the cognistx blog

Banking on AI: Our Tools for the Financial Industry

March 29, 2022
By Sanjay Chopra, CEO, Cognistx

AI can serve the banking industry in powerful ways, such as:

• Customer segmentation and attrition. As digital banking takes over and the branches are less effective at retaining clients, it is critical that banks understand their customer segments, match appropriate products to each segment and push appropriate products/services in a timely manner. It is also crucial for banks to understand which customers are likely to move away and to then prevent them from leaving. Cognistx has developed advanced customer-clustering models and attrition models that can help on both of these fronts.

• Automating part of the underwriting process. Banks collect a lot of documents for new loans and line of credit applications. AI can help with:

  • Pre-processing applications as they are submitted online to ensure the applicants qualify and they have submitted all appropriate documents.
  • Post processing so that the documents are automatically analyzed by the Document Intelligence Platform (DIP). DIP can highlight areas for the underwriter to review. DIP can be augmented by SQUARE (Scalable Question Answering & Recommendation Engine), which allows the underwriter to quickly assess the risk and make sound decisions.

These technologies were utilized in our implementation for the RISE fund. DIP and FEAST have been utilized for our implementations with Schneider Downs, Odds On Compliance, Fannie Mae and SAE.

• Data anomalies and related analytics, including customer transactional data. Our Data Quality Engine (DQE) can help identify customer data issues; transaction data issues, including but not limited to fraud or AML transactions with the help and support of a robust rules engine; and loans data. DQE can find business rules–based anomalies and statistical models–based anomalies. It can further identify new patterns of interest that human operators can annotate to create new dynamic rules.

DQE has been utilized significantly for our implementations at AmeriGas and Armada.

• Economic reports and forecasts. To help chief economists, we have developed tools that can analyze large amounts of unstructured text (internal and external) and provide insights on key economic indicators such as unemployment, inflation, interest rates, pricing indices, supply chain issues, etc. We again utilize a combination of DIP and SQUARE to analyze large texts and then provide the ability to ask questions and seek insights. We also have a “needle in a haystack” module that presents interesting insights that humans will likely miss.

• Customer product recommendations. A smart engine/assistant will help bank tellers and front-line employees make product recommendations/cross-sell to clients dynamically.  

• Real Time Performance Monitoring for Employees. Helps managers and senior executive management monitor and present performance results in dashboards that can monitor multiple business units and processes: i.e. lead generation, customer service metrics, branch performance, online banking activity, and deposit and loan targets.

If your bank or organization would like to explore these opportunities, we are game for a partnership!

Please contact Cognistx CEO Sanjay Chopra to learn more about how AI can enhance your business.

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