Improving application credit scores through AI technology
Hitachi Capital Consumer Finance wanted to understand the uplifts that may be possible through using a deep learning approach. The Consumer Finance division appointed Jaywing to explore the potential to significantly improve its existing application credit scores using Jaywing’s AI modelling technology, Archetype.
Jaywing processed data from Hitachi’s recent scorecard development using Archetype to replace the traditional modelling steps. Using the software, Jaywing was able to apply appropriate constraints which reflected how Hitachi’s modellers would apply common sense rules to the inputs. These rules meant that the system would only generate model outputs adhering to Hitachi’s expectations, making models explainable to regulators and customers alike – a key differentiator compared to other Neural Network-based approaches.
Using exactly the same data, Archetype demonstrated an impressive uplift of 7.2% compared to an optimum linear regression model, showing that the Archetype model had the potential to predict and prevent more bad debt or to increase the number of customers taken on without increasing bad debt levels. On a smaller sub-prime portfolio, an uplift of 11% was seen, from a lower baseline.
Nick Gibbs, Head of Commercial & Strategy at Hitachi Capital Consumer Finance, said: “We were very interested in the role that AI could play in transforming aspects of our business’s operation. Not only did Jaywing promise uplifts through the Archetype software, they delivered them too. Archetype solves the black box problem in credit risk and has given us food for thought in how we approach our modelling activity. I look forward to working with the Jaywing team in the future as we continue to explore the use of AI in our business.”
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