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Automatic Real-Time Credit Scoring Based on Transactional and Digital Assets Data

AuDaScience BRAINs™ next generation, Spark-based, big data, automated machine leaning platform provides a unique and revolutionary approach to the automatic development, deployment and updating of machine learning models for credit scoring based on transactional and digital data.

AuDaScience BRAINs enables enterprises to streamline credit application decision, by using a powerful big data machine learning application which can assist them:

Collect in real-time all customers’ digital experience activities from digital assets and save raw digital data to a big data environment; Use Profile Builder BRAINs application to construct a real-time “Digital Customer Profile View” from raw digital big data, including several hundred attributes profiling each customer’s activity in the digital assets (websites, mobile app). This digital customer profile is constantly updated in real-time, enabling the company to define real-time triggers and to update credit scoring in real time;
Use Risk BRAINs to rapidly develop dozens of credit scoring models for different customer segments; Real-time scoring, based on the most up-to-date information available on each customer based on digital big data streaming.

Profile Builder BRAINs enables credit risk analysts to define a business logic of transformations they would want to apply to raw digital data for constructing and update an aggregated digital profile, including calculated attributes, in real time. Profile Builder BRAINs deploy the business logic using Spark streaming for updating the digital profile in real time.

Risk BRAINs supports the full lifecycle of development and real-time deployment of complex credit scoring models and enables credit risk analysts to rapidly develop complex credit scoring models, by different customer segments, without writing a line of code. After models are ready they can be automatically deployed for batch or real-time scoring on streaming digital data.