The Reason Financial Analytics Leaders Have Higher Profitability

The more you analyze, the more likely your decisions will be superior to those of competitors. JL

Tom Groenfeldt reports in Forbes:

"Only 0.5% of data is ever analyzed, and the amount of data is growing faster than the amount of it that’s analyzed.” Analytical leaders don't leave data and analytics to departments -- they hold it centrally impos(ing) uniform standards for how it is gathered, stored and used. Good analytics companies are 2x as likely to be in the top quartile, 3x as likely to execute decisions as expected and 5x as likely to make decisions faster.
The phrase “Big data is the new oil,” is looking more than a little shop worn. Most organizations have far more data than they know how to use, write Tom Davenport and Jeanne in the recently reissued and updated book, “Competing on Analytics — the New Science of Winning".

‘The data in their systems is like the box of photos you keep in your attic, waiting for the ‘someday’ when you impose meaning on the chaos. IDC estimates that only 0.5 percent of data is ever analyzed, and we would guess that the amount of data is growing faster than the amount of it that’s analyzed.”

Capital One is a leader in using sophisticated analytics.

The International Institute for Analytics, co-founded by Davenport, conducted a 2016 survey of 50 companies across several industries and found that few were analytical competitors. Amazon, no surprise, had the highest score and financial services firms were the second most analytical industry, but on average banks were not at the analytical competitor level. The lowest ranked industries were health care and health insurance.
The top ranked had four key characteristics:
They supported a strategic capability
Their approach was enterprise-wide
The senior management team was committed
The company made a  significant strategic bet on analytics-based competition
Some of the names in finance will not be a surprise. Progressive Insurance and Capital One have been leaders in using credit scores to improve profits. Progressive was early to understand that people with good credit scores also had better driving records than people with poor credit. But then Progressive, like Capital One, began picking apart those same FICO credit scores looking for potential customers who were better risks than their scores indicated, picking up profitable business that competitors couldn’t recognize.
Analytical leaders don't leave data and analytics to departments -- they hold it centrally or impose uniform standards for how it is gathered, stored and used.
RBC Financial Group decided in the 1970s that customer data would be owned by the enterprise and held centrally. Bank of America decided that interest rate exposure would be managed in a consistent way across the bank.
That emphasis on enterprise-wide approach is fundamental to competing on analytics because departmental analytics tend to rely on Excel. User-generated spreadsheets often have errors, and by their nature create multiple versions of the truth. When business users meet and bring their own spreadsheets, discussions often get bogged down in whose data is accurate. Analytics programs often have to overcome fiefdoms within the organization, the authors write.
Firms that get it right see significant profits. Kroger uses the customer analytics tool dunnhumby, which was so useful to the British grocer Tesco that it bought the company. Kroger grew its same store sales for 52 straight quarters through its customer loyalty program and made millions selling shopping data to food companies. It should be interesting to see what happens as Kroger meets Amazon and Whole Foods.
Capital One saw EPS and ROE grow 20%  year on year through its aggressive analytics. The bank runs about 80,000 marketing experiments per year. It increased retention in its saving business by 87% and lowered the cost of acquiring by 83%.
The authors quote Bain which said that really good analytics companies are 2x as likely to be in the top quartile, 3x as likely to execute decisions as expected and 5x as likely to make decisions faster.
The leaders are not standing still. The CIO of Capital One looks forward to using machine learning to provide more tailored products for customers. Credit Suisse is using Quill from Narrative Science to produce investment research reports on 5,000 companies it covers.
Becoming analytical takes time, and sustained commitment. The authors say it can take 18 to 36 months of working with data to get into the practice, and sometimes the process slips. They recount a conversation with a banker whose firm used to be a leader in analytics but now said the organization was slipping into silos of data. That can lead to unfortunate cases like one they recount where a customer with a $100 million trust account was charged $35 for a bounced check. A manager, who apparently couldn’t see the trust account,  said the customer's savings account wasn’t
large enough to justify waiving the fee.

Analytics is easier at digital corporations like eBay orNetflix than at “a legacy corporation where IT appears to have been built in a series of weekend handyman jobs,” they note.