EC’s Abhishek Raval speaks to Kajal Ghose, CGM (ESS), SBI on a whole host of areas, where analytics is applied for the bank’s 30 mn customers.
Role of Analytics at SBI
SBI has 300 mn customers and thus it’s not easy to do the one-to-one interactions as was possible a few years back. Then, the bank staff had a personal rapport with the customer because of in-branch interactions. But over a period of time many alternate channels have come in, which have been disruptor of sorts. Now, 71% of the bank’s customers access the bank through those alternate channels. Hence the in-person conversations have reduced.
So, to identify with the customer’s line of thought, their next choices, what sort of customers they are, the bank need to set up analytics. Thus the first step is to build a data repository.
SBI has set up a data warehouse in 2009. It’s one of the biggest data warehouses in the world with 170 TB of data, which comes in through Core Banking Solution (CBS) and 37 other systems – RTGS, NEFT, ECS, AML, cash management product etc. On the basis of the data, which customers hold what value to the bank is assessed; How much deposits they have with the bank; the amount of advances, the number of loans taken. The banks also overlays group data – from SBI Life, Demat, SBI mutual fund etc. Having put that data, customers are categorised using the transfer price mechanism and basis that the customers are ranked as platinum, gold customer etc.
“Then a tool is used as a model to see the next best product to sell to the customers. The bank knows for e.g. that XYZ customer has a card, a house, marital status etc. Thus he might need a mutual fund, a home loan etc.,” says Kajal Ghose, CGM (ESS), SBI.
Role of analytics in Non Performing Assets (NPA) management
Analytics can do studies on NPAs. It can in fact be predicted, which of the loans are going to turn NPAs in say the next 6 months. We have done it. On the basis of the symptoms, from the accounts, which went bad already, NPAs that will turn bad and the ones that can be recovered – geographically, demographically can be identified. NPAs has been a problem. “In fact we have reduced our NPAs for the last few quarters,” informs Ghose.
Incorporating Credit bureau data for customer history
External data is also incorporated. Data from Credit Bureaus like CIBIL, Equifax, Experian, High Mark credit information.
This data is also used for customer retention. The leads relating to various other aspects is sent to the business units to inform them about where the current SBI customers are spending money. For e.g. There are many customers who send money to other banks on a monthly basis for home loans. The narration feed can help do data mining and communicate to the business units that X number of people have a home loan from X bank but their main account is with SBI; Y amount of customers are sending money to a particular bank for auto loans; a certain amount of customers are paying their taxes through a different bank, so a lot of leads can get generated these customers do the same transactions via SBI, the bank with which they have the main account.
Data can also be dug out on who are the customers, likely to close the account with the bank on the basis of the number of customers who have left the SBI in the last few years. With that as a base, the solution will identify the major symptoms in the accounts that led to the customer exits. Factors like the number of transactions coming down; taking loans from other banks etc.
This data can be run over the current data to identify customers having the aforementioned trend and give a heads up to the business units.
Analytics team: A Small start
The analytics team to start with consisted of ten people internally from varied backgrounds: with Economics, statistics, Mathematics etc. “We have recruited 16 more experts from the market. SBI has hired domain experts from IIMs: two professors are guiding us to do models, one from Bengaluru and one from Kolkata. We plan to get more resources. Hitherto, for 4 months, the bank partnered with a consultant for analytics policy, roadmap, the type of use cases, the models which we should be using,” says Ghose.
About SBI on Social Media and how analytics helps
We have joined social media and also run analytics on it. “SBI now is the bank with the second largest amount of users on Facebook. We expect to be number one by November, 2015. Our rate of growth is more than other private and public banks. The bank has overtaken all the others. SBI has the largest amount of Youtube subscribers vis-avis other banks. The views are growing up. We are number two in the number of people following us on Twitter, informs Ghose.
The bank has also joined Linkedin, Pinterest, Instagram and Google+. More importantly, the country’s largest bank is also the most responsive banks on the social media platforms.
Social engagement activities include various competitions: feel good fridays, thursday trivia, motivational monday among some of them. The bank runs campaigns like having quizzes on facebook based on videos on Youtube.
SBI’s App strategy
Apps have a tremendous potential. It enables banks to be glued with the customer. “The App downloads allows to track the customer location, in case the customer agrees to the bank’s request on GPS enablement, says Ghose. The bank can show advertisements, promote top-ups based on the customer profile.
SBI has ‘SBI freedom’ and ‘SBI Anywhere’ as apps. The bank recently launched ‘The Buddy’ as a wallet app, which lets the customers to encash their credit or debit card through the app. The points can be redeemed thereafter over the app itself.
Role of analytics in Pradhan Mantri Jan Dhan Yojana (PMJDY)
The analytics is operated via operational CRM and analytical CRM. The operational CRM will get all the data and pass it on to the back end. The rest of the work is done by the analytical CRM.
“As of now, SBI doesn’t have a full fledged CRM but we have a large part of what we should be having. SBI has a customer-one view – with complaint and lead management,” says Ghose.
As per the analytics reports sourced internally, under the PMJDY, micro insurance and tiny recurring deposit schemes are popular. These are deposits of Rs. 50, Rs. 100 etc a month.
