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Home Retail and Marketing

How Banks Can Use Dynamic Wealth Data

January 30, 2017
Reading Time: 3 mins read

Speaking to the more than 1,000 attendees at ABA’s Government Relations Summit in Washington, D.C. today, Sen. Tim Scott (R-S.C.) criticized the Dodd-Frank Act, saying that the legislation created a “regulatory labyrinth” that has stymied banks’ ability to serve their customers and grow the economy.

By Eric Haller

A post-election tip for banks on getting data right: Combine dynamic wealth scores with traditional insights.

As banks and credit unions look to identify fresh revenue streams in the new year, it’s worth taking a lesson about data from election pollsters. When the candidate who is least predicted to win an election based on polling results ends up with a victory, it’s time to revisit whether you’re looking at the right data.

In today’s low-interest-rate environment, and with a cloud of uncertainty hanging over Washington, it is more crucial than ever that banks ground services in reliable data and analysis, drawing information from the widest array of credible sources. Because when data fails, it can put businesses, households, and our economy at risk, with consumers often being the ones who suffer the heaviest blow.

The key: relentlessly explore innovative new data sources to provide the type of fresh and actionable insights that are so vital to business success today.

Here’s one example. To most businesses, customers with similar credit scores look nearly identical on paper. What if you could sift through these individuals and further identify, through accumulated wealth, spending patterns, and consumer behavior, where the best opportunities lie for your business?

For bankers, that means understanding your customers’ wealth potential, so you can predict future spending habits. For example, households with $250,000 or more in investable assets are 43% more likely to open bankcards than households with less than $50,000 in investable wealth. Each group might be open to widely different kinds of offers from their bank, tailored to their needs.

But how do you know how to target those offers?

Traditionally, data analytics companies have been able to differentiate consumers and predict behaviors by looking at credit score and other credit-related characteristics such as payment history and length of credit history. A new approach to differentiating consumers even further is by using micro-segment data. Micro-segment technology differentiates a given family from its neighbors based on wealth accumulation, lifestyle, and other demographic and psychographic characteristics—rather than grouping contiguous households in a street together as one demographic.

This effort has yielded over 11 million micro-segments in the U.S., which have been captured for banks to analyze and target. With the ability to analyze the most powerful data set, banks have consumer characteristics like affluence, spending habits, home value, marketing, and auto ownership at their fingertips. They also have access to wealth scores verified monthly for every U.S. household, derived from direct-measured investor data, which enables financial institutions to target consumers with unmatched precision.

This approach can help in providing effective and timely products to your clients. While unbanked customers tend to be attractive to banks looking for new business, a profitable relationship can take time and may not always pan out. Using innovative data analytics, however, you can help bolster that relationship, especially during the typical 3-month honeymoon period with new customers. That’s the timeframe when clients are most likely to consider additional services that they may be recommended. However, banks don’t always know much about their customers beyond the accounts they hold at the bank—and even that can be difficult to determine at times when banks have been through multiple acquisitions.

Using dynamic and verified wealth data, you can access an in-depth perspective of a consumer’s complete financial picture, including spending behavior and other financial habits, as well as total liquid investable assets both at your bank and at other financial institutions. This, in turn, can allow your financial institution to offer customers more pertinent services, help them consolidate extraneous assets, and advise them on more efficient consumer behavior. This will make for a happier union between you and your clients, increasing customer loyalty as well as profit margins.

To avoid repeating any analytics mistakes from the past, financial institutions must take advantage of all the new data analytic innovations that are available today.

Eric Haller is executive vice president at Experian Global DataLabs, the creators of Wealth Insight ServicesSM and other advanced analytics, big data and software solutions transforming the FinTech industry. Wealth Insight ServicesSM helps financial organizations make smarter business decisions and build stronger customer relationships through the power of wealth-based strategy and targeting technologies for prospecting, cross-sell and retention.

 

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