The phone rings at the relationship manager’s desk. It’s another commercial customer asking for a higher rate. The customer is only getting 80 basis points and wants one closer to the far higher target Fed funds rate. For the third time today, the banker opens his “rate sensitivity tracker” and adds this customer to the “rate sensitive” customer list.
And now comes the important decision — how does the banker decide on the “right” rate for the customer?
TODAY’S INTUITION-BASED DEPOSIT PRICING
Such a scenario is playing out daily at banks across the country. Many banks make this decision based on a combination of banker experience and intuition. Customers who seek a higher rate put the bank in a defensive position that often ends with the bank offering a rate that is above the optimal and fair price for that client’s deposit.
This approach can bring emotion and inconsistency into pricing decisions and is all but guaranteed to be sub-optimal. Further, given the recent extended period of very low interest rates, many bankers lack experience in pricing deposits in a rising-rate environment. Their first experience with rate-sensitive customers may be the loss of a large client balance because the bank didn’t pro-actively offer a higher rate. Additionally, competitive deposit rates are all over the map, ranging from seven basis points to 220 basis points (see Figure 1).
Banks can no longer afford to make these sub-optimal decisions. Novantas has identified significant value in implementing advanced pricing methods, techniques and processes; such efforts can result in a reduction in betas of up to 10% and a drop of as much as nine basis points in deposit costs. It is time to incorporate consistency and science into setting deposit rates, while retaining the “art” to better leverage the customer relationship.
Novantas has identified three steps that will help lay the foundation for strong rate management: a deeper understanding of customer behavior, determining how those insights drive deposit value and using analytics to segment customers so that a bank can align rate offers to the “right” customers.
WHEN THE EXCEPTION BECOMES THE RULE
One of the major challenges with the current approach to deposit pricing is that the incidence and magnitude of non-standard rates has increased significantly. Exception rates now represent approximately 50% of commercial-deposit balances, according to data compiled by Novantas. While this represents about 20% of customers, most banks find this level of exception pricing difficult and inefficient to manage.
Oftentimes, small pricing teams are fielding all exception rate requests because the bank lacks analytical tools needed to make data-driven rate decisions. As a result, these teams become overwhelmed by the volume of exception requests, especially as interest rates continue to rise.
MAKING THE TRANSITION TO DATA AND ANALYTICS-DRIVEN PRICING
Customer segmentation is the key to smart rate management, but it can be uniquely challenging for commercial customers when the right tools aren’t in place. Novantas believes customers should be grouped according to deposit value, defined as deposit persistence or retention, customer rate sensitivity and balance levels. That enables a bank to make better use of rate offers that reward or incentivize desired behaviors or to manage risks like balance attrition and increased deposit costs. Finer segmentation also allows banks to reduce exception rates, leading to fewer manual, or intuition-based, rate decisions.
The first step in achieving refined customer segmentation is to understand where and how customer balances move. What is part of “normal” or expected cash flows and what isn’t? To do this, a bank needs to analyze a meaningful history of client balances, rates, transactions and relationship factors. Novantas has developed proprietary methodology to define which customer balance movements are related to their operating cashflows, and which movements appear to be more discretionary.
This is a critical step toward understanding customer deposit behaviors better because it segments customer deposits — both across and within deposit product types. Discretionary balances are a bigger driver of the balance/rate relationship than are operating balances, so it’s important to understand the behaviors of these two distinct types of cash.
Novantas sees three primary levels of customer segmentation, ranging in complexity from low effort and low impact to highly rigorous with large impact.
REFINE CURRENT SEGMENTATION
Most banks set deposit rates by segmenting commercial customers according to deposit product type and, to some degree, balance level. Novantas has found that even simple sub-segmentation within this basic structure can yield measurable improvements in deposit costs. This approach works well when a bank lacks more sophisticated analytical tools or teams, as it is easier to execute.
CREATE NEW, BEHAVIORAL-BASED SEGMENTATION
In the next tier of complexity, banks create new segments derived from the empirical analysis to identify customer behaviors that drive value.
This segmentation allows for the aggregation of seemingly dissimilar clients into behaviorally homogeneous groups. Examples may include relationship depth, level of discretionary cash versus operating cash or sophistication of cash-management practices.
This approach requires the ability to generate and update behavioral analytics and metrics at the customer level, and to share that information with sales and product teams in a way that facilitates better pricing. This level of segmentation can generate improvements in deposit costs that are two times greater than simpler segmentation.
DEVELOP CUSTOMER-LEVEL SCORES
The newest development in deposit pricing is customer-level scoring, and the application of scores to segment and price customers. Scoring ranks clients based on their behaviors and characteristics that indicate high likelihood of positive response to rate treatment, which allows for more targeted and proactive distribution of rates. This segmentation methodology provides the most powerful customer-level insights and has the biggest impact on improved deposit performance, but requires sophisticated data and analytical capabilities.
PUTTING SEGMENTATION INTO PRACTICE
Customer segmentation is more than an interesting analytical exercise; banks need it to differentiate rate offers in a more systematic way. It can help banks determine how and whether to move rates on the overall “back book”, for which customers and by how much. It can also assist bankers in responding to customer requests for higher rates. And these analytical tools can help banks price new deposits.
Still, banks must be reminded that even the most sophisticated client segmentation will not work if the infrastructure does not support the required data, analytics and reporting.
Manager, New York