Big Data and Predictive Analytics: A Big Deal, Indeed

By Charles Keenan

When it comes to predictive analytics and big data, it’s well-documented that some banks have been relatively slow, compared with other industries, to invest in the technology.

But now might be the time to ramp up.

For one, the banks regarded as leaders in analytics are deepening their capabilities in order to better serve customers. With lending, there’s also the threat of nonbank competitors using analytics to make loans in minutes. Analytics are also playing a role in the regulatory environment around fair lending violations.

A slow start
No doubt, banks have trailed other industries in use of analytics. Retail is well ahead of banking (think Amazon). So is search (Google) and insurance (Geico).

Despite the gap—and maybe in part because of it—the future is bright for banks.

“We are still in the relatively early stages,” says William Losch III, EVP and CFO at the $26 billion First Tennessee Bank, based in Memphis, Tenn. “We have got a ton of opportunities to do a lot more with analytics than what we do today.”


Important, but Not Most Important: How Bankers Rank Analytics Compared to Other Technology Investments

Just in terms of spending, it’s clear the interest of banks in analytics keeps rising. Financial institution spending on marketing analytics and customer data is expected to total $2.8 billion in 2015, up from $2.6 billion in 2014, according to the Aite Group, a consulting firm. That number is expected to rise to $3.2 billion in 2017.

Use of analytics will certainly increase simply due to banks’ retail goals. About 78 percent of bankers listed “improving sales results” as a top-one or top-two retail-banking priority, according to a Celent survey published earlier this year. About 53 percent listed improving customer relationships. That compares with 28 percent listing cost reductions, 24 percent regulatory compliance and 19 percent fraud and risk management.

There’s a host of reasons why banks have held back spending on analytics, including privacy concerns and the cost for systems and past merger integrations. Analytics also competes with other areas in tech spending; banks rank digital banking channel development and omnichannel delivery as greater technology priorities, according to Celent.

But banks really no longer have a choice of whether to get into analytics. In the days when most banks’ interactions with customers took place in branches, substantial judgment was involved, notes Bob Meara, a senior analyst with Celent. Real people would listen, interpret inflection and observe mannerisms in order to best serve the customer.

But now customer interaction is moving to the digital space across all demographics, taking more human interaction out of the equation. “Analytics is the only way you can hope to personalize and influence favorable outcomes,” Meara says. “Analytics will have to be your eyes and ears.”

Forming relationships
Many institutions today are placing greater emphasis on helping customers meet financial goals, with a longer-term goal of building a relationship holistically rather than promoting a specific product for short-term gains.

Financial Institution Spending on Marketing Analytics and Customer Data, 2012 to 2017, in Millions of Dollars (Source: Aite Group)

Financial Institution Spending on Marketing Analytics and Customer Data, 2012 to 2017, in Millions of Dollars (Source: Aite Group)

“When we use analytics, we need to let the customer know how they are managing their money today, and make recommendations about on how to help them reach their goals,” says Edgar Enciso, EVP and director of customer intelligence at BBVA Compass. “This is where most of the opportunity is.”

At BBVA Compass, a U.S. subsidiary of Spanish bank BBVA with $82 billion in assets, analytics are helping staff identify which customers generate better responses to offers, what segments are taking those offers and what keywords customers are using to search the Internet for answers to their financial problems, Enciso says.

Transaction analysis also helps the bank determine when to proactively send out new checkbooks or alert a customer to pay a bill. The bank has also been working to alert customers to how they can get more points in credit card rewards. BBVA Compass has also moved into the realm of using social media and website browsing patterns to cross-sell potential products, such as mortgages to a customer who has been searching for home loans.

Analytics help banks get a clearer view of profitability of products, and that view is getting more refined. At First Tennessee, only about 40 to 45 percent of products are profitable when the bank takes into consideration the capital needed to back up loans, according to CFO Losch. But rather than shelve those products, the bank uses the numbers to show its front-line salespeople that some of the unprofitable products might lead to a broader—and more lucrative—banking relationship down the road. The data also shows what industries have higher credit quality and are more apt to have cross-selling opportunities.

“When you are thinking about product positioning, you always do whatever is right for the client,” Losch says. But for loans, First Tennessee can say, “here are the characteristics of higher-value lending relationships versus lower-value lending relationships. We have been able to break it down so that it is much more actionable for the front line to use the information.”

Increasing competition as a driver
Another compelling reason for banks to deepen their involvement with analytics is that banks face stiff competition outside of the industry. “Silicon Valley is coming,” says Jamie Dimon, chairman and CEO of J.P. Morgan Chase & Co. in the company’s annual shareholder letter this year. The startups are “very good at reducing the ‘pain points’ in that they can make loans in minutes, which might take banks weeks.”

These newer entrants have gained momentum as they target underserved markets of consumers and small businesses, using analytics to score risk. Peer-to-peer lenders such as Lending Club and Prosper have grown fast. Lending Club, for example, facilitated $3.6 billion in loans for the first six months of this year, up 97 percent from a year earlier, according to its second quarter earnings release. OnDeck, which lends to small businesses, uses analytics to lend to riskier small business borrowers.

Meanwhile, banks must balance keeping up with the competition while also paying close attention to privacy and fair lending regulations that apply to depository institutions.

“Our industry is continuing to come under pressure from competitors that are not in our industry,” Losch says. “Nonfinancial tech companies can disintermediate the most profitable businesses from the banks and not be subject to the regulation we are subject to.”

Fair lending considerations
Fair lending itself is reason enough for banks to invest in analytics. This is especially the case with mortgage data, as regulators pore over banks’ Home Mortgage Disclosure Act data looking for anomalies and patterns. But banks are also getting cited for violations in other areas of consumer lending. In one of the more noteworthy cases, the Consumer Financial Protection Bureau and the Department of Justice ordered Ally Financial Inc. in December 2013 to pay $80 million to minorities allegedly harmed by disparities in pricing for the bank’s indirect auto loans. Ally, which has $105 billion in assets, had to pay another $18 million in penalties.

“It’s in every bank’s best interest to get one step ahead of the regulators and understand what that regulator is going to know and find,” says Carl Pry, a managing director at Treliant Risk Advisors. “They need to resolve any discrepancies [and]do any file review analysis needed to be able to explain any disparities before the regulators find them.”

A June Supreme Court decision also added urgency for using analytics. Texas v. Inclusive Communities Project ruled that disparate impact claims, under certain conditions, are enforceable under the Fair Housing Act. So even without discriminatory intent, a financial institution may find itself having to explain uneven lending patterns. Better to spot and analyze those patterns first than learn of them in a court filing.

“The degree of sophistication expected of banks these days in the fair lending space has increased dramatically,” Pry says. “Any bank that doesn’t use any more sophisticated tools than Excel is probably facing a criticism that their program is not at the level that it should be to identify where the problems might be.”

Joseph Porter Jr., a partner at the St. Louis-based Polsinelli law firm, advises clients to do the analyses themselves, before the examiners come in and allege—say—discriminatory pricing of loans made to women. “If you’ve got a problem, you have to lay the defense groundwork in your loan portfolios so to show that reason for a percentage was the age of the car, not the fact they were women,” Porter says.

The Ally case was a signal by regulators to all banks, warns Sheldon Hendrix, a senior managing consultant in the Houston office of BKD, an accounting and advisory firm. “Whenever they start these trends, they attack the biggest dogs first and it starts to trickle down,” he says. “Every institution would benefit from some type of software.”

All in all, analytics will become ever increasingly a part of banking. “The industry is going to be a lot smarter where the opportunity is—where our customers are wanting to interact—as opposed to waiting for that opportunity to see them,” Losch says.

Charles Keenan is a freelance writer based in California.