The RPA implementation at Muthoot Group began in May 2018. Overall, at the Muthoot Group, RPA is impacting risk management, which includes frauds, KYC, credit appraisal, AML, customer service and surveillance. The company offers gold loans and thereby gold worth hundreds of crores is kept in over 4,500 branches across the country. It’s manually overwhelming to monitor the multiple cameras deployed at the branches. RPA helps in monitoring the cameras and provides alerts as per the events defined. Manual monitoring in this case is not feasible and ineffective.
The customer’s personal information has to be validated before service activation. Details like mobile number, ID proof, etc, have to be matched with the respective database. For instance, driving license has to be validated with the driving license database of the respective state. RPA helps the group to enable that. Earlier, it was done manually. The exercise saves time and gives accurate results because with respect to the driving license verification, every state stores data in their respective format resulting in complexity and having a modular approach. With RPA, the same exercise has become relatively easy.
K N C Nair, Group CIO, Muthoot Group, says, “The particular reason why driving license verification is important because we have found that many gangs operating in North India steal gold and pledge it with gold loan companies like us by using fraudulent driver’s license. They don’t prefer Aadhaar or PAN card.”
The Muthoot Group is also in the business of money transfer and the regulator insists on having checks for money laundering. The company gets the list of suspicious people from the authorised sources, which is updated on a daily basis. RPA helps in verifying the authenticity of the credentials of the customers.
Loan origination system
RPA is used to collect the data from the backend of the customer, who already has a financial relationship with the company. When the customer has been cross sold another product and the re-verification has to be done, it’s not only the backend data that is verified, but data is also pulled from the credit information companies, social media, etc. The data is compiled and a decision is arrived upon. The loan appraisal time has, thus been reduced from five days to a few hours.
Earlier teams from regional offices monitored the events and investigated further. Feedback was taken from the branch manager and team members were informed accordingly. The motion detection sensors are placed, which automatically detect and generate alerts. Image recognition software is used and screenshots are taken to classify an incident as critical or whether it is a false alarm.
Initially, this job was done by a team of 10 people. However, it’s now done by two people without diluting the effectiveness. The company has hired the services of two vendors, both of them are already providing IT services to the company and they have given RPA as an additional tool to the company. For example, the vendor for the loan origination system has tie-ups with RPA vendors. The same company has partnered with the Muthoot Group.