Data comes of age
Neil Williams, Chief Technology Officer of LendingMetrics, looks at how automated decisioning has moved from fringe technology to mainstream game changer. Underwriting technology has come a long way since it was first introduced to the sector, and I can recall the very beginnings of such technology as early as the mid-naughties. The early days were not easy for com- panies with new automated underwrit- ing APIs to sell. Attitudes surrounding the use of technology in what had tra- ditionally been a pretty labour-intensive area - underwriting - were entrenched. Why would any lender want a ‘comput- er says no’ solution when they had a perfectly good team of underwriters in place? Conversations with what became the early adopters of this transformational technology were always challenging. You would often find that while you might have persuaded senior manage- ment of the benefits, the deal would falter at the eleventh hour when they could not sell the technology internally. There were too many defensive man- agers with groundless worries about their departments or jobs being made obsolete. Part of the issue was the use of the word automated, which many misinter- preted as meaning the end of all manual input (and therefore redundancy for the underwriting team). A key element of the learning process involved telling lenders that the term automated under- writing covered a very wide spectrum, and that their position on that spectrum was determined by the sort of lending they were involved in.
If most of their lending involved sums of under two hundred pounds, then they might want to automate 90% of their transactions (given the dispropor- tionate cost of manually underwriting such cases). Alternatively, if they were a mortgage lender, then they may prefer to retain manual review and only auto- mate the early stages of their screening process.
I would unpack the automated under- writing process and tell lenders to rather think of their back office as perhaps 20 tasks, of which they may well be able to automate the first 15. Also, if they did, they could then free their existing team to focus on areas that actually benefit- ed from human input. No redundancies, just a refocusing of the team. Eventually, the message did get through to lenders. Bit by bit.
08 | Metrics Monthly
Q1 | 2022
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