Andrew Williams, client partner – EMEA at FICO, outlines how to bring the fintech experience to motor finance customers.

The crippling challenges Covid-19 presented to motor finance will guide the industry’s choices for years, but a major problem persisting from before the pandemic can be resolved with advanced analytic science.

Car dealers want to get more customers through their doors, virtual or physical, and quickly back out again with a set of new keys or a signed contract. Part of the process is setting up the finance — and this is where many lenders fail. Their automated systems will reject a finance request without making a compelling counteroffer that could win them the business. Most auto lenders have no automated counteroffer process.

Meanwhile, the evolution of the online car buying experience – think Cazoo, Carzam and Cinch – is creating a whole new consumer expectation.  Motor finance companies wanting to support traditional motor retailers will need to respond to that challenge.

A smarter counteroffer

Automating the counteroffer process is much more complex than it first appears. It needs to be comprehensive and consistent in line with FCA regulations that came into force at the end of January.  Nearly every possible counteroffer needs to be evaluated for acceptance, and then the bundle needs to be rapidly reduced to those that will interest the buyer.

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The process should take into account that some buyers care most about the interest rate, some care most about the deposit, while others care most about the monthly payment. It must also be fast. Any approved offer needs to conform to the lender’s credit risk criteria, which can be arduous to determine when the offer terms are constantly changing.

This problem cannot be comprehensively solved within a lender’s existing rules engine. What’s needed instead is mathematical optimisation — the analytic technology that can search through thousands of potential combinations to find the best possible counteroffers within the lender’s and dealer’s constraints and return those offers to the dealer in less than five seconds.

Optimisation solvers factor in credit and pricing logic plus behavioural analytics, such as the likelihood of response.

This kind of alternative deal structure optimisation (ADS) can help car dealers improve the customer experience and underwriting levels.

ADS optimisation allows dozens, hundreds, or even thousands of options to be evaluated, helping to ensure that the best alternative offers are discovered. It uses a dynamic search path controlled by business objectives and policy constraints, eliminating the need for lists of all possible options to be considered.

ADS has a variety of applications:

  • Conditional approval – Generate counter-offers when the initial deal structure is not system-approved
  • Approval with options – Generate additional options when the initial deal structure is system-approved
  • Inventory decisioning – Request for approved financing options on all available inventory at a dealer
  • Pre-approval – Request for approval limits not linked to any specific vehicle
  • Manual review – Generate alternatives for the underwriter before queuing for manual review
  • Buyer self-service – Guide dealer/customer on approved structures via the self-service portal

ADS provides self-service capabilities to both the dealer and customer, who are both looking for more insight and input over deal-structuring decisions. Many auto lenders are currently evaluating options and trialling pilot tools.

ADS has widespread and immediate benefits. The incremental real-time decision service leverages lender scorecards, credit policies and pricing policies to ensure risk-compliant outcomes. Crucially, it also improves overall time-to-decision and reduces the need for manual decisioning. This all boils down to an increase in approval and booking rates, helping motor dealers respond to the challenging market conditions.