PFM's generating a lot of buzz among banks, which are embracing the tools to build loyalty. But increasing attention is being paid to mining PFM data to make targeted offers to customers, a strategy that first requires boosting consumer adoption.
PFM technology providers such as Lodo, Strands and Intuit are rolling out functionality that helps banks do a better job tapping this data. "Data is probably the most valuable part of PFM," says Mark Vipond, CEO of Lodo. "You not only have information about budgets, but where they are spending their money. Financial services companies deploying PFM need to control and access this data to take advantage."
But despite the potential to enhance their understanding of customers, analysts say that for the most part banks are not ready to mine PFM data. "The promise is greater than the reality," says Ron Shevlin, a senior analyst at Aite.
He and other analysts give a variety of reasons. First, very few customers use PFM. Mark Schwanhausser, a senior analyst at Javelin Strategy & Research, estimates that only three percent of all bank customers use a bank PFM tool (another three percent use an independent PFM provider such as Yodlee or Mint.) "The first thing you need to do is get the PFM base big enough to draw meaningful data," he says. Given low usage, no history of PFM data, and a lack of expertise to interpret the data, banks face significant hurdles before they can effectively mine this data.
Cathy Graeber, founder of consulting firm Swimming Upstream, says there is another critical problem for banks: undifferentiated products that are not competitively priced. Even if they could mine aggregated PFM data, she says, many banks don't have a compelling counteroffer for customers.
Even so, Graeber believes PFM has enormous long-term advantages. She conducted a case study last year of a top 100 credit union and compared PFM users with online customers who didn't use PFM. She found that PFM users visited the credit union's Website twice as often (18 vs. nine times per month), had on average 3.7 products compared with 3.4, and had nine percent higher balances. The differences were even more pronounced among Gen X and Gen Y users-balances that were 19 percent higher.
"You're serving your best younger customers. You're not necessarily changing behavior but you're locking them in and not losing them to a third-party provider," she says.
But vendors are betting that banks and credit unions will soon be focusing more on how to make use of this PFM data. Lodo Software launched the FI Dashboard in February, a cross-selling tool built to work with the company's OurCashFlow PFM solution. Lodo's dashboard captures data about PFM users-including assets, accounts, transactions, budgets, savings goals and spending activity. The software organizes and analyzes the information, allowing financial institutions to target customers to receive a product or service offer. For example, a bank marketing manager can set the FI Dashboard to send a weekly message that promotes a CD to people who hold more than $10,000 in their savings account. Or they can offer mortgage refinancing to high-net-worth customers whose current mortgage interest rates are greater than six percent.
Elsewhere, Intuit's FinanceWorks rolled out cross-sell functionality in mid-2010 that also lets bank employees design marketing campaigns based on criteria such as account balances and interest rates. "Our sweet spot is smaller community banks and credit unions looking to differentiate themselves from big banks," says Mark Shulman, FinanceWorks product manager. Meanwhile, Strands, another PFM provider, recently launched a business intelligence application that plugs into the Strands PFM platform and provides a dashboard view of customer data, analytics and key metrics. "It's hard to get actionable insight with so much data," says CEO Ed Chang. "We're trying to help banks filter it down so a bank analyst can get actionable data in a quick way." Bank of Montreal is among Strands' adopters.
However, Aite's Shevlin notes that even these cross-selling products do not involve sophisticated data mining in its true sense. Instead, they can broadly segment customers. For instance, with FinanceWorks a bank can quickly launch a marketing offer but it can't provide an aggregate number of potential customers. "But as banks add PFM functionality it will be a platform for engagement that will help enable cross-selling."
