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Despite billions of dollars in cost cuts in 2016 alone, large US banks are still struggling to make their numbers.
In Q3 2016, three of the top six US banks posted lower YOY profits. During the same period, annualized GDP growth was only about 2%, which suggests that the Fed is unlikely to offer relief in the form of significant interest rate hikes to “cool off” the economy.
With few costs left to cut and no sign that the margin squeeze will loosen in the near future, banks need to evaluate their current portfolios for unexplored profitability opportunities. My belief is that home equity lending is one of those opportunities. De-emphasized when US housing values in many markets plummeted last decade, that market has been quietly reviving. As home values recover, consumers once again find themselves with home equity that can be leveraged at a much lower interest rate than other forms of debt, such as credit cards.
Even though origination rates are returning to pre-2008 levels, today’s home equity market is different. Not only has customer behavior changed as a result of economic upheaval, but also customer expectations are different. There are generational differences, new technologies, and a whole class of competitors who didn’t exist in 2006. Fortunately, data-driven banks can use analytics to find profitability levers across the customer lifecycle.
A structured approach to home equity lending gives banks a greater strategic advantage by building customer engagement at every point in their lending relationship. Historically, banks have focused their data analytics strategies on originations, optimizing rates using dimensions such as customer price sensitivity and competitive rates. Expanding those dimensions and increasing the number of touch points beyond originations allows banks to uncover opportunities by meeting the customer where they’re at. Bank interactions become win-win interactions by meeting the customer’s expectations and bank’s goals.
A recent survey by Nomis Solutions demonstrates that there is significant opportunity for profitability throughout the home equity lifecycle. Sent to home equity lending executives from leading banks, the survey showed that banks are increasing their use of data science. Compared to previous surveys, respondents demonstrated increasing use of analytics in the number of pricing dimensions used to set go-to rates. Two thirds of respondents report using more than four dimensions, and a growing number are using more than six.
But we didn’t see that kind of data-driven insight applied consistently across other aspects of the customer lifecycle where they could increase profitability. For instance, more than 60% offered blanket introductory promotions to all qualified customers with no insight into price sensitivity or other factors. That means that customers who would have drawn funds at the published rate paid less than they were willing to, reducing profitability.
Yet only a little more than one-quarter of respondents use any customer targeting at all for promotional offers. As customer behavioral segmentation moves beyond price sensitivity and banking relationship as the primary drivers, banks are recognizing a broader range of segmentation choices. These insights allow them to uncover pockets of profitability that were missed using more simplistic models.
Another opportunity to increase the profitability of a home equity lending book is stimulating utilization. Even though home equity originations have been trending higher than they have in a decade, utilization has been a real challenge for many home equity lenders. Stimulating borrowing is tricky: generally, consumers either need money or they don’t, but banks can encourage consumers to choose home equity over other kinds of debt.
When asked about their efforts to stimulate utilization, banks reported that they were more actively using data analytics to encourage utilization of existing lines compared to promotional offers. About 44% are using targeted customer offers to stimulate utilization, and only 11% offered expensive blanket promotions. On the other hand, almost 40% of respondents reported that their bank had no formal strategy whatsoever, suggesting that there is still significant opportunity to encourage customers to leverage their available credit.
Analytics based on a deep understanding of customer behavior can help banks identify the signals that indicate which customers may be likely to transfer balances or make purchases using their HELOC. The bank can then design promotions specifically targeting the needs of those customers. This is an area where banks can look at other financial services as inspiration for more innovative and compelling offers. Credit cards, for instance, are very successful in getting customers to transfer consumer debt balances with offers such as promotional rates and cash back.
Unfortunately, not every customer with available credit is going to utilize it. Some will be “silent attrition” – customers you’ve already lost and just don’t know it yet. Others are at-risk customers who could be lured away by a competitor. By using predictive segmentation and competitive insights within a pricing framework, banks turn market data such as ICON LendersBenchmark actionable strategies for targeted retention offers.
Only 11% of the bankers surveyed claim that they aren’t experiencing any attrition, yet less than one-quarter of banks have a formal plan for preventing attrition. That means that 80% of respondents have no way to be certain that they can identify and retain customers, leaving them open to portfolio runoff and decreased profitability.
But the best analytics in the world aren’t enough, even if they drive the best pricing and products. Analytics don’t train employees to provide value-added interactions or ensure that the best offers are made to the most appropriate customers. Banks need to empower their frontline with offer intelligence to make sure that customers get consistent pricing and offers across every channel. This is especially true as customers migrate from traditional banking interactions and show a preference for digital engagement.
The Nomis survey suggests that banks aren’t fully exploring how to increase profitability by improving the channel experience for home equity customers. This year, banks were asked about their mobile strategy for home equity. Despite the fact that the majority of users in all segments except Baby Boomers like to use their smart phones to interact with their banks, not a single bank had implemented a mobile strategy for home equity. This seems like a huge missed opportunity for engaging mobile-first users.
It’s true that rates could rise sooner and faster than expected, easing the margin squeeze, but that won’t eliminate the pressure to increase profitability. In fact, lending portfolio managers may be under even more pressure to quickly deliver results when economic conditions improve. With the appropriate data analytics employed across all phases of the customer lifecycle, banks will be able to accelerate their profitability compared to competitors because cost-cutting isn’t the path to market dominance.
About The Author
Rutger's areas of expertise include cross-border project management, PMO development, M&A integration, business development (both B2C and B2B), product management, strategy development, international mortgage origination and securitization, planning, coordination and implementation.