Industry Insights

February 11, 2019
Is Your Financial Institution Prepared to Meet Clients' Technology Expectations?
By Joseph Lowe, Commercial Lending Marketing Manager, Abrigo

Ultimately, all financial service institutions – large, small, community, national or alternative lenders – share one common goal: to meet customer expectations.

But it’s 2019 – customer expectations for banking have shifted toward digital platforms, and community bank leadership is on notice. According to the American Bankers Association’s (ABA) 2018 Community Bank CEO Priorities report, which surveyed 440 community banks, 71% of respondents planned to offer digital processes for small business lending last year, and 57% planned to offer digital processes for consumer lending.

Whether or not those respondents ultimately made good on their goals, it’s apparent that technology disruption is top of mind for community bank CEOs. From quicker loan decisions to streamlined credit analysis to customized workflows, financial technology offers a competitive advantage when it comes to internal banking processes. Perhaps more importantly, however, customer-facing technology is increasingly becoming an expectation among banking customers, putting pressure on banks and credit unions to quickly adopt tech solutions or risk becoming irrelevant.

According to Salesforce, 57% of consumers say it’s critical for companies to provide an easy-to-use mobile experience

Offering mobile banking in an effort to attract Millennials is a popular strategy, as 62% of consumers in this demographic do most of their banking on a phone. But it’s important to remember that Baby Boomers, Generation Xers and Generation Z are equally important to keep in mind as well, as mobile phone ownership across all generations has increased dramatically over the past seven years. For example, the Pew Research Center found that the share of Americans with a smartphone has jumped from 35% in its first survey in 2011 to 77% in 2018. Further, Pew also notes that more adults are reaching for their handheld devices for their banking needs as well, with 51% of U.S. adults banking online, and 35% of those individuals doing so from a mobile device.

Large banks caught on to this trend early, with giants like Citi, Wells Fargo and USAA offering account management, money transfer and conversational banking services from the convenience of customers’ pockets. What does this mean for community banks and credit unions? It’s time to catch up. Community financial institutions that want to level the playing field with big banks must offer an optimizable and seamless mobile experience for banking customers, whether it’s something as simple as online account summaries or offering online loan applications.

According to the ABA, 45% of loan applicants complained of long waits for a credit decision

Have you ever wondered how much the glut of business meetings or inefficient processes – such as lenders traveling to client meetings – ultimately cost your financial institution? Over $25 million is wasted per day on meetings, and $37 billion is spent on unproductive meetings each year. It’s become so much of a problem that the Harvard Business Review came up with a calculator that allows management to review how much money is wasted via unproductive meetings.

Automating timely front-end bank processes such as meetings, signatures and data entry through digital loan origination systems can be a time-saving and cost-saving endeavor for community banks, with lending automation helping to reduce loan processing time by over 50%, while also decreasing costs by up to 54%.

But according to the ABA State of Digital Lending report, financial institutions aiming to please consumers still have a lot of ground to make up. Community banks and credit unions can start by simply offering a digital loan origination process in the first place. While several banks have a functioning digital branch, only 50% of banks over $1 billion in assets and 38% of banks under $1 billion in assets offer digital loan origination in some capacity.

In the end, despite the number of customers who continue to visit physical branch locations, over 90% of mobile bank users prefer using their app over walking into nearby branches – which means that offering an easy-to-use online platform for clients will continue to be a vital component of a community institution’s success.


Disclaimer: The views and opinions expressed in this article are those of the author(s) and do not necessarily reflect the official policy or position of the Financial Managers Society.

About the Author

Joseph Lowe is the commercial lending marketing manager at Abrigo, a leading technology provider of compliance, credit risk and lending solutions for community financial institutions.


January 7, 2019
FMS Quick Poll: 2019 Priorities
By Financial Managers Society

In putting together “The War for Deposits” as the cover story for the March-April 2018 issue of FMS forward, it became clear that concerns about deposit growth for community institutions would not be subsiding any time soon. In fact, it seemed at that time that things were just beginning to really heat up on the deposit front – as competitive pressures were increasing and loan portfolios were swelling, banks and credit unions were on the hunt (in some cases, desperately on the hunt) for reliable funding sources to maintain liquidity and keep pace.

So it wasn’t terribly surprising to see deposit growth lead the pack as the most pressing goal or focus heading into 2019 for a majority of FMS members in our latest Quick Poll. What was surprising, however, was just how thoroughly deposits dominated the discussion. Among the nearly 75 respondents – 79% from members representing banks/thrifts and 22% from credit unions, with nearly two-thirds coming from institutions between $200 million and $2.49 billion in asset size – an outsized 44% tabbed deposit growth as the topic or issue that will occupy most of their focus in the year ahead.

WHAT IS THE MOST PRESSING GOAL OR FOCUS FOR YOUR INSTITUTION IN 2019?



While it’s probably safe to say that almost every institution will be keeping an eye on deposit growth in 2019 to some degree, 12% of respondents said they will be more focused on technology in 2019, with projects ranging from product upgrades to core conversions to cybersecurity initiatives. Meanwhile, 10% of respondents are going to be spending some quality time with CECL in the year ahead, as implementation deadlines inch closer and the need for quality data becomes ever more apparent. Elsewhere, smaller pockets of FMS members will be honing in on growing revenue, managing the challenge of margin compression or working through an M&A deal in 2019 (4% each).

Of course, an open-question survey such as this one also provides a great opportunity to discover some of the more individualized issues to which members will be directing their attention this year, which is how the “other” category swelled to a full 15% of responses. And even if most respondents will be focusing on the higher-charting topics noted above, it is certainly likely that at least a few of the issues from this miscellaneous collection will be on their minds in 2019 as well, including:

- Profitability management
- Compliance
- Succession planning
- Talent recruitment and retention
- IRR management

Thank you to everyone who took the time to share their thoughts in this FMS Quick Poll!





December 24, 2018
Data Needed to Comply with CECL
By Toby Lawrence, President, Lawrence Advisory Services and Owner, Platinum Risk Advisors

Having attended more than 20 different CECL seminars offered by accounting firms, software companies and industry regulators, one common question continues to come up time and time again.

What data is needed to comply with CECL?

Some of the speakers respond by listing everything except the kitchen sink to ensure they don’t leave anything out, while others state that no additional data is needed because their solution relies only on the data within an institution’s Call Report. One concern with these so-called “simple models” is that when we experience another economic slowdown, the adequacy of these models may come into question and/or may result in a small amount of losses tainting an institution’s entire portfolio – resulting in a higher provision for the allowance for loan and lease losses (ALLL) than what is actually necessary.

Many institutions likely already have the data they need to calculate CECL in their current loan subsidiary ledgers (with the possible exception of the additional information needed to calculate prepayment percentages). For the actual CECL calculation, however, you need to be thinking about the following information.

Data needed for loans that are currently outstanding
- Customer / member number
- Loan number
- Loan type
- Ability to distinguish between term loans and line of credit loans
- Date the loan was originated
- Maturity date of the loan
- Original amount of the loan
- Current interest rate
- Unpaid balance at month-end
- Additional amount that can be draw on the loan (for line of credit loans)

For CECL, you may want to use more loan types than what are currently in your loan subsidiary ledger. This will help prevent significant losses in one loan type from tainting a large portion of your loan portfolio, leading to your institution having to record a higher ALLL balance than necessary. Additionally, the more collateral types you use, the better your ability to segment the loan portfolio and truly analyze the opportunities and risks within.

Data needed to calculate prepayment percentages for term loans
- Amount of contractually due principal payments received by vintage or year of origination
- Amount of total principal payments received by vintage year

Data needed for charge-offs
- Date of the charge-off or recovery
- Loan type
- Unpaid balance of the loan at the time of charge-off
- Estimated selling costs incurred to liquidate the related collateral
- Net proceeds received from the liquidation of the collateral
- Amount of the charge-off or recovery
- Year the loan was originated
- Amount of any remaining accrued interest
- If using migration analysis, the last risk rating (commercial loans) or FICO credit score (consumer loans) and the date the loan was assigned to that risk rating / FICO credit score
- Loan officer assigned to the loan
-If using the probability of default / severity of loss method, the number of net charge-offs and number of loans originated by each loan type and vintage year (year of origination)

Additional data will be required to justify the subjective adjustments to the CECL historical charge-off percentages. To help with this, be prepared to segment your loan portfolio by:
- Collateral type
- Ranges of the loan-to-value ratio
- Ranges of the debt service coverage ratio for commercial loans and debt-to-income ratio for consumer loans
- Risk rating for commercial loans and FICO credit scores for consumer loans (assuming the institution doesn’t risk consumer rate loans)
- Separating the loans located inside and outside of the normal trade area
- Loans acquired through participation
- Loan officer responsibility codes (to determine if there are any trends in loan officers’ individually-managed portfolios)
- Delinquency status
- Spec versus presold loans for commercial construction one-to-four family loans
- Level of policy and technical exceptions
 
In order to segment a loan portfolio as noted above, lenders will need additional data for their loan subsidiary ledgers.

Data needed to justify subjective adjustments
- Collateral type (to do this correctly most lenders will need to add significantly more loan types to their loan subsidiary ledgers)
- Risk ratings for commercial loans
- FICO credit scores for consumer loans
- Cash flow generated from on-going operations (commercial loans)
- Principal and interest payments due to the institution (commercial loans)
- Principal and interest payments due to other lenders (commercial loans)
- Estimated market value of collateral pledged against the loan
- Debt-to-income ratio for consumer loans
- Number and type of policy exceptions
- Number and type of technical exceptions
- Zip code for real estate loans (this information is already in the loan subsidiary ledger)
- Whether the loan is on nonaccrual status or a TDR (this information is likely already in the loan subsidiary ledger)

The good news for most institutions is that their data processing systems are already set up to store this additional data. An interagency statement issued by the FDIC, OCC and the Federal Reserve Bank in 2006 required banks to segment their loans for major loan concentrations. This statement hasn’t been enforced well to date, but regulators will be expecting institutions to do a better job of segmenting their loan portfolios going forward. These same types of data will also be needed to properly stress test a loan portfolio.

Getting this data for the current year will take some effort and will require a data scrub of all the loans currently in the loan portfolio. However, after the initial data scrub tracking this additional data should be relatively painless. The most challenging issue with implementing CECL will be obtaining this same level of data for prior years. To ensure you have enough data for your CECL calculation it is strongly recommended that institutions implement whatever model they’re planning to use for CECL adoption as soon as possible, since at least 3 to 5 years of verifiable data will be needed to perform a proper CECL-compliant ALLL calculation.


Disclaimer: The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Financial Managers Society.

About the Author

Toby Lawrence is the president of Lawrence Advisory Services and the co-founder and owner of Platinum Risk Advisors.



December 3, 2018
Hedging to Cope with Interest Rate Uncertainty
By Ira Kawaller, Managing Director, HedgeStar

Most market observers face a conundrum. After seeing a change in prices in virtually any market, it’s difficult to discern whether said change reflects the beginning or continuation of a trend in that direction, or if the change is a temporary distortion soon to be reversed. With interest rates, however, we have a unique consideration – the Federal Reserve (the “Fed”).

The Fed has unparalleled influence in this sector, and seasoned forecasters know better than to ignore the Fed’s public statements. As of this writing, the Fed is unambiguously projecting interest rate increases. Of course, this projection rests on an expected continuation of the current economic expansion, as well as a sanguine outlook for inflation. While both of these forecasts will likely be tested at some point in the future, the Fed can be expected to signal any revision of its sensibilities if and when they were to change. Until then, however, higher interest rates seem most likely.

The more relevant question, then, is not whether interest rates will rise, but rather how high they are likely to go. Answering this question requires at least enough humility to admit that nobody knows for sure – not even the Fed. That said, interest rate futures markets offer clues as to consensus expectations for a variety of benchmark interest rates. For example, with one of the most actively traded futures contracts, three-month LIBOR is one such benchmark rate. These contracts effectively reveal where this key interest rate is expected to be at three-month intervals over the next 10 years. And while futures prices adjust with trading every day, they offer explicit, objective forecasts at any point in time.

We can also look to bond and note futures, fed funds futures and swap futures for analogous forecasts of other benchmark interest rates. Besides offering rate-specific forecasts, these various futures prices serve as the foundation for pricing a broad array of over-the-counter interest rate derivatives.

Building a Hedge
While it’s generally understood that interest rate derivatives can protect against rising or falling interest rates, the starting point for the protection derives from futures pricing curves as of the date the derivative is transacted. Thus, if a hedger wanted to use a derivative to lock in an interest rate today, the rate that would be available to that firm would be consistent with the consensus forecast. In other words, the hedger seeking to lock in rates would have to accept the consensus forecast rate as its hedging objective – regardless of whether the spot interest rate happens to be higher or lower than that consensus forecast rate at that time.

Depending on the nature of the exposure, the difference between current spot interest rates and the implied forecasted rates underlying interest rate derivatives might be adverse or beneficial. These days, for instance, with consensus forecasts anticipating rate increases, hedging with derivatives tends to impose somewhat of a cost for hedging against rate increases, while at the same time offering a benefit to entities faced with the opposite risk of falling interest rates. (If you can borrow today at 5%, but the market offers the opportunity to lock up a future funding cost of 5.5%, you’re forced to accept a 50 basis point penalty; on the other hand, if you can invest at 5% today, that same derivative would let you invest in the future at 5.5%, thereby offering a 50 basis point benefit.)

Consider the case of a commercial entity that expects to issue three-year debt in the coming four months, where the prospect of higher interest rates has stimulated interest in entering into an interest rate swap to lock in the interest rate on an intended funding. Three critical questions would have to be asked:

1. What benchmark interest rate can be secured for the three-year period starting in four months? (This question distills to getting a quote for the fixed rate on a forward starting three-year swap.)
2. What is the credit spread that the firm would likely bear, relative to this benchmark interest rate?
3. Given the expected all-in rate (i.e., the swap’s fixed rate plus the expected credit spread), what portion of the interest rate exposure that the firm is facing should be hedged?

In the current environment, this all-in interest rate should be expected to come in at a rate higher than the cost of funds that the company would bear if it were to issue debt today. This higher-than-today’s interest rate might discourage the company from hedging, but it shouldn’t preclude it. The appropriate question is how much of the exposure should be addressed with a derivative, given the fixed rate level that the derivative allows the firm to access?

Dealing with Uncertainty
Along with the implied fixed rate available with the derivative, a complementary consideration is the business judgement as to the probabilities associated with interest rates ultimately falling below, reaching or rising above the implied rates underlying the derivative. It should be clear that if the market for swaps allowed this prospective borrower to lock in an all-in cost of funds at, say 5%, while at the same time expecting rates to rise even higher, hedging would be particularly attractive. On the other hand, hedging would be less attractive if the firm didn’t expect market interest rates to rise above 5%. Extending this line of thinking further, it may be interesting to realize if the consensus forecast reflected in the pricing of the derivative were actually realized (which shouldn’t be expected), the swap wouldn’t generate any payoff whatsoever – the company would realize identical earnings regardless of whether it hedged or not.

Unfortunately, the calculus becomes more complicated because we live in a world of uncertainty. The idea of not hedging at all because we don’t expect market rates to surpass the threshold of the implied forecast of the derivative is problematic because we might be wrong. Thus, even if we might not believe the rate will move beyond that critical value, it may still be reasonable to hedge some portion of an existing exposure. Put another way, even though the market conditions force the hedging entity to lock-in an implicit rate increase dictated by the price of the swap, it’s the probability that interest rates could move even higher that would justify hedging, even at a seemingly elevated interest rate.

Employing the swap serves to eliminate the uncertainty that would otherwise prevail if the exposure were left unhedged. With the swap, the company should have a high degree of confidence that the anticipated all-in funding costs initially calculated would be realized (subject to accurately forecasting the credit spread) for the portion of the exposure that the company chooses to hedge.

Managing a Hedge
Thus far, the discussion has focused on how much to hedge at the start of the hedging process, but hedging deserves reconsideration both periodically and whenever economic circumstances change in material ways. Suppose, for example, an initial hedge was initiated to protect against a rate increase that ultimately materializes. But suppose further that with time remaining before the hedge expires, the market has evolved, and now it now seems more likely that interest rates could retreat. Does it make sense to maintain the hedge in the face of these changed circumstances? Probably not. As time passes and perceptions change as to the probabilities associated with adverse price moves, or if the company’s risk tolerances change, the degree of hedge coverage could be adjusted – either up or down. Critically, just because a derivative contract hasn’t expired doesn’t necessarily mean it’s prudent to maintain hedge coverage.

Clearly, an orientation that favors a dynamic hedge adjustment process could open the door for abuse. Consider the case of the company that starts out with a hedge of 50% of some exposure. Assume that the firm perceives the risk as being more pressing, thus adjusting its hedge coverage to 75%. Later, the company reassesses conditions and decides that the expected adverse rate move has run its course such that rates now are expected to move beneficially. With this reassessment, the firm decides to reduce its hedge coverage down to 25%.

Throughout this adjustment process, this firm could represent that it is mitigating risk, albeit at varying degrees. Still, while it might be appropriate to observe these kinds of hedge adjustments over weeks or months, an objective observer would likely have a problem with these kinds of adjustments if they were made over the course of a single trading day! The moral here is that hedge adjustments should be implemented on the basis of some previously devised plan that reflects the company’s risk management orientation and policies. Thus, a mechanical rule that imposes an objective discipline on the hedge-adjustment process is preferable to ad hoc assessments relating to adjusting hedge positions. Unfortunately, it’s not clear that any single rules-based approach will be appropriate in all circumstances.

When considering an objective hedge management plan, it’s critical to be sensitive to two opposing concerns: if you’re starting with partial hedge coverage and interest rates move adversely, it’s natural to want to increase the degree of hedge coverage; on the other hand, at some point, the prospect of interest rates achieving a top (or bottom) might gain greater currency. Prudent managers will periodically review their hedge coverage and adjust their plans accordingly, reflecting a forward-looking orientation as to the changing probabilities associated with future interest rate changes.

Disclaimer: The views and opinions expressed in this article are those of the author(s) and do not necessarily reflect the official policy or position of the Financial Managers Society.

About the Author

Ira Kawaller is a Managing Director of HedgeStar, a Minnesota-based consulting firm that specializes in derivatives strategies, valuations and hedge accounting services.


November 19, 2018
How to Determine Millennial Borrowers' Credit Worthiness
By Joseph Lowe, Marketing Manager, Sageworks

When assessing the potential risks a borrower presents an institution’s portfolio, the typical starting point for most lenders is the “five Cs of credit” – capacity, character, capital, collateral and conditions. But as a younger generation, burdened with excess debt, becomes the prime demographic for commercial and consumer loans, community banks and credit unions may want to reconsider that approach if they want to capture this increasingly important segment.

Judging by the numbers, the American economy is on an uptick. The national unemployment rate sits at its lowest rate since 2000 (3.9%), the average FICO credit score is at its highest point ever (704) and median household income is at its highest mark in over 30 years ($61,372). In addition, young borrowers’ share of the lending market is growing.

Despite these positive figures, however, the financial outlook for young borrowers is not on par with the national averages. For example, the average FICO credit score for young borrowers (ages 21-34) is 638, while the average income for Millennials is $35,592.

Given these disparities, it will be difficult for community institutions to grow revenue if they choose not to factor in metrics other than the five Cs when analyzing young borrowers. Let’s take a look at the five Cs of credit in consideration with the young borrower market.

Capacity – Young borrowers earn an average salary of $35,592 and owe an average of $25,000 in student loan debt alone, making for a poor debt-to-income (DTI) ratio.

Character – Young borrowers’ average credit score of 638 is considered fair or poor for most financial institutions that rely on credit scores as the only gauge of character.

Capital – Young borrowers are spending more on bills than previous generations, leaving less money to put toward loan payments.

Collateral – Young borrowers are postponing major purchases such as homes and cars, opting instead for renting and public transportation.

Conditions – Young borrowers are starting new businesses, which, due to their limited credit history and high debt burden, can be too risky of a loan for community banks and credit unions to offer.

In light of these realities, community financial institutions looking for a share of the up-and-coming young borrower market may consider including supplemental factors within their credit analyses and implementing technology to better evaluate credit risk.

Analyzing a young borrower’s entire relationship through global cash flow
Global cash flow refers to a lender or credit analyst’s ability to review a borrower’s financial relationships with his or her peers in the community and, more importantly, the financial institution. Rather than solely focusing on the borrower’s financial history as a key determinant of creditworthiness, financial institutions can determine how businesses, properties and family members connected to the young borrower will affect credit risk for the institution.

For example, consider a loan application from a young borrower named Jack for a $5,000 commercial loan to pay equipment costs for a moving business. When analyzing his financial statements, you see that not only does Jack make a lower-than-average income of $29,000 per year, but he also owes a total of $25,000 in student loans. Your initial reaction is to deny the line of credit. However, upon reviewing the global cash flow analysis, you realize that his student loans have a guarantor on the account – his mother, Linda. Linda earns an income of $110,000 annually and has a credit score higher than 750. She co-owns two businesses with other prominent community members and has banked with your institution for 20 years.

By considering relationships through global cash flow, you have more evidence to potentially justify the line of credit and offer the loan to Jack based on conditions that mitigate his credit risk. By using global cash flow analysis, lenders can identify opportunities, increase defensibility of loan decisioning and take informed, calculated risks.

Using technology to determine credit worthiness
In a recent article published by the Wharton School of the University of Pennsylvania, Benjamin Keys, Wharton professor of real estate, and Richard K. Green, director of the University of Southern California’s Luck Center for Real Estate, both pointed to technology as a way for banks and credit unions to pull in other factors during credit analysis to provide supplemental evidence that borrowers can repay loans.

Implementing credit analysis technology allows lenders to identify portfolio risks based on both internal factors (such as probability of default) and external factors (such as data from other financial institutions) through automated credit risk models and APIs. APIs layer on another source of bank data for lenders to include within credit analysis as well – third-party data.

An automated commercial credit risk model can determine credit worthiness using predictive financial factors and limited data entry from lenders or credit analysts. Furthermore, automated credit risk models can quickly compare probability of default with broader industry trends and examine the industry’s risk to the institution. For young adults with limited access to capital, a better understanding of industry trends can provide another factor to be taken into account when examining credit.

As the demographics of community financial institutions’ customers shift to younger borrowers with less credit history and higher DTI than previous generations, it’s important for banks and credit unions to focus on more ways to help them find good risks that represent profitable growth from a core of young borrowers.


Disclaimer: The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Financial Managers Society.

About the Author

As a commercial lending marketing manager at Sageworks, Joseph Lowe helps educate bankers on ways to optimize their lending and credit risk processes.



October 22, 2018
Hedge Accounting: A Q&A with Dan Morrilll and Ryan Henley


As the FASB’s hedge accounting standard continues its march to implementation – and with early adoption permitted – many companies may be wondering exactly how the changes will impact their operations. To get a better handle on life under the new rules, FMS checked in with Dan Morrill of Wolf & Company and Ryan Henley of Stifel for a quick summary of the changes to be aware of and the opportunities that may emerge for financial institutions.

Q: Which institutions would you expect to see the greatest impact from the hedge accounting changes?
A: While the accounting changes improved upon hedge relationships of several types, predominantly the rule changes allow for much greater flexibility in hedging fixed-rate instruments (converting fixed-rate assets or liabilities to floating), otherwise known as a fair value hedge. Given the current rate environment, institutions that would benefit most are those that have a risk to shrinking net interest margins in a continued rising rate environment as funding costs increase and fixed-rate asset yields remain constant.

Q: What are some of the new opportunities that have emerged as a result of these changes?
A: There are two primary strategies currently employed as a result of the changes. First, institutions are hedging assets that typically are offered in the market in a generic fixed-rate form. Fixed-rate loans or bonds of a longer maturity can now be converted to floating-rate asset classes by entering into an interest rate swap utilizing the new hedging rules. Secondly, institutions can create funding strategies paired with these same hedging alternatives to arrive at a cheaper funding profile for a given interest rate risk position.

Q: For those institutions that were hedging under the old rules, how significant will these changes be?
A: FASB’s effort significantly simplifies the accounting results (in constructing, measuring and monitoring) of hedge relationships. For institutions with legacy hedge relationships, this would apply to both future hedging strategies they would employ, as well as the opportunity to amend existing hedging relationships upon adoption. It will simply lead to a cleaner hedging platform for the institution going forward.

Q: Which change in particular do you see as having the most impact on the operations of banks and credit unions?
A: The ability to now hedge fixed-rate assets (swap fixed-rate instruments to float) gives an institution a tremendous amount of flexibility in product offerings to its client base. If the institution’s core market desires a longer-term fixed-rate product (in the consumer or commercial space), management can originate into this demand and then subsequently adjust the interest rate risk of the product without client involvement and in a clean accounting manner.

Q: Are there any effects of these changes that might be seen as a negative?
A: Generally speaking, most accounting changes carry with them a set of considerations or consequences that are not always favorable. Importantly, ASU 2017-12 was an attempt to rectify previous issues within hedge accounting. As a result, the rule really only improves upon the legacy framework. In our opinion, there are no negative consequences, as it affords greater flexibility than before.

Q: What should institutions be doing to prepare for these changes, or to make sure they’re in the best possible position to take advantage of them?
A: It is important to note that a significant number of institutions are currently early adopting the standard to take advantage of these rules. Why is this so important? Because it is likely that a competitor will be employing the strategies mentioned above due to the added flexibility. There are considerations upon adoption that must be analyzed, such as whether the institution has any legacy hedge relationships. If so, should these relationships be amended upon adoption (leaning on the transition provisions of the rule), and does the institution have investment securities classified as held-to-maturity that are eligible to be transferred to available-for-sale as permitted by the standard? If so, does it make economic sense to do so for each eligible instrument? These are some of the questions to be asking now.


Disclaimer: The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Financial Managers Society.

About the Authors

Ryan Henley is a Managing Director and the Head of Depository Strategies at Stifel. In this position, he provides ongoing analysis and balance sheet strategies to financial institutions and portfolio managers nationwide, as well as a broad variety of analysis related to economics, interest rates, investments and interest rate risk management strategies.

Dan Morrill is a Principal at Wolf & Co. and is responsible for the firm’s Professional Practice group. In addition to leading the Audit and Accounting Committee, Dan conducts training on technical issues, performs quality control reviews, participates in learning and development initiatives and conducts technical research.



October 15, 2018
Strategic Uses for Customer Profitability
By Brad Dahlman, Sr. Product and Consulting Services Manager, ProfitStars

As accounting/finance professionals, we spend the majority of our time focused on delivering accurate financial reporting, but less time determining how the information will be used by the business units tasked with driving the institution’s success.

As a result, accounting/finance managers often want to have deep conversations about Funds Transfer Pricing (FTP) methodologies or the benefits of full absorption costing rules. While having good business rules is key to providing accurate results, it is equally important to focus on how front-line employees should be using customer profitability data to effectively drive business decisions..

Identification and Protection of Key Clients
In the more than 100 customer profitability installations I have overseen, it has been universally true that over 180% of a financial institution’s profitability comes from the top 20% of clients. This dramatic concentration of profit among relatively few clients demonstrates the importance of identifying these key clients and putting in place strategies to ensure they never leave your institution. While most well-run institutions have a good idea of who many of their top clients are, there are always some surprises – especially with deposit/service clients that don’t go through credit underwriting processes.

In Figure 1, a well-performing $800-million bank shows average profitability for each client in the top 10% as $4,623 annually. Losing any of these clients will certainly hurt, so the organization must:

1. Identify them
2. Assign relationship officers to these key accounts
3. Put in place programs or rewards to ensure the client is satisfied, including providing key profit information to tellers and personal bankers so they can properly address fee waiver requests
4. Track lost “key” clients


Figure 1: Profit Is Highly Concentrated



Effectively Pricing New Transactions
The second use for customer profitability data is in pricing new transactions. As new business requests (loan or deposit) are considered, institutions with a customer profitability system should:

1. Understand current profitability (i.e. “before”)
2. Price the new transaction, considering various pricing scenarios and terms
3. Assess the “after” – or post-approval profitability – to ensure an adequate return (profit/ROE)
4. Provide only those options to the client that meet targeted profitability thresholds

Segmentation and Marketing Strategies
The third major use for customer profitability data is by the marketing department. Accurate customer profitability data is often loaded into CRM/MCIF systems, as opposed to using rudimentary CRM/MCIF tools to determine profitability. With this accurate data imported into the application, the data is then used to segment clients and develop marketing campaigns targeted around both product usage and profitability data.

While many CRM/MCIF systems have basic profitability analysis included, it is essential to have one consistent view of profitability for use by finance/business leaders, tellers or other front-line personnel, as well as marketing. As such, data from a sophisticated profitability system should ideally be fed into the CRM/MCIF system.

Evaluation of Relationship Managers’ Performance
The fourth major use for customer profitability data is evaluation of relationship managers’ performance. The concept here is to determine the value of a relationship manager’s portfolio at the beginning and end of the year to assess profit improvement.

In most institutions today, relationship manager goals often revolve around production goals like growing loans and/or deposits. While growth is indeed a positive measure, we also want to make sure these goals align with profitability goals. Without profitability targets, relationship managers will be incentivized to simply “price down” transactions to win business that could negatively affect the institution’s overall financial performance. In other words, not all deals are profitable!

When a relationship manager has profitability growth goals, he or she is encouraged to find ways to make transactions profitable. Access to customer profitability data and effective pricing tools are key elements in this process.

Summary
Customer profitability systems have been available in the market for many years. However, the number of financial institutions that have accurate, sophisticated customer profitability systems and use them in the manners described above are few.

In my experience, community bank clients who actively use their customer profitability systems have experienced between 8-10 basis points of additional profitability over their peers. As your institution considers future growth and profit objectives, it is therefore worth asking this basic question: “Do we provide our front-line staff with the information to effectively engage with clients to grow profitability?”

If the answer to this question is “no,” perhaps 2019 should be the year your organization explores customer profitability and pricing solutions.

Disclaimer: The views and opinions expressed in this article are those of the author(s) and do not necessarily reflect the official policy or position of the Financial Managers Society.

About the Author

Brad Dahlman is a Senior Product and Consulting Services Manager for ProfitStars focusing on the importance and uses for relationship profitability. In addition to developing a customer profitability system in the late 1990s, Brad has personally led the installation of customer profitability solutions at over 100 financial institutions over the past two decades. He has a broad background in banking and has held various positions in finance, audit, operations and technology with several mid-sized community banks.





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