3. Integrate + Automate Create an automated decisioning solution to manage end-to-end straight-through processing for applications. Data from your chosen vendors or marketplace will be integrated into these workflows. With the right technology this should be a quick and easy process. You’ll deploy your risk models into these processes to power world-class user experiences and store the data you need to fully track KPIs across the decisioning flow. 4. Analyze To track the performance of your alternative data risk models you’ll need to analyze the data based on the predetermined KPIs of your POC project. These may include approval rates, average pricing, decisioning speed, credit risk accuracy, default rates and more. With business insights, machine learning models, and visualization tools directly integrated with your decisioning solution, you can track these metrics in real-time. 5. Determine Return on Investment As with any data source, there is an associated cost. To determine the success of your proof-of-concept project you should evaluate whether the increased cost of using more data results in improved portfolio performance. With data showing that most lenders see a return on the cost of alternative data within the first year, you should be confident that investing in an alternative data strategy will be well worth it!
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