Risk management and customer data are two key areas where data analytics is being applied in financial services.
Given that predictive analytics software is increasingly easier to use, it’s no surprise the technology is being adopted more and more in the financial services industry. In general, it is applied there in two ways:
1) Against customer data
2) Against internal and market data for risk management
While both uses are predictive, there are large differences between the results. Using customer data, banks and other financial institutions are applying the technology to predict customers likely to churn and then taking action to prevent the churn from occurring. Predictive analytics identifies customers likely to churn, then segments those customers by profitability, volume, and length of engagement.