Metrics Monthly | November 2019 | UK Edition

LendingMetrics assisted with designing a multi-functional decision engine to cover all areas of credit risk including a multi bureau approach. Utilising score- cards alongside an automated rule set over various data components, they built an affordability check including an offer and loan term matrix, providing automated flexibility built into the loan offer, based on the consumer’s individ- ual circumstances. The LendingMetrics Auto Decision Platform (ADP) implementation team then took the lead - headed by a client dedicated Project Manager - and held several scoping and requirements gath- ering calls to provide a full project plan with timelines. Once all requirements were gathered, LendingMetrics took 4 weeks to complete the build of the decision engine and complete the addi- tional third party integrations required

by Loans 2 Go. During the implementa- tion of ADP, regular calls took place with lead developers on both sides so that the ADP project ran smoothly. Results LendingMetrics have delivered a service which produced a scaleable model and Loans 2 Go have now successful- ly launched online and are looking to increase their lending portfolio using the ADP platform and associated ser- vices. The solution was delivered within budget and on time, entirely as a result of the collaborative and knowledgeable teams at Loans 2 Go and LendingMet- rics. Following training, the Loans 2 Go team are now using the ADP interface to change their credit decisions in real time, champion challenge their rules and analyse the results within ADP, as well as using the Equifax suite of prod- ucts and OBV.

Consumer credit case studies Our large amount of recent consumer credit case studies (in the UK and Aus- tralia) include Omni Credit (Owned by JC Flowers), Evolution Money, Loans- 2Go, Fair For You, and Aus Loans one of Australia’s largest motor and per- sonal loan originators.

For Aus Loans in particular we have delivered a novel solution which allows Aus Loans to mirror the lending crite- ria of the 40-or-so banks and lenders on their panel, allowing them to auto- matically match a client to a specific lender (based on credit data) and then further select available deals based on the best rate available.

This is not simply pre-approval filter- ing, but a decision based fully upon the full lending criteria of those 40 or so lenders. The editing control of the engine logic is entirely within the control of the lender and they have no such dependency on LendingMetrics. We believe the solution to this model to be truly unique.

See more of our case studies

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