Case study Ethical lender Fair Finance automate decisioning with ADP
LendingMetrics and Fair Finance had already been in contact for a number of years, developing a strong relationship based on a mutual interest in the devel - oping technologies within the lending markets. As with many other lenders, Fair Finance were using a completely manual underwriting process and were interested in learning more about the different options available to update this process. As LendingMetrics have a range of products, including their Auto Decision Platform (ADP), and Open Banking product OBV, they were able to demonstrate how they could support Fair Finance with their mission in a number of different scenarios, earning their trust as experts in this field. Many businesses are conscious that automating processes may result in a journey or experience being dehuman - ised for the end customer and a threat to staff morale with the fear of job
losses, and this was particularly impor - tant to Fair Finance as a socially con - scious business. LendingMetrics were able to show that automation can be used to simplify the parts of the process that involve black and white decisions, leaving the underwriting team to review the results for rules that might still need a human’s touch. After taking some time to discuss inter - nal priorities and taking into consider - ation the advice and consultation pro - vided, Fair Finance decided that they wanted to progress with implementing a software solution to support their decision making. Due to the importance of this decision, Fair Finance adopted a thorough tender process, using an external consultancy firm to perform an option analysis on the various providers with whom they had engaged. Lend - ingMetrics were delighted to be select - ed, following the tender process, and
Fair Finance offers a range of financial products and services designed to meet the needs of people who are financially excluded. Their mission is to design and deliver financial services that improve financial wellbeing and have a positive Fair Finance recognised that in order to continue their success, they needed to improve the consistency and quality of their underwriting and decisioning. They were keen to find technology that would enable them to automate the process, but also provide them with a future-proofed system that allowed for ongoing decisioning changes and new third party data suppliers. impact on their clients. Choosing LendingMetrics
12 | Metrics Monthly
September 2020 | AU Edition
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