Dr. Andrew Jennings, Chief Analytics Officer, FICO
Banks have had analytics and decision management tools in place for a number of years. What is happening now is a move away from human insight, and instead we're seeing a stronger reliance on real-time analysis through technology, says Dr. Andrew Jennings, Chief Analytics Officer, FICO, in this interview with CIO Asia.
Why is big data important for banks?
Big Data is not a recent concept for banks. Banks have been using Big Data and analytics for a long time; so it's very common for banks to use data to screen applications for credit risk and also to check if a transaction that's being made and is registered to a customer's account is fraudulent or not. So Big Data and the use of data are already well established in the banking arena. That being said, with greater adoption of analytic solutions, banks are able to mine their existing data to drive profitability and customer retention.
Let's take fraud as just one example of where analytics helps reduce risk and retain profit. The majority of banks in Asia suffer financial losses due to fraud, which may be in the form of application, ATM, or card fraud. By analysing big data from transactions, banks can determine from historical data and customer modelling, if that transaction is fraudulent or authentic. Doing this successfully both prevents the losses while enhancing the customers' trust in the bank's ability to protect their accounts.
Another Big Data area that is interesting for banks is analysing customer interactions via mobile and online channels. This show them the how, why, when and what customers want from the facilities offered. This feedback loop allows the bank to improve its offerings and even develop new products.
How are new big data tools replacing the older systems (BI and analytics)? What does it mean in terms of investments?
Banks have had analytics and decision management tools in place for a number of years. What is happening now is a move away from human insight, and instead we're seeing a stronger reliance on real-time analysis through technology. Of course, the 'brain' that drives all of this is still managed by analysts and other individuals at the bank to constantly tweak the decisions that are taken. However, the great benefit is the accuracy and velocity with which banks can run their organisations using big data effectively. The insights derived increasingly influence decision making. This means a greater investment in big data as more decision makers look for a competitive edge in the marketplace.
Do all banks use analytic tools? If some of them don't, how do they manage their data-gathering and business intelligence processes?