The 80's called....it wants its deposit pricing strategies back. So put down the walkman and turn off Cheers because there is no specialized software, subscriptions, machine learning, AI, separate databases, or IT work required to bring your pricing capabilities into 2020.

Seems like the 1980s have become all the rage again in fashion, film, and most especially banking. When I began my career the senior executives would tell me of the old banker’s axiom to live by; “3-6-3” they said, “deposits at 3%, loans at 6% and you’re on the golf course by 3:00pm”.  My, how times have changed- or have they?

On a daily basis we see oversimplified, heuristic, and inefficient pricing processes abound.  Don’t believe me? Take a look at your deposit rate sheet (or your competitor’s).  How many of your price points end with a “5” or a “0”?  If the answer is more than half, then you are almost certainly pricing using the BOPSAT method to price your deposits (BUNCH-OF-PEOPLE-SITTING-AROUND-A-TABLE). 

Curiously, American Banker recently conducted a study to evaluate perceptions at banks over $10b in assets with respect to their pricing capability. Unsurprisingly, 87% of bank executives who responded rated their price setting and optimization capability as “Advanced”.  It reminded me of my undergraduate Psychology class when they referenced the study that asks participants “Do you consider yourself an ABOVE-average driver?” and nearly 100% of participants answered in the affirmative.

When phrased as a confidence question: “Are you confident in your bank’s pricing capabilities?” you, your CFO, and the president of your financial institution will almost always answer “Yes!”- so let me phrase this differently.2020DepositPricingstrategy

Are you better at pricing your deposit products than Amazon.com is at pricing a Casio calculator? Better than Delta at pricing a seat from Orlando to Minneapolis? Better than Marriott at pricing an ocean view king room in Marina Del Rey? Better than Wal-Mart at pricing 13-gallon garbage bags?  I suspect your answer is less enthusiastic. Financial Institutions should be much better at pricing, but categorically we’re not.  The reasons are myriad, but usually have to do with staff talent, bandwidth, systems, or perceptions that compliance would never allow a more dynamic pricing structure.

So how do we upgrade our pricing capability? First, let’s align on definition. When we say “price” let’s agree that we are referring to the APY paid on a deposit balance (or an APR on a loan if you happen to work on both sides of the balance sheet). We’ll save fees for another blog post. This APY may be publicly posted, may be a back-pocket offer, a promotion, a relationship price, or be off-menu or “back book”. Whatever the schema applied, the APY that appears on your customer’s statement is the “price”. 

Step 1: Count your pricing cells

How many pricing cells or price points do you offer between your front book (the prices on your rate sheet or being actively offered in the market) and your back book (the prices that are not actively offered, but are still being paid on existing client accounts)?  If you don’t know the answer to this question, drop what you are doing and go find out.  The cardinal sin we see in the market is that larger financial institutions have too many pricing cells (we ran an analysis of large US banks, and total deposit pricing cells range from 1,700 on the low end to over 20,000 at the extreme high) and smaller financial institutions have too few pricing cells (10-20 for term deposits and 10-20 on all liquid products).

Discovering the number of pricing points may not be easy.  The first step would be to review your current rate sheet and count the number of different combinations of prices (example- standard money market account, tier $10,000 to $25,000, non-relationship rate at 0.50% APY in Region X would be 1 pricing cell). Next, count all your promotional and relationship rates currently being sold.  Next, you will need an extract of every deposit account (remember, look at accounts, not customers- many customers have multiple accounts) and be sure you capture the balance, open date, and APY paid on the account from your data warehouse or core system, or your finance department may already have this report.  Each account should be one row (for banks with over a million customers you will likely need some help from an analyst on your team to put this into a tool built for business intelligence). Now that you have a row for every account, sort the list and subtotal the different APYs paid by product.  You may be shocked by two things: first, how many products you actually have on your system, and second, how many pricing cells exist between your front and back book.

Step 2: Separate your front book pricing cells

The second cardinal sin we see in banks is pricing different cells at the same price. For example, a money market tier that pays 0.50% APY at the $10,000 to $25,000 level and at the $25,000 to $50,000 is nonsensical. Creating separation will allow you to pay more in the higher term while saving on interest expense in the lower tier. This action seems like common sense, but we see violations abound.  The separation in tiers also forces the customer to make a choice; bring more money or take a lower rate. When the tiers are the same the customer has no reason to put more money into your institution to earn the higher rate. The customer is then free to keep money in a different deposit product or at another financial institution. The core principal of your retail rate strategy should be built around forced trade-offs - does your customer want a better rate? Then they need to bring a bigger share of their wallet or lock up their money for longer.

While we acknowledge the rate environment is flat, it is not so horizontal that your financial institution can’t put in at least 1-2 basis point of difference between cells. Some smaller institutions take the easy road and just go up by 5 basis points for each tier or term, larger institutions aren’t usually so generous, but are rarely any more scientific in their approach.

Step 3: Shock the system

Did your customer choose to put their dollars in their deposit account because they liked the rate, or for another reason? Given a snapshot of your portfolio today it’s impossible to tell.  When you “shock’ your rate sheet you get an idea of who’s chasing rate and who values other benefits your financial institution provides. Your ALM software and risk or finance team are already performing their own shock tests of the portfolio, but we’re talking about something different.  Shocking your rates means making a series of adjustments in short order, but keeping your interest expense flat or down. To do this properly you will need to refer back to your subtotals of balances by product and tier. The next step will be driven primarily by the balances and APYs of each pricing cell. 

Step 4: Measure Results and Adjust Strategy

With improved understanding of the portfolio and a snapshot of where you stand before making changes you will be positioned to measure outcomes. Measure at 30, 60, and 90 days after your “shock date” to see how your balances have shifted between buckets, what money has come in, what has gone out, what has moved from liquid to term, and how much hasn’t moved at all. The customers who have moved money from a lower APY to a higher APY are your rate sensitive customers. Tag them for future campaigns. Customers who could have done something but didn’t are your less rate sensitive customers, tag them as well for future reference when your executive team is deciding what to do in the future (e.g. a large block of term deposits is maturing and you need to decide whether to match or beat the market in your rollover rate). 

Enhancing your deposit pricing capability can start simple. The steps above require no specialized software or subscriptions, no machine learning, AI, separate databases, or IT work, though all of those investments will help your institution progress along the maturity curve. Any financial institution can revisit their portfolio and create occasional shocks, then measure results and apply that understanding of customer behavior in executing more granular and intelligent pricing decisions. So next time you are thinking about running a deposit rate promotional offer, take a step back and think about running a “shock and ahah!” campaign instead.

Now, looking for a way to pull all this data together quickly? Join the upcoming webcast with CBA. If you need a discount code, message me on LinkedIn.