A multinational Canadian bank with a broad range of products and services including personal and commercial banking, wealth management, corporate and investment banking. The bank is one of the largest both nationally and globally.
The bank wanted to identify and deploy a new model that could track and analyze behavioural data for millions of its credit card customers. Objectives for the new predictive model included:
Old statistical models used to predict customers at high-risk for delinquent payments were limited in the following ways:
The bank approached DeepLearni.ng to design, build and deploy a deep learning model that would offer solutions to the old models’ challenges in the following ways:
In a cross-comparison between the bank’s old statistical model and DeepLearni.ng’s deep learning software, DeepLearni.ng’s software consistently outperformed the bank by at least 20% each month.
Unlike the bank’s old model, DeepLearni.ng’s model also offers banking executives the power to generate personalized customer insights from data.
Powered by their platform Frontiers, the DeepLearni.ng team was able to quickly identify the best deep learning model to build to reach the bank’s objectives for credit card management. By pairing Frontiers with technological expertise, the DeepLearni.ng team also ensured the model was seamlessly installed, without the need to overhaul the bank’s existing legacy IT infrastructure.
DeepLearni.ng’s successful deployment of a model to enhance the bank’s credit card risk management was a great first step in demonstrating the technology’s potential for new solutions in retail banking. With optimized customer communications and a better bottom line as the result of DeepLearni.ng’s model, the bank will continue to partner with our team to move beyond a narrow and specific collections tool. In the coming months, DeepLearni.ng will work with the bank to build holistic strategies for use in branches and across its digital channels.