CyborgIntell, an innovator in end-data to value-focused artificial intelligence (AI), has announced two powerful additions to its transformative zero-code AI platform for banking, financial services, and insurance. The product suite now includes Feature Store and Model Risk Management (MRM) functionality.
Feature Store automatically creates thousands of new features from raw data, saving 90% of the time spent in data preparation for modelling. A feature is a set of input variables that are used to train AI and ML models to help them make better predictions. Precomputed features are created by applying specific transformations, aggregations, or calculations to raw data before storing them.
This allows financial institutions to surface hidden transaction behaviours, transaction patterns and habits, payment preferences, risk behaviours, depth and breadth of customer relationships, and more. They can use these features to train AI and machine learning (ML) models to solve diverse business challenges and leverage them to gain a 360-degree view of data within seconds.
The Feature Store will reduce the time it takes to compute feature pipelines and create multiple data lineages for model development and experimentation. It offers automated data pipelines for model deployment and helps prevent errors with feature validation and tracing to reduce risk. The store offers pre-built features for lending, banking, and insurance, and showcases complete explainability and documentation for streamlined operations.
“For too long, financial organizations have struggled to harness the raw power of data effectively. With our turbocharged, next-gen AI offering, CyborgIntell aims to empower financial institutions to derive unparalleled value from their data, to arrive at expedited decisions that will transform their business, and unlock ROI from day zero,” says, Suman Singh, Founder and CEO, CyborgIntell.
The Feature Store goes beyond traditional analytics to model the complete depth and breadth of customer behaviour, from how much revenue can be generated to determining risk parameters. The feature pipeline is seamlessly integrated into an automated ML platform, where AI helps to create thousands of ML models, perform champion challenges, and recommend the best-in-class model.
Another game-changing addition to the CyborgIntell product stack is the industry first Model Risk Management (MRM) or diagnosis tool, designed to instil a newfound trust in AI deployments. MRM monitors more than 60 different parameters real-time for three different kinds of reports namely model, feature and data drift reports.
MRM generates early warning indicators if the AI fails and provides root cause analysis for the failure. It also tracks if there’s any change in customer behaviour or patterns or if the model has started deteriorating and helps to self-mitigate the problems. MRM gives businesses confidence to make data-driven decisions without fear of unpredictability or failure.
Bryan McLachlan, Managing Director: Africa at CyborgIntell, says: “Data scientists should be spending their time solving business problems rather than on complex, but repetitive work that can now be done by an efficient, zero-code platform. Feature Store and MRM allows financial services institutions to vastly accelerate ROI from AI deployments, rapidly unlock business value and scale deployment.”
