State of Big Data in Banks Subpar, Survey Finds

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Bankers realize the importance of using Big Data to make better decisions, but few have the technology and internal talent to make the most of their information stores, a survey has found.

The first problem: most bankers surveyed characterize the quality of data in their organization as either "adequate" (30%) or "un-integrated" (27). A smaller group chose "good" (24%) or "excellent" (18%).

This doesn't mean there's a shortage of data in banks. "Banks always have had a lot of data and they collect a lot of data," says Omer Sohail, principal, Deloitte Consulting. "The issue has been not leveraging all this data. More than 70% feel like they're not leveraging the data to the best of their ability." The consulting firm queried c-suite and senior executives at 33 banks, most of which have more than $1 billion in assets.

Surveyed bankers are less than thrilled with the state of analytics technology in their companies. About 16% said their analytics tools were "rudimentary" (meaning, spreadsheets and basic reporting tools); the majority (50%) said they had basic reporting tools with limited predictive analytics. Only 6% said they have the highest level of technology identified in the survey: reporting and predictive tools, plus tools for analyzing unstructured data, with prescriptive triggers and alerts. A third (30%) of the bankers said their organization doesn't even use analytics in its strategy because it lacks proper technology and infrastructure.

In their marketing analytics projects, banks are trying to predict patterns of behavior and life events so they can target particular offers at the right time, Sohail says. "There was a belief about 20 years or so that if a person was just about to get new job, they'd go buy a car, probably rent an apartment, down the line they're going to get married, buy a house." Banks would market based on those assumptions.

But with additional streams of real-time data available, "they're becoming smart," Sohail says. He views Bank of America's BankAmeriDeals as an example of a bank using analytics to monitor customers' buying habits and provide real-time offers from relevant merchants.

Sohail also sees banks stepping up their use of risk analytics, especially in the areas of stress testing, market risk analytics, and operational risk.

Voice analytics is another area in which Sohail sees renewed interest. "When bank customers call in to the call center, they usually have an issue or want to make payments," he points out. "They have a history of the voice record, so it's not just about first-call resolution any more, it's also about things like analyzing the tone of voice, or combining voice and tone with speech recognition on certain words, such as 'I'm calling my lawyer,' that indicate there's a problem."

Overall, the Deloitte survey found that 88% of financial services respondents believe analytics will become more important in the next three years. "The validation is there," Sohail says. "Everybody feels analytics is important. Some issues around talent are there, but still a lot of people can use basic reporting tools."

In the survey, only 30% of financial services companies reported that they have staff with the right analytics skills.

Case in point: HSBC wrote in a recent job posting that it's seeking to recruit "candidates of the highest calibre to develop into the roles of Data Scientist. Described in the Harvard Business Review as 'The sexiest job of the 21st century,' these exciting new positions are likely to play an increasingly key role at HSBC."

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