Credit, collections & insolvency news
Risk analytics consultancy, 4most, has announced that it has partnered with financial services provider, Fair Finance, to deliver a more automated approach to decisioning and improve decision quality by expanding its lending activity. 4most has been working closely with the risk team at Fair Finance to create a series of initiatives designed to improve the customer journey and boost several aspects of the risk assessment and credit decision process.
Torgunn Ringsjø, Director of Products and Recurring Services at 4most said “Improving the financial wellbeing of its customers is at the core of Fair Finance’s strategy. Previously, most decisions were manual, relying heavily on the experience of the underwriting team. Whilst this approach can work well in a branch environment, a common challenge is the ability to scale this model as the organisation moves online and deals with exponential application volumes. The need to automate decisions, whilst building on Fair Finance’s underwriting know how, were key goals identified from the start.”
Using its Knowledge Elicitation Process (KEP), 4most incorporated a combination of expertise from the underwriters at Fair Finance supported by statistical insight from historic data into the model build. The KEP process is designed to ‘elicit’ knowledge from the Fair Finance underwriters and risk team about their own customers. This insight is then used to create a scorecard model that incorporates the characteristics the ‘experts’ believe to be the key drivers of risk for their portfolio.
The data available from the historic Fair Finance applications supported the process in two ways; firstly, by providing real life scenarios for the KEP workshops to produce a model to infer the manual ‘expert decision’ and, secondly, to give insight into historic decisions and subsequent customer behaviour for the purposes of model consistency and validation.
Guillaume Foucaud, Chief Risk Officer for Fair Finance, said “From the outset, the team at 4most understood the challenges we had experienced. We have a small risk team, so 4most took the lead in identifying which data was available and suitable for the model development. The KEP was a big win for us as this allowed our experienced underwriters to input into the development process and create a model which was fit for purpose. It also helped to get buy-in from our underwriters for the automation journey as they were able to see first-hand, how the automated model worked and how it could support them in their day-to-day role. The result is a more automated and also consistent approach to application decisioning.”
Ringsjø added “As with any new scorecard, monitoring is essential. We will therefore be using LUMOS, our model monitoring solution, to provide Fair Finance with a hosted monitoring service, including the production of regular monitoring packs as well as bi-annual workshops to discuss trends in portfolio profile and scorecard performance.”