“I’m back, baby!” – George Costanza
Much like the great George Costanza of Seinfeld fame, bankers are feeling that the tides have finally turned in their favor. Optimism has returned to the industry, as interest rates are on the rise, the regulatory winds have shifted, and share prices have responded in kind.
All of that optimism has also created some interesting discussions. With technology budgets finally restored – after a drought of nearly a decade – bankers are evaluating wide swaths of their infrastructure, especially those that directly impact the customer experience and revenue. Included in that evaluation for many is a potential overhaul of how they price, negotiate, and deliver deals for their commercial customers. We’ve helped dozens of banks dig into that decision over the last few months. That process has given us the chance to look under the hood at the current processes. To be blunt, it isn’t pretty.
Banks of all shapes and sizes have ignored this process for years, and it shows. There are several recurring issues in particular that are negatively impacting both the banks and their customers.
As you look at reshaping the experience for your commercial customers, make sure you are aware of these seven deadly sins of pricing.
Sin #1: Failure to Scale
Pricing is one of those functions that many banks choose to tackle internally. After all, this is just a little math, and we’re great at math! But while getting the math right is an important step in pricing, it’s far from the only step. We see far too many banks that have stretched poor Microsoft Excel WAY beyond its limits. They’re now struggling to cope with a laundry lists of problems that include: lack of usability, slow processing, formula errors, garbage data, lack of integration, poor version control, difficult updates, and very limited controls, just to name a few.
Pricing impacts the bottom line more than any other function in your bank, and resources should be allocated accordingly. The most progressive banks are investing in platforms that are centered around the customer conversation, using AI to amplify great relationship managers. These RMs are given insight at the time of the negotiation that enables them to be flexible and responsive to their customers. That added value creates happier customers and better returns.
Sin #2: The Wrong Users at the Wrong Time
Many banks have Credit Analysts entering deals into a pricing model as a part of the approval process, but this is too late; by this point expectations on both sides are already set. At best this allows the bank to say no to a deal that it shouldn’t be doing – after making the customer and the credit group jump through a bunch of unnecessary hoops. More likely the bank does the deal anyway, and uses the model results to shame the RM after the fact.
Many banks are now shifting pricing away from pure “models” in credit, and are instead giving a sales and negotiation platform for their RMs. These systems make it possible for RMs to reshape and negotiate that deal early in the process, while it is still malleable. This not only leads to more profitable structures and happier customers, but also greatly reduces the number of deals in underwriting that never get booked. Instead, your credit group can focus its attention only on deals that have been qualified.
#3 Applying Vinegar Instead of Honey
Because of the risk-averse nature of banking, most systems are designed to avoid problems. Pricing is no exception. Banks typically use simple directive when setting up their pricing process: to stop RMs from doing bad deals. With any deal that is entered, there is typically a list of reasons why it won’t work or is outside of policy. The RMs essentially have to clear those “exceptions” to get the deal approved.
We’ve found the opposite approach to be much more effective. Instead of a list of problems, provide your RMs with a list of solutions: “Here are 10 ways we can make this deal better; now find one of those that also works for your customer.” It is a subtle difference, but it dramatically improves the way your RMs structure deals and serve their customers.
Sin #4: Death by “Accuracy”
Bankers get very uncomfortable when their debits and credits don’t balance. This sort of focus is perfectly understandable for much of the business, but it is detrimental to pricing. Asking your relationship managers to navigate lots of extra steps with high degrees of complexity just so we can zero in on the last basis point of origination costs or liquidity premiums is a bad tradeoff.
As scientific as the math can make it seem, we have to remember these are all educated guesses. We are pricing prospective transactions, meaning we are making assumptions about future market and economic conditions, not to mention human behavior like death or prepayments.
We need to be directionally correct, and accurate enough to ensure we are generally allocating capital to the most profitable deals. Handicapping RMs with an inefficient process will cost you far more revenue from lost deals than you could ever gain by nailing the economic capital allocation out to four decimal places.
Sin #5: Death by Acronyms
Like all technical industries, banking is awash in strange acronyms and arcane jargon. When evaluating the RAROC, don’t forget that we are Dfast and subject to CCAR, the FDIC will have extra costs, and that overhead needs to include the new BSA/AML procedures. Add on top the fact that most large banks have around 20 borrower risk grades and a dozen facilities risk grades (typically named with more letter and number combos), and you have bankers who are spending so much time drowning in the jargon that they can no longer speak the same language as their customers.
Your borrower doesn’t care about your RAROC, or that they have been deemed a 3J on their Facility Risk. They care about the rate, the structure, and the collateral and guarantees they have to pledge. Technology now allows the decoder ring for this mess to live behind the scenes.
RMs are more effective when their options are presented in a common language (like real estate collateral) instead of your bank’s internal lingo (especially when all the banks they deal with speak a different language).
Sin #6: Ignoring the Real World
In the hypothetical world of spreadsheets, pricing is easy. Just add 75 basis points to the deal and it works!
In the real world things are obviously much different. There are competitors that have different balance sheets, different strategies, and different processes. In many of the best deals, there will be a competitive offer that is well below your bank’s comfort zone. Ignoring that reality is incredibly frustrating to RMs who are tasked with growth.
It becomes equally frustrating to the finance team when they try to incorporate competition by adding “market average” rates as benchmarks. These averages provide the RMs with no context, and instead of helping margins, act as justification for an ever lower rate. It’s an ugly prisoner’s dilemma for which the RMs are blamed.
Sin #7: Pricing in a Vacuum
Finally, many existing processes price in a vacuum, with little to no relation to the bank’s overall strategy. Most banks still have a universal hurdle rate that is set for all products, in all markets. The result is that they are low price leaders on some of the least desirable deals in slow growth markets, and overpricing the best deals in more competitive markets.
We see the highest performing banks taking the exact opposite approach, setting granular profitability targets by market, line of business, product type, industry, and risk profile. Doing so allows the bank to aggressively price the deals they want, and ensure they are very well compensated on the deals for which they have less appetite. These targets are informed by AI and deep analytics, and are actively managed to reflect evolving strategies and changes to the competitive landscape.
Time for Some Self-Appraisal
These “Seven Deadly Sins of Pricing” are costing the industry billions of dollars in lost profits, not to mention adding frustration for both bank employees and bank customers. But there is change in the air, and some of the highest performing banks have been distancing themselves from the pack by investing in user-friendly, customer-centric, scalable technologies that incorporate the latest in AI and machine learning.
Unfortunately, there are banks that still believe they can only price “where the market allows.” They are further commoditizing their own business, and trying to convince themselves that sticking with the status quo will somehow suddenly produce different results. If the top banks are, in the words of George Costanza, “Back baby!” these laggards are in danger of falling victim to a completely different Costanza quote:
“Jerry, just remember, it’s not a lie if you believe it.”