How Big Data Is Becoming Critical In Asian Banks 

big data in asian banks

Whether it’s marketing, customer service, back-office, fraud detection or audit & evaluations, Asian banks stand to gain immensely from Big Data in the coming years.  

As per a Nielsen report Asian banks will witness a transaction volume upwards of USD10trillion by 2015!.

And a Gartner report last year stated that within Asia-Pacific 45% Banking & Financial players indicate that they plan to invest in big data during the next 2 years. 

As per Scott Russell, COO, Asia-Pac & Japan, SAP, he mobile banking platform at Barclays UK had zero customers. Now it has 3.2 million customers who log in an average of 28 times monthly, giving the platform 80 million logins a month. The result? Loads of Big Data 

But where is this huge volume of data coming in? 

Today’s banking users are 24*7 on mobile and keep accessing banking services from various time zones and locations and they need data in real time.  There are 3rd party services that are now integrated with banks like utility bill payments or payments via apps. 

The consumers also interact with banks more via social networks and essentially they prefer to do banking without really having to go to the branch. While doing all this consumers not just access data they also create data…big data.

How can the banks leverage big data?

Social media feeds can help bank’s capture trends and sentiments and that can help them innovate or create better products and customer service

Banks can leverage big data to check abnormalities in deposits or debits or online payments, they can also use big data to identify potential defaulters.

As per Russell, CBA (Central Bank of Australia)  processes nine million transactions per day, handles 40% of the card transactions in Australia and maintains 12 million account profiles. If a customer makes an unusually large deposit, the automated system will trigger a workflow that suggests a relevant offer, encouraging that customer to keep her money invested at the bank.   

Banks can also use data analytics to map the lifecycle profitability of each channel thereby closely analyzing the flow of transactions and linkage with shopping behavior and preferences


• The CIOs need to talk to the CMOs and business heads and include the marketing and truly understand the business   strategy.
• Draw an actionable plan with clear goals 
• Be ready to invest in infrastructure. Big data needs a great data resource capability so as to collect        unstructured and structured data
• Data flow and post analysis in such a way that it reaches the right people in right time
• And of course, be conscious of data security & compliance.

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