Create and manage end-to-end underwriting processes without writing any code to improve efficiency, reduce IT burden and eliminate regulatory concerns by creating transparent workflows that your organization understands. Take your underwriting processes beyond traditional credit scores by using automated machine learning to analyze historical data and train models that predict defaults on future credit applications.
Automatically process a wide range of data to determine the likelihood of fraud for online transactions. Instantly flag or reject suspicious activity by combining predictive models that can identify fraud patterns with explicit business rules to make sure you're protected.
Increase marketing efficiency and improve ROI with predictive analytics that ensure the most accurate targeting and messaging possible. Optimize your marketing with machine learning models that predict response rates and suggest the right message at the right time.
Use rules management tools to automate NSF, no-pay and other actions in a systematic way to improve customer experiences, enhance recovery rates and ensure consistent operations across your organization.
Leverage historical loan information to create predictive models that forecast future borrower performance and predict loss rates on lending products. Models can then be incorporated into decision strategies for underwriting, pricing and developing loan products.
Leverage historical data from verified applications to train predictive models that accurately estimate the applicant’s income on future applications. Use this estimate to approve, reject or flag applications for manual review.
Evaluate applications and transactions in real-time with predictive models that accurately estimate the probability of fraud, saving you time and money while streamlining customer experiences.