 2020, said Preston Cecil, vice president of risk management at Innovate Auto Finance, at the Auto Finance Risk & Compliance Summit last month.

Human capital, technology, and data are the trio of risk-management tools that lenders must employ to hone scoring mechanisms, Cecil said. Here are some specific ideas to implement within each area:

Invest in human capital.

  • Offer training courses so that employees can bolster their knowledge. Courses may be company-funded or based on available openware.
  • Encourage creativity by challenging the status quo and setting aside time for brainstorming.
  • Pay for performance. Define and track key performance indicators, then reward employees appropriately.

Allow technology to aid workflow.

  • Rely on automation. “Let the machines do the busy work,” Cecil said. Their speed and accuracy allow for deeper dives into non-quantifiable data.
  • Employ the appropriate statistical software, and tools that integrate easily into your loan-origination system.
  • When it comes to data architecture, use an adaptive and robust infrastructure.
  • Develop the ability to quantify unstructured data ― the information that doesn’t reside in a traditional row-column database ― like email messages, call center notes, and survey responses.

Harness data, don’t abuse it.

  • Tap into non-bureau data to enhance tailored scorecards, particularly for thin-file applicants.
  • Identify leading indicators, which are ever-changing. Historically, consumers paid for groceries first, then for utilities, rent, and cars, Cecil said. Nowadays, phone bills commonly trump utilities, and car payments trump rent.
  • Aim for meta-analysis. Use statistical methods to contrast and combine results from different data sets in the hope of identifying patterns or other interesting relationships.
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