Consider this scenario: Your most valuable bank customers are considering reducing their deposits with your bank. You may know what to say, but do you know how to identify the customers?
The clock is ticking.
Global economic caution and the Fed’s rate reductions are causing consumers to scrutinize their finances, and especially their deposits. If interest rates get cut again, as predicted, a bank that is not a market leader on yields risks reductions among price-sensitive households. And you can count on it: These households are already comparing rates.
The evident solution is to get ahead of the customer’s desire to lock into better interest rates and secure the relationship with this high-value customer. This takes identifying the at-risk households through statistically modeling and testing different offers across various channels.
But today there is a twist: Customers are influenced by far more variables and options, from online-only banks to more complex relationship pricing structures that award deposit consolidation product combinations. Yesterday’s modelling process alone no longer helps a bank recognize its most at-risk customers of today; at least not reliably.
In this column, I’ll explain how to find the households most likely to reduce their deposits using a stratification process from which banks can develop more reliable models. I’ll then provide some examples of how banks can respond to prevent rate-related attrition.
Create the Models: First Find the Skews
Finding households most likely to reduce their deposit positions requires a formula I call the 80/18/2. Here’s how it works.
While roughly a total of 20% of deposit households control 80% of total deposits pretty consistently across banks and credit unions, the 20% proportion can be even more skewed within subgroups. By digging into the household numbers, a bank may find that a much smaller percentage of high-deposit customers, about 2%, holds a much higher percentage of those deposits.
We identify these subgroups by classifying them based on deposit ranges and then calculating the percentage of the total deposits each group represents. Take, for example, one of our bank clients. It counts 180,000 households, 39,600 of which carry more than $10,000 in deposits. That translates to 88% of the bank’s total deposits.
Further, about 2% of those households hold more than $100,000 in deposits and control 35% of the total.
Focusing on those two customer segments – customers between $10,000 – $99,999 in deposits and customers with more than $100,000 in deposits – the bank should create models to predict the likelihood of a household reducing its deposits over a 30-day period. The reduction of a household’s deposits is the first step of this important relationship leaving the bank. If the model was based upon account attrition, it would be too late to take any action as the customers have already established accounts and moved their balances to the competition.
After identifying the households that are apt to reduce their deposits, the bank should also create a second model on the same population to predict the amount of the deposits. Using these two models together, the bank not only could identify the household that is going to reduce its deposits, but also by how much.
Tease Out the Differences in the Models
This stratification process enables banks to identify other significant differences and similarities among high-deposit households, as well.
Those households carrying more than $100,000 in deposits are more likely to be serviced by private bankers than households carrying $10,000 to $99,999, for example. They also tend to have longer-standing, multi-service relationships.
How often the models are run – weekly or monthly, for example – is a key consideration because the timelines dictate the actions the bank will take. The size and activity of the most valuable households should be the guide.
Take Action: 4 Examples
Once the target households are identified, the bank can extend services and offers relevant to each segment. Again, customer value should be the guide. Here are four examples based on various model outputs.
- If a high deposit household is more likely to reduce deposits by $5,000 or more. A senior representative of the bank should check in with these customers and offer to personally analyze their portfolios (gratis, of course), make recommendations to improve performances or learn if there are any service issues and get ahead of the problems.
- If the household is shopping for a better rate. Modeling can determine which offers would resonate with households that have previously shopped around. A well-timed, high-yield savings account or a CD offer could keep such customers engaged and even generate additional deposits. (That being said, we don’t recommend soliciting households with maturing CDs that have a long history of renewal because traditionally they stay put.)
- If the household is not likely to reduce deposits. When modeling, it’s essential to analyze activities on the opposite end of the model and isolate households who have the highest likelihood to increase their deposits with you. These “opposite” customers may have capacity to significantly increase relationships with the bank, generate additional deposits and should be solicited to consolidate their deposits with you.
- If the household does not have a checking account at all. A high-deposit customer with significant upside deposit potential might jump at the offer of a premium checking account with the right incentive. The result of this checking account cross-sell is a core account, a more stable, less price sensitive customer relationship. Some major banks offer their highest-deposit customers more than $1,000 in cash bonus for opening new checking accounts.
These offers could be highly effective, but only if the bank is able to identify its most important customers first. It’s a process of targeting, setting up carefully thought-out offers that do not entirely reprice the portfolio, and communicating to the customers in their desired channel. This sometimes means a telephone call or even a lunch conversation for customers with more than $100,000 in deposits with a bank.
Most important, the process should never stop. Long-term customer relationships require ongoing refinement. So always keep talking to these high-deposit customers and building relationships.
Written by: David Funsten -SourceLink’s Vice-President of Financial Services Strategy. David has over 25 years’ experience in database marketing and customer relationship management, with a focus on direct marketing and omni-channel programs for retail banks and lenders. Reach out to David at firstname.lastname@example.org.