Introducing Big Data Lake to Indian Banking System; SBI’s Path-breaking Stunt

Introducing Big Data Lake to Indian Banking System; SBI’s Path-breaking Stunt
The Siliconreview
21 September, 2017

In a move to analyse internal and external data to create a customer profile, State Bank of India is eyeing to implement a big data lake – a one-point data processing and storing warehouse. The bank, India’s largest lender, looks to scrutinize vast pools of data, including that generated on its social media platforms.

It’s learnt that such practice where banks analyse data both internally and externally to enhance their customer offerings is common worldwide. However, the banks in India have somehow skipped to embrace the technological aspect of widening their customer base.

“Surprisingly, the practice is not widely followed by banks in India,” said Amit Jaju, partner-head of forensic technology at EY India.

While talking to the bank’s chief technology officer, Shivkumar Bhasin, he asserted that SBI is strengthening its data infrastructure to enable large volume of data mining on a real-time basis. 

“The current data warehouses do not hold the capacity to match the pace with such large data volume,” he said.

Mrutyunjay Mahapatra, deputy managing director and chief information officer at SBI confirms that the bank, through the big data lake, is looking at processing unstructured data such as those from social media, and feeds from other agencies.

“We are seeking to process data from Facebook and other social media platforms. And from the 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,” he said.

SBI seeks to rope in eligible parties as to implement the big data lake for the bank in a timely manner, he adds. It’s revealed that the bank’s customer base has grown to over 420 million at the start of this fiscal. And it’s expected to touch a new high after the implementation of big data lake – as it will help find out nature and pattern of transactions.