Data collision: efficient lending under CECL

John Toohig

Over the course of this chapter we will illustrate some of the early data points necessary to assess CECL, and examine the use case for making an institution a more data-driven lender. We will focus on several common loan product types, such as residential mortgages, consumer auto loans and commercial real estate (CRE). Not only will we dive into newly originated loans and their profitability, but also the ongoing maintenance and monitoring of the portfolio. As the CECL standard has had time to sink in, there is a silver lining starting to emerge. Gathering the information necessary to comply with CECL can make lenders more profitable over the long run by enabling them to price loans correctly at origination, and can also improve the risk profile of institutions by allowing them to monitor the performance for the life of the loan.

The community depository loan balance sheet is often where a loan goes to live its life undisturbed and misunderstood. The loan portfolio for most banks and credit unions throughout the US is a conglomerate of relationship-based credit exceptions, secondary market purchases, mergers, core servicing conversions, and shifts in credit policies that

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