SBI plans to set up big data lake to enhance customer offerings
SBI is setting up a one-point data processing unit for data storage and analysing vast pools of data, including that generated on its social media platforms
Mumbai: State Bank of India (SBI) has started the process of implementing a big data lake, a one-point data processing and storing warehouse, as the country’s largest lender looks to analyse vast pools of data, including that generated on its social media platforms, to enhance customer offerings, according to senior officials of the bank.
Through the big data lake, the bank is looking at processing unstructured data such as those from social media, and feeds from agencies providing economic data and credit scores, along with data generated within bank to get insights into user experiences and upgrade its risk management capabilities, said Mrutyunjay Mahapatra, deputy managing director and chief information officer at SBI.
SBI has sought expressions of interest from eligible parties for providing software solutions, services and implement a central big data lake for the bank.
Following the merger of five associate banks, SBI’s customer base has grown to over 420 million at the start of this fiscal. The bank is also seeing a rise in the number of digital transactions through mobile phones, payments solution applications as well as its website.
Currently, it has around 2.5 million followers on Twitter and over 13 million users for its Facebook page.
SBI, under the chairmanship of Arundhati Bhattacharya, has focused on technology, according to analysts. In fact, one of the key reason for the seamless merger with its associate banks was the use of data analytics as the bank got various insights for better branch optimization, human and technology integration.
According to chief technology officer Shivkumar Bhasin, the bank is strengthening its data infrastructure to enable large volume of data mining on a real-time basis.
Post-merger of the five associate banks, transaction volume has grown exponentially, generating data of around 6-8 terabytes a day.
“The current data warehouses cannot work with such large data volume,” he said.
“Big data lake will help find out nature and pattern of transactions, including those conducted in the past, on a real-time basis. This will help us dynamically provide various offerings such as cross-sell of other financial services product, different kind of loans, etc., through digital channels,” Bhasin added.
Amit Jaju, partner-head of forensic technology at EY India, said that while such practice where banks analyse internal and external data to create a customer profile is common worldwide, it is not widely followed by banks in India.
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