Due to the current economic situation, forecasts predict mortgage default rates will rise between 7% and 15%, with losses expected to exceed 200 Billion dollars by 2021. To stay ahead of the game, financial institutions will need an effective credit risk and monitoring tool empowering their teams.
To efficiently handle this problem on a large-scale, leveraging the power of automated tasks and advancements in machine learning can help predict and prevent loans from becoming Non-Performing Assets (NPAs).
Introducing EWS – Speridian’s Default Prediction and Early Resolution Tool
EWS offers two key Modules
is an intelligent predictive analysis tool that uses the power of data science and machine learning algorithms to successfully predict loan default probability. This tool helps to categorize a loan portfolio into High, Medium and Low Risk watch list groups based on risk scores derived from ML algorithms. It offers a unique approach, combining internal loan data with current impacts from external data elements to predict the likelihood of default.
works very closely with the Default Prediction tool, taking a particular loan as input and analyzing different workout options through a configurable workflow of questions. Based on the answers provided, the workflow can identify the best-suited workout option by using a rules-based intelligent resolution model that combines borrower scenarios with existing loan data. It also offers easy integration with call centers, intelligently routing the loan to the best-qualified loan modification agents for proper handling and easy resolution.
The EWS Advantage
Our solution uses the most advanced AI-Machine Learning solution, using the Gradient Boosting and Random Forest testing methodologies yielding nearly 99% confidence in determining loans at risk.
Our rapid deployment and innovative pricing models including “pay-by-the-drink” and gain-sharing, eliminate long-term projects and complicated agreements.