Chapter 2: Price Setting

Chapter 2: Price Setting

Following the financial crisis of 2008-09 and the subsequent deep recession, a multi-billion dollar bank in the Midwest was at an important crossroads. The bank had in essence been born during the crisis, as a large investor arranged several shotgun weddings of smaller banks that were either failing or simply run by management teams that didn’t feel equipped to deal with the changes facing the industry.

The resulting bank in some ways resembled Frankenstein’s monster, as the various pieces didn’t seem to fit together exactly right. In fact, for this story we’ll call it Frankenstein Bank. There was a core piece that was a traditional community bank, with high concentrations in commercial real estate, but there were also smaller offices spread all over the country, with lending focuses in areas such as energy, entertainment, and gaming. They all had different management teams, and each had its own culture that dictated everything from credit standards to pricing practices. The new leadership at Frankenstein Bank had their work cut out for them, to say the least.

After putting the basic underwriting process in place, the bank’s management team shifted its attention to pricing. Like a lot of banks, they turned to trusty old Microsoft Excel, and went about expanding on a risk-adjusted return on capital (RAROC) model from one of the precursor banks to price loans.

The finance folks did their homework and covered all the bases. They built a bank-specific funding curve with a built-in liquidity premium. They debated on which interpolation method was best. They did extensive studies of overhead costs, and they built credit migration assumptions. They even started a massive project that would enable them to use stochastic modeling to allocate economic capital for individual loans based on their specific credit profile.

However, despite the thousands of dollars and hundreds of hours spent on pricing over a three-year period, Frankenstein Bank’s results were lagging far behind those of its peers. Specifically, despite growing the loan portfolio at an impressive clip and improving the loan/deposit ratio, the bank’s net interest margins were shrinking. And not just by a little. As the chart below shows, net interest margins declined by more than 100 basis points. For a bank that size, that’s about $70 million per year worth of margin.

frankensteinNIM

So, why didn’t these efforts translate to results? After all, Frankenstein Bank clearly realized the importance of pricing, and was willing to spend the time and money necessary to improve in this area. Why were the prices they had spent immense effort to calculate so precisely not the ones that were actually landing on their books? And why weren’t they building valuable relationships with their customers that would translate to premium pricing?

The bank was coming to realize what many before had found; you can’t simply “out-math” the competition. No matter how good you are at Price Setting, to price effectively you have to be equally good at Price Getting.

Don't let perfect be the enemy of good."

Pricing is a forward-looking, prospective exercise, and as such, it can get messy.

The Two Dimensions of Pricing

Pricing is hard. This is one of those universal truths that applies to every business, and it is certainly true in banking. The difficulty lies in the fact that pricing is inherently cross-functional. You need inputs from lots of different sources, both internal and external, and you have to please numerous stakeholders that all have different perspectives and end goals. And in banking there is the added complexity that you are pricing financial instruments, which adds degrees of both math and risk that aren’t found in most industries.

PriceSetting_vs_PriceGetting_performanceEvery bank in the world struggles with pricing, and just when they start to get comfortable with it, there is a fundamental shift in either their own bank or in the market at large, and they have to start over.

But why is this? Why is pricing, which is the essence of the banking business, such a struggle for so many?

To answer that big question, let’s start with the research of Stephan Liozu, author of The Pricing Journey. Liozu describes two dimensions of pricing capability, Price Setting and Price Getting, and shows that in order to excel at pricing, companies must master both dimensions.

We’ll tackle Price Setting in this chapter and then turn our attention to Price Getting in Chapter 3. Brace yourself, because right now we’re going to go into full bank-nerd mode.

Why Bankers Prefer Price Setting

Price Setting is the one that gets all of the attention in the banking business. Why? Because it’s math. Most bankers pride themselves on analytics, and on being able to quantify a deal in a neat and tidy box.

Even though Price Setting is the dimension that gets the most attention, that doesn’t mean all banks are good at it. We have all seen plenty of evidence to the contrary in the marketplace. Still, given the comfort level with the concepts and the fact that progress should be quantifiable, bankers almost universally choose fixing this dimension as the way to correct their pricing woes. This approach makes sense, as Price Setting is the foundation for everything else.

Although the range of Price Setting skill in banks is very wide, there are a few common stumbling blocks. But, before we jump into these, there is a conceptual framework that we need to establish first.

As much as it pains bankers, when it comes to Price Setting, they need to live by the old saying, “Don’t let perfect be the enemy of good.” Pricing is a forward-looking, prospective exercise, and as such, it can get messy.

There is no such thing as 100% accuracy, and bankers (especially the finance types) get uncomfortable with the uncertainty. They know the importance of pricing, so there is an urge to get the assumptions just right. And many, like Frankenstein Bank, will spend years trying to get everything perfected. In the meantime, they are pricing millions of dollars in loans with an old tool that they know is flawed.

Instead, banks should use the “continuous deployment,” mentality whereby they can roll out the improved methodology (After all, it is better than what you have!) and then slowly refine it over time. All of this should happen with the understanding that perfection is not the goal. There will come a point when gaining the extra degree of accuracy is not worth the time, resources, or interference with end users needed to achieve it.

Finding the Right Funding Costs 

With that said, there are a few common Price Setting issues that we see banks struggling with on a regular basis. First is the fundamental question of what to use for funding costs. There are still a number of banks that insist they should be pricing off their internal cost of funds. Their thinking: “Don’t we want to know the true profitability of this loan we are about to book?”

From an accounting perspective, yes, we will want to measure true profits. However, balancing back to the GAAP financial statements is not the goal of pricing, nor is it making the ideal accounting decision. The goal is to make the best economic decision. If you have ever spent time in the inner workings of bank financial statements, you know that accounting and economic decisions are often at odds with each other. You already spend plenty of money on balancing the debits and credits and reporting on how much money you made yesterday. This is about making optimal decisions to make more money tomorrow, and the inputs should be different.

At first blush, pricing off an internal funding cost seems very logical. But it almost always results in underpricing loans in a rising rate environment and overpricing loans in a declining rate environment. This occurs because an internal funding cost is a historical number and includes deposits with varying maturities. As a result, an internal funding cost moves much more slowly than an incremental funding cost, and will lag the true market rates where assets are being booked.

In addition to having a funding cost that reflects a historic cost versus a current funding cost, there is also the question of what premium should be charged for pricing out on the funding curve. In other words, how much more should you charge a borrower to lock in a rate for five years compared to three years? How much does your pricing change for a floating rate loan?

The better answer is to use a market-based curve that represents a realistic marginal funding source for you. Although you can’t fund your bank exclusively with FHLB advances, you can buy money at exactly the rate posted. Further, these rates change daily and move with general market rates. Most community banks use FHLB, and then as banks get larger they tend to use the LIBOR swap curve as the basis for funding costs.

You can certainly adjust the curve as needed to reflect things like your liquidity premium or your own exposure to rate movements, but the important takeaway is that the funding curve moves with market rates, and is not skewed by your own accounting of historical decisions.

What to Do With Overhead Costs

The next big stumbling block is overhead costs. The indecision here usually stems from having to choose between using fully absorbed overhead for the loan department versus just using the incremental cost to originate and service an individual loan.

A simple question should help here. Do your borrowers care if you have high overhead? Are they willing to pay more just because you have an expensive branch network, or spend more than your peers on health insurance? Of course not! You don’t want to avoid making a loan because you have high overhead; if anything, you want to make more loans to help carry that burden.

Instead, you should be measuring the marginal cost to get the loan on the books. The goal is to find the optimal place to invest available funds, and not to tie back to accounting results.

Measuring Credit Risk and Allocating Capital

The final stumbling block is one that is admittedly not as simple to solve. How do we measure credit risk and allocate capital?

The perception of capital in the banking industry has changed dramatically over the last several years. Banks were almost always viewed (at least internally) as having excess capital. While perhaps this was true, the biggest mistake that resulted from this belief was a drive for growth without a corresponding pricing differentiation based on quality.

Regardless of the cause, the important thing is to arm lenders to compete aggressively for the best quality loans, and to be well compensated for all other borrowers. Due to the new Basel standards, capital is now the bottleneck for growth, and as a precious resource, it needs to be allocated in the most efficient and profitable way possible. More risk in a deal should translate to more capital, and therefore more revenue to justify making that loan.

Yet for most banks, there is little difference in how they price a strong credit and a weak credit. If all borrowers are priced close to average, then we are overcharging the best borrowers and undercharging the worst. Is this really the strategy we want to pursue, aggressively chasing the borrowers who are the least desirable?

The differentiation of pricing based on quality is in flux in the industry, as there is a slow transformation occurring from the single-factor approach to the multi-factor approach. In the single-factor approach, the loan loss reserve and credit capital are based on the risk rating for the loan. The risk rating for the loan includes all the underwriting criteria, such as exposure at default, risk of default, collateral and guarantors. In other words, after considering each of these items, the lender comes up with one number that represents the credit risk of the loan.

The multi-factor approach seeks to be more precise about the actual risk of the loan, the probability of the default, and the anticipated loss in the event of default. As such, the risk of the borrower, the type and value of collateral, and the type and amount of the guarantees are all inputted separately instead of being combined into one risk factor.

The risk of the borrower tells us the probability of default (PD). From there, we use the facility details (exposure at default, collateral, and guarantees) to determine a loss given default (LGD).

The big takeaway, though, is that we again do not need to be 100% accurate. In fact, that is impossible when pricing a prospective transaction in which we have to make so many guesses about what will happen in the future.

The goal is to be directionally correct, giving our lenders the ability to price more aggressively to win the very best deals and making sure we are adequately compensated for the risk and uncertainty in all of the other deals. Point yourself in the right direction with an approach and a tool that are better than what you have, and then refine it over time.

 

 

As you can see from the few issues we covered here, the Price Setting isn’t easy. The concepts might make sense, but there will still be internal disagreements based on the differing perspectives. The finance team has different incentives than the credit team, and both will often be at odds with the loan team. And, once the concepts are settled, the execution can be tricky. We didn’t even cover some of the heavier math involved in deciding between using regulatory capital versus economic capital, or how to treat caps and floors, or what to do with prepayment penalties.

The good news is that there are industry standards and lots of resources available to fix Price Setting, so you should be able to continue making incremental progress forward.

The bad news? Without mastering the second dimension, Price Getting, all of that Price Setting work is for naught.

Last Chapter

Chapter 1: Why is Pricing So Important?

The key to creating stronger customer relationships with customer is pricing. But why? Just how much can improvements in pricing impact your bank? Where can those improvements be found? And what does it look like when you start to move the ball forward on pricing?

Next Chapter

Chapter 3: Price Getting

How good are banks at actually booking that price after they set it? In other words, how good are they at Price Getting? And how can banks get better at Price Getting in a way that builds relationships and positively affects their brands?

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