AI in Financial Services

Predict which credit card customers will default on their credit card loans to strengthen credit card portfolio.

Predict the likelihood of a mortgage defaulting by leveraging historical mortgage default data.

Predict ATM fraud in order to take preventative action.

Estimate loss given default (LGD) to better set loan loss reserves, forecast losses, and maintain capital adequacy.

Risk-prioritize alerts generated from rule-based transaction monitoring systems to reduce the number of false-positive alerts and increase the efficiency of the alert investigation process.

Monitor the health of your relationship with high value customers to prevent them from churning.

Maximize the effectiveness debt collection efforts by predicting in advance which borrowers are likely to pay back.

As a relatively new financial system, blockchain is particularly vulnerable to security threats. Build and deploy machine learning algorithms that can detect anomalous behaviour anywhere along the chain.

Use the power of AI to reach and engage new clients, matching the right customer with the right product.

The cost of credit card fraud is billions of dollars per year. By accurately predicting which transactions are likely fraudulent, banks can significantly reduce these illegal transactions while providing card holders an excellent customer experience.

Making accurate judgments on the likelihood of default is the difference between a successful and unsuccessful loan portfolio. Reduce defaults and minimize risk by predicting the likelihood that a borrower will not repay their loan.