Net Interest Margin

-- by Dan Buell

Towards the end of 2007, the management of Bay Area Credit Service embarked on an agressive strategy to dramatically enhance the company's market position and increase its collection revenues.  These goals could be achieved only through superior performance at competitive rates.  At the same time, though, the company needed to drastically reduce internal operating expenses while facing significant competition.  The company's major goals for 208 included:

*  Earn a much larger share of business from one of the nation's top five cellular phone service providers;

*  Become a major collections partner for one of the nation's largest banking institutions;

*  Earn more than 50 percent of the market in the pre-charge-off, early-out segment for the nation's largest landline communications provider;

*  Enhance the company's position in the secondary collections tier.

It's an interesting case study.  Navigate to the link to learn more: 

http://www.experian.com/whitepapers/index.html

--by Kari Michel

Most lenders use a credit scoring model in their decision process for opening new accounts; however, between 35 and 50 million adults in the US may be considered unscoreable with traditional credit scoring models. That is equivalent to 18-to-25 percent of the adult population. 

Due to recent market conditions and shrinking qualified candidates lenders have placed a renewed interest in assessing the risk of this under served population.  Unscoreable consumers could be a pocket of missed opportunity for many lenders. To assess these consumers, lenders must have the ability to better distinguish between consumers with a clear track record of unfavorable credit behaviors versus those that are just beginning to develop their credit history and credit risk models.

Unscoreable consumers can be split out into three populations:

• Infrequent credit users:  Consumers who have not been active on their accounts for the past six months, and who prefer to use non-traditional credit tools for their financial needs.

• New entrants:  Consumers who do not have at least one account with more than six months of activity; including young adults just entering the workforce,  recently divorced or widowed individuals with little or no credit history in their name, newly arrived immigrants, or people who avoid the traditional system by choice.

• Thin file consumers:  Consumers who have less than three accounts and rarely utilize traditional credit and likely prefer using alternative credit tools and credit score trends.

A study done by VantageScore® Solutions, LLC shows that a large percentage of the
unscoreable population can be scored with VantageScore* and a portion of these are credit-worthy (defined as the population of consumers who have a cumulative likelihood to become 90 days or more delinquent is less than 5 percent).  The following is a high-level summary of the findings for consumers who had at least one trade:

Lenders can review their credit decisioning process to determine if they have the tools in place to assess the risk of those unscoreable consumers.  As with this population there is an opportunity for portfolio expansion as demonstrated by the VantageScore study.

*VantageScore is a generic credit scoring model introduced to meet the market demands for a highly predictive consumer score. Developed as a joint venture among the three major credit reporting companies (CRCs) – Equifax, Experian and TransUnion.

-- By Kelly Kent

Source: Experian-Oliver Wyman Market Intelligence Reports

Analyzing recent trends from vintages published in the Experian-Oliver Wyman Market Intelligence Reports, there are numerous insights that can be gleaned from just a cursory review of the results.

Mortgage Trends

As noted in an earlier posting, recent mortgage vintages show a broad range of behaviors between more recent vintages and older, more established vintages that were originated before the significant run-up of housing prices seen in the middle of the decade. As below, the 30+ delinquency levels for mortgage vintages in 2005, 2006, and 2007 approach and in two cases exceed 10% of trades in the last 12 months of performance, and have spiked from historical trends, beginning almost immediately after origination. On the other end of the spectrum, the vintages from 2003 and 2002 have barely approached or exceeded 5% for the last 6 or 7 years.

Bankcard Trends

As one would expect, the 30+ delinquency trends demonstrated within bankcard vintages are vastly different from the trends of mortgage vintages. Firstly, card delinquencies show a clear seasonal trend, with a more consistent yearly pattern evident in all vintages, resulting from the revolving structure of the product. The most interesting trends within the card vintages do show that the more recent vintages, 2005 to 2008, display higher 30+ delinquency levels, especially the Q2 2007 vintage, which is far and away the underperformer of the group.Within Within each vintage pool, an analysis can extend into the risk distribution and details of the portfolio and further segment the pool by credit score, specifically VantageScore. In the chart below, an alarming trend is evident. This chart provides the 30+ delinquency levels for the subset of VantageScore A and VantageScore B consumers at the time of origination. In other words, the loans in this pool are only for the most creditworthy customers at the time of origination. The noticeable trend is that while these consumers were largely resistant to deteriorating economic conditions, each vintage segment has seen a spike in the most recent 9-12 months. Given that these consumers tend to have the highest limits and lowest utilization of any Vantage Score band, this trend encourages further account management consideration and raises flags about overall bankcard performance in coming months.

As shown, even a basic review of vintage pools and the subsequent analysis opportunities that result from this data can be extremely useful. This analysis can add a new perspective to risk management, supplementing more established analysis techniques, and further enhancing the ability to see the risk within the risk.

--by Mike Sutton

I recently interviewed a number of Experian clients to determine how they believe their organizations and industry peers will prioritize collections process improvement over the next 24 months. Additional contributions were collected by written surveys. Here are several interesting observations:

All of the categories mentioned above were considered important by every respondent, but the most urgent priorities were not consistent across industries.

-- By Kelly Kent

Vintage analysis, specifically vintage pools, present numerous useful opportunities for any firm seeking to further understand the risks within specific portfolios. While most lenders have relatively strong reporting and metrics at hand  for their own loan portfolio monitoring...these to understand the specific performance characteristics of their own portfolios -- the ability to observe trends and benchmark against similar industry characteristics can enhance their insights significantly.

Assuming that a lender possesses the vintage data and vintage analysis capability necessary to perform benchmarking on its portfolio, the next step is defining the specific metrics upon which any comparisons will be made. As mentioned in a previous posting, three aspects of vintage performance are often used to define these points of comparison:

1. Vintage delinquency including charge-off curves, which allows for an understanding of the repayment trends within each pool. Specifically, standard delinquency measures (such as 30+ Days Past Due (DPD), 60+ DPD, 90+ DPD, and charge-off rates) provide measures of early and late stage delinquencies in each pool.

2. Payoff trends, which reflect the pace at which pools are being repaid. While planning for losses through delinquency benchmarking is a critical aspect of this process, so, too, is the ability to understand pre-repayment tendencies and trends. Pre-payment can significantly impact cash-flow modeling and can add insight to interest income estimates and loan duration calculations.

As part of the Experian-Oliver Wyman Market Intelligence Reports, these metrics are delivered each quarter, and provide a consistent, static pool base upon which vintage benchmarks can be conducted.

Clearly, this is a rather simplified perspective on what can be a very detailed analysis exercise. A properly conducted vintage analysis needs to consider aspects such as: lender portfolio mix at origination; lender portfolio footprint at origination; lender payoff trends and differences from benchmarked industry data in order to properly balance the benchmarked data against the lender portfolio.
 

-- By Ken Pruett

I find it interesting that the media still focuses all of their attention on identity theft when it comes to credit-related fraud.  Don’t get me wrong.  This is still a serious problem and is certainly not going away any time soon.  But, there are other types of financial fraud that are costing all of us money, indirectly, in the long run.  I thought it would be worth mentioning some of these today. 

Although third party fraud, (which involves someone victimizing a consumer), gets most of the attention, first party fraud (perpetrated by the actual consumer) can be even more costly.  “Never pay” and “bust out” are two fraud scenarios that seem to be on the rise and warrant attention when developing a fraud prevention program. 

Never Pay   
A growing fraud problem that occurs during the acquisition stage of the customer life cycle is “never pay”.  This is also classified as first payment default fraud.  Another term we often hear to describe this type of perpetrator is “straight roller”. 

This type of fraudster is best described as someone who signs up for a product or service -- and never makes a payment.

This fraud problem occurs when a consumer makes an application for a loan or credit card. The consumer provides true identification information but changes one or two elements (such as the address or social security number).  He does this so that he can claim later that he did not apply for the credit.  When he’s granted credit, he often makes purchases close to the limit provided on the account.  (Why get the 32 inch flat screen TV when the 60 inch is on the next store shelf -- when you know you are not going to pay for it anyway?) 

These fraudsters never make any payments at all on these accounts. The accounts usually end up in collections. 

Because standard credit risk scores look at long term credit, they often are not effective in predicting this type of fraud.  The best approach is to use a fraud model specifically targeted for this issue. 

Bust Out Fraud
Of all the fraud scenarios, bust out fraud is one of the most talked about topics when we meet with credit card companies.  This type of fraud occurs during the account management phase of the customer lifecycle.  It is characterized by a person obtaining credit, typically a loan or credit card, and maintaining a good credit history with the account holder for a reasonable period of time.  Just prior to the bust out point, the fraudster will pay off the majority of the balance, often by using a bad check.  She will then run the card up close to the limit again -- and then disappear. 

Losses for this type of fraud are higher than average credit card losses.  Losses between 150 to 200 percent of the credit limit are typical.  We’ve seen this pattern at numerous credit card institutions across many of their accounts. 

This is a very difficult type of fraud to prevent. At the time of application, the customer typically looks good from a credit and fraud standpoint.  Many companies have some account management tools in place to help prevent this type of fraud, but their systems only have a view into the one account tied to the customer.  A best practice for preventing this type of fraud is to use tools that look at all the accounts tied to the consumer -- along with other metrics such as recent inquiries.  When taking all of these factors into consideration, one can better predict this growing fraud type.   

There are a lot of areas covered in your comment: efficiency; credit quality (human side or character in an impersonal environment); and policy adherence. 

We define efficiency and effectiveness using these metrics:

• Turnaround time from application submission to decision;
• Resulting delinquencies based upon type of underwriting (centralized vs. decentralized);
• Production levels between centralized and decentralized;
• Performance of the portfolio based upon type of underwriting; and
• Turnaround time from application submission to decision

Due to the nature of Experian’s technology, we are able to capture start and stop times of the typical activities related to loan origination.  After analyzing the data from 160+ financial institutions of all sizes, Experian publishes an annual small business benchmark report that documents loan origination process efficiencies and inefficiencies, benchmarking these as industry standards.  

Turnaround Time

From the benchmark report, we’ve seen that institutions that are centralized have consistently had a turnaround time that is half of those with decentralized environments.

Interestingly, turnaround time is also much faster for the larger institutions than for smaller.  This is confusing because the smaller community banks tend to promote the close relationship they have with their clients and their communities. Yet, when it comes to actually making a loan decision, it tends to take longer.

In addition to speed, another aspect of turnaround is consistency.  We all can think of situations where we were able to beat the stated turnaround times of the larger or the centralized institutions.  Unfortunately, these tend to be isolated instances versus the consistent performance that is delivered in the centralized environment.

Resulting delinquencies based upon type of underwriting/Performance of the portfolio based upon type of underwriting

Again, referring to the annual small business lending benchmark report, delinquencies in a centralized environment are 50% of those in a decentralized environment. 

I have worked with a number of institutions that allow the loan officer/relationship manager to “reverse the decision” made by a centralized underwriting group.  The thinking is that the human aspect is otherwise missing in centralized underwriting.  When the data is collected, though, the incremental business/portfolio that is approved by the loan officer (who is close to the client and knows the human side) is not profitable from a credit quality perspective.  Specifically, this incremental portfolio typically has a net charge-off rate that exceeds the net interest margin -- and this is before we even consider the non-interest expense incurred. 

Your choice: is the incremental business critical to your success…or could you more fruitfully direct your relationship officer’s attention elsewhere?

Production levels between centralized and decentralized

Not to beat a dead horse, but the multiple of two comes into play here too.  As one looks at the throughput of each role (data entry, underwriter, relationship manager/lender), the production levels of a centralized environment are typically double that of a decentralized.

It’s clear that the data point to the efficiency and effectiveness of a centralized environment

Some articles that I’ve come across recently have puzzled me.

In those articles, authors use the terms “monetary base” and “money supply” synonymously -- but those terms are actually very different.

The monetary base (currency plus Fed deposits) is a much smaller number than the money supply (M1). The huge change in the “base”, which the Fed did affect by adding $1T or so to infuse a lot of quick liquidity into the financial system late in 2007/early 2008, does not necessarily impact M1 (which includes the base plus all bank demand deposits) all that much in the short-term, and may impact it even less in the intermediate-term if the Fed reduces its holdings of securities.  Some are correct, of course, in positing that a rotation out of securities by the Fed will tend to put pressure on market rates.

Some are equivocating the 2007 liquidity moves of the Fed, with a major monetary policy change. When the capital markets froze due to liquidity and credit risks in August/September of 2007, monetary policy was not the immediate risk, or even a consideration. Without the liquidity injections in that timeframe, monetary policy would have become less than an academic consideration.

Tying the “constrained” (which actually was a slowdown in growth of) bank lending to bank reserves on account at the Fed I don’t think their Fed reserve balance was ever an issue for lending. Banks slowed down lending because the level of credit risk increased. Borrowers were defaulting. Bank deposit balances were actually increasing through the financial crisis. [See my Feb 26 and March 5 blogs] So, loan funding, at least from deposit sources was not the problem for most banks. Of course, for a small number of banks that had major securities losses, capital was being lost and therefore not available to back increased lending. But demand deposit balances were growing.

Some authors are linking bank reserves to the ability of banks to raise liabilities, which makes little sense. Banks’ respective abilities to gather demand deposits (insured by the FDIC, at no small expense to the banks) was always wide open, and their ability to borrow funds is much more a function of asset quality (or net asset value) more than it relates their relatively small reserve balances at the Fed.

These actions may result in high inflation levels and high interest rates -- but it will be because of poor Fed decisions in the future, not because of the Fed’s action of last year. It will also depend on whether the fiscal (deficit) actions of the government are: 1) economically productive and 2) tempered to a recovery, or not. I think that is a bigger macro-economic risk than Fed monetary policy.

In fact, the only way bank executives can wisely manage the entity over an extended timeframe is to be able to direct resources across all possibilities on a risk-adjusted basis. The question isn’t whether risk-based pricing is appropriate for all lines of business, but rather how might or should it be applied.

For commercial lending into the middle and corporate markets, there is enough money at stake to warrant evaluating each loan and deposit, as well as the status of the client relationship, on an individual basis. This means some form of simulation modeling by relationship managers on new sales opportunities (including renewals) and the model’s ready access to current data on all existing pieces of business with each relationship. [See my April 24 blog entry.]

This process also implies the ability to easily aggregate the risk-return status of a group of related clients and to show lenders how their portfolio of accounts is performing on a risk-adjusted basis. This type of model-based analysis needs to be flexible enough to handle differing loan structures, easy for a lender to use and quick. The better models can perform such analysis in minutes. I’ve discussed the elements of such models in earlier posts.

But, with small business and consumer lending there are other considerations that come into play. The principles of risk-based pricing are consistent across any loan or deposit. With small business lending, the process of selling, negotiating, underwriting and origination is significantly more streamlined and under some form of workflow control.

With consumer lending, there are more regulations to take into account and there are mass marketing considerations driving the “sales” process.

Agreement covers what the new owner wants now and may decide it wants in the future. This a form of strategic business risk that comes with accepting the capital infusion from this particular source.
 

-- By Kari Michel

What is your credit risk score?  Is it 300, 700, 900 or something in between?  In order to understand what it means, you need to know which score you are referencing.  Lenders use many different scoring models to determine who qualifies for a loan and at what interest rate. For example, Experian has developed many scores, such as VantageScore®..  Think of VantageScore® as just one of many credit scores available in the marketplace.

While all credit risk models have the same purpose, to use credit information to assess risk, each credit model is unique in that each one has its own proprietary formula that combines and calculates various credit information from your credit report.  Even if lenders used the same credit risk score, the interpretation of risk depends on the lender, and their lending policies and criteria may vary.

Additionally, each credit risk model has its own score range as well.  While the score range may be relatively similar to another score range, the meaning of the score may not necessarily be the same.   For example, a 640 in one score may not mean the same thing or have the same credit risk as a 640 for another score.  It is also possible for two different scores to represent the same level of risk. If you have a good credit score with one lender, you will likely have a good score with other lenders, even if the number is different.
 

As I'm preparing for traveling to the Baker Hill Solution Summit next week, I thought I would revisit the ideas of risk-based loan pricing.

Risk Adjusted Loan Pricing – The Major Parts 

I have referred to risk-adjusted commercial loan pricing (or the lack of it) in previous posts. At times, I’ve commented on aspects of risk-based pricing and risk-based bank performance measurement,  but I haven’t discussed what risk-based pricing is -- in a comprehensive manner. Perhaps, I can begin to do that now, and in my next posts.

Risk-based pricing analysis is a product-level microcosm of risk-based bank performance. You begin by looking at the financial implications of a product sale from a cost accounting perspective. This means calculating the revenues associated with a loan, including the interest income and any fee-based income. These revenues need to be spread over the life of the loan, while taking into account the amortization characteristics of the balance (or average usage for a line of credit). To save effort (and in providing good client relationship management), we often download the balance and rate information for existing loans from a bank’s loan accounting system.

To “risk-adjust” the interest income, you need to apply a cost of funds that has the same implied market risk characteristics as the loan balance. This is not like the bank’s actual cost of funds for several reasons. Most importantly, there is usually no automatic risk-based matching between the manner in which the bank makes loans and the term characteristics of its deposits and/or borrowing. Once we establish a cost of funds approach that removes interest rate risk from the loan, we subtract the risk-adjusted interest expense from the revenues to arrive at risk-adjusted net interest income, or our risk-adjusted gross margin.

We then subtract two types of costs. One cost includes the administrative or overhead expenses associated with the product. Our best practice is to derive an approach to operating expense breakdowns that takes into account all of the bank’s non-interest expenses. This is a “full absorption” method of cost accounting. We want to know the marginal cost of doing business, but if we just apply the marginal cost to all loans, a large portion of real-life expenses won’t be covered by resulting pricing. As a result, the bank’s profits may suffer.

We fully understand the argument for marginal cost coverage, but have seen the unfortunate end-result of too many sales -- that use this lower cost factor -- hurt a bank’s bottom line. Administrative cost does not normally require additional risk adjustment, as any risk-based operational expenses and costs of mitigating operation risk are already included in the bank’s general ledger for non-interest expenses.

The second expense subtracted from net interest income is credit risk cost. This is not the same as the bank’s provision expense, and is certainly not the same as the loss provision in any one accounting period.  The credit risk cost for pricing purposes should be risk adjusted based on both product type (usually loan collateral category) and the bank’s risk rating for the loan in question. This metric will calculate the relative probability of default for the borrower combined with the loss given default for the loan type in question.

We usually annualize the expected loss numbers by taking into account a multi-year history and a one- or two-year projection of net loan losses. These losses are broken down by loan type and risk rating based on the bank’s actual distribution of loan balances.

The risk costs by risk rating are then created using an up-sloping curve that is similar in shape to an industry default experience curve. This assures a realistic differentiation of losses by risk rating. Many banks have loss curves that are too flat in nature, resulting in little or no price differentiation based on credit quality. This leads to poor risk-based performance metrics and, ultimately, to poor overall financial performance. The loss expense curves are fine-tuned so that over a period of years the total credit risk costs, when applied to the entire portfolio, should cover the average annual expected loss experience of the bank.

By subtracting the operating expenses and credit risk loss from risk-adjusted net interest income, we arrive at risk-adjusted pre-tax income. In my next post we’ll expand this discussion further to risk-adjusted net income, capital allocation for unexpected loss and profit ratio considerations.

Due to the recent economic events, increased collections workloads are straining client infrastructures and resources. Most clients in North America operate their delinquent accounts on legacy collections systems that are inflexible and expensive to manage and maintain. A recent and abrupt spending shift has drifted toward collections tools, data, operational, efficient workflow and decisioning systems.

On the information technology front, the collections workflow software industry is on the brink of a technology shift from legacy systems to modern next generation offerings that are typically coded in Java. Very few collections software vendors have actually released and implemented their next generation products and are preparing to do so over the next six to 12 months. Clients are aware of this technology shift and the interest of many end users has been heightened and many are actively researching and shopping.

Reducing operational costs is an urgent priority for most financial institutions and utilities. Legacy systems do not allow management to change strategies or flows quickly or in a cost effective manner, which leaves most collections departments unable to keep up with rapidly changing environments and business objectives. Clients also have critical business needs to reduce losses, improve cash flow and promote customer satisfaction. 

Many clients maintain multiple systems and it is common that these disparate systems do not communicate with each other. Consolidating collections operations and databases into one central system is strongly desired and presents an opportunity for significant financial gain.

 

I encourage all of you to have a look at this newly launched Federal Trade Commission Web site dedicated to the Red Flags Rule guidelines.  It is a good resource to that organizes the requirements of the Rule in a user-friendly manner.  It also looks to be an ongoing resource for the posting of updates and related commentary.  I suggest you make this site one of your bookmarks today:
 

The Federal Trade Commission has launched a Web site to help entities covered by the Red Flags Rule design and implement identity theft prevention programs. The Rule requires “creditors” and “financial institutions” to develop written programs to identify the warning signs of ID theft, spot them when they occur, and take appropriate steps to respond to those warning “red flags.”
 

Of particular interest, is the "Read the Guide" tab, where you can view and download the new FTC guide to Red Flag Rules.  For those in the telecommunications and utilities spaces, check out the "Publish the Articles" tab where you will find two bulletins on Red Flags in these arenas.  Enjoy.

Beyond the financial risk management considerations related to a bank’s capital, which would be directly impacted by Troubled Asset Relief Program (TARP) participation, it should be clear that TARP also involves business (or strategic) risk. We have spoken in the past of several major categories of risk: credit risk, market risk, operational risk and business risk. Business risk includes a variety of risks associated with the outcomes from strategic decision making, corporate governance considerations, executive behavior (for better or worse), management succession events (Apple and Steve Jobs, for instance) or other leadership occurrences that may affect the performance and financial viability of the business.

Aside from the monetary impact on the bank’s capital position, TARP involves a new capital securities owner being in the mix. And, with a roughly 20 percent infusion of added tier one capital, we are almost always talking about a very large, new owner relative to existing shareholders. The United States Department of the Treasury is the investor or holder of the newly issued preferred stock and warrants. The Treasury Department says it does not seek voting rights, but none-the-less has gotten them in at least some cases. The real “kicker” is embedded in the Treasury’s Securities Purchase Agreement – Standard Form. 

The most interesting clause, that appears to represent a very open-ended business risk to management decision making, is one relatively small paragraph, named Amendment, in the middle of Article V - Miscellaneous, just ahead of governing law (which is federal law, backed up by the laws of the State of New York).

Amendment begins normally enough, requiring the usual signed agreement of each party, but then states: “provided that the Investor may unilaterally amend any provision of this Agreement to the extent required to comply with any changes after the Signing Date in applicable federal statutes.” Wow. My reading of this is that if in the future Congress enacts anything that Treasury finds applicable to any aspect of the previously signed TARP Agreement, the bank is bound to go along. Regardless of whether the Treasury negotiates any voting rights, once the TARP Agreement is executed by the bank, management is not only bound by what is in the document to begin with, it is subject to future federal law as long as the TARP shares are held by the government. As a result, many banks have said no thank you to TARP.

At least four banks have recently paid back $340 million to repurchase the government’s shares. And, apparently another bank has offered to pay back $1 billion but, according to Andrew Napolitano at Fox Business Channel, the offer was turned down and the bank was threatened with adverse consequences if it persisted in its attempt to get out.

More pointed and public, and much larger in size, is the dance taking place now between Chrysler Corporation, Fiat, the UAW, four lead lenders and, you guessed it, the federal government. The secured loans in question total almost $7 billion and the government wants J.P. Morgan Chase, Goldman Sachs, Citicorp and Morgan Stanley to exchange $5 billion of the loans for Chrysler stock. The banks know they would do better (for their shareholders) by selling off Chryslers assets. This is an example of why bankruptcy exists. The stakes are large and so is the business risk of the influence from the government. It will be interesting to see how things turn out.

So, this new major owner does have a voice. If Congress wants certain lending volumes or terms, or they want certain compensation levels, it needs to be enacted into federal law. Short of having to pass a law, there is the implied threat of the big stick in the TARP agreement. The Purchase Agreement covers what the new owner wants now and may decide it wants in the future. This a form of strategic business risk that comes with accepting the capital infusion from this particular source.

This post is a feature from my colleague and guest blogger, Mark Sofietti, Associate Process Architect in Advisory Services at Baker Hill, a part of Experian.

Change is inevitable.  If you are not changing, then you are standing still and the world around you is changing.  In today’s market, the banking industry seems to be changing at a very rapid pace.  The current crisis that we are in, as an industry and as a nation, is forcing institutions to revisit their risk management policies and procedures to make the appropriate changes needed to remain healthy and profitable.  However, the current crisis is not the only reason why institutions should focus on change management.  Change management needs to be appropriately handled in bad and good times.  Understanding change management is always a necessity to a well-run organization.  Whether it is a reorganization, a new collections software system, a new policy or moving to a new building, change can cause a great deal of stress and uncertainty -- but it can also cause benefits.

So, as managers, you may be asking, “What can I do to ensure that positive changes are happening within my organization?  What are some of the items that I should consider when I am bringing about organizational change?” 

There are four necessary steps that need to be taken in order to improve the success of an initiative that is causing change to an institution.

1.  Understand current situation and needs
The first item necessary to have a successful implementation of change is to understand the current climate and reason for the change.  People are scared of change and many believe that “if it is not broken, don’t fix it.”  This is why the reasons for change need to be understood and communicated to all employees.  Changing, just for the sake of changing, causes a great deal of unrest to a department or organization.  With clearly defined reasons and objectives, the implementation of change can have a lower degree of failure.

2.  Identify resistance
During change, there will be some form of resistance.  As a manager, you will need to have thought through from where resistance might come and consider how to work through confrontations. 

One type of major resistance can be people who are looking out for their own self-interests.  People have their own agendas within the workplace and could view change as a threat to their advancement.  When dealing with these situations, you will need to have a good deal of collaboration and involvement from these individuals in order to successfully implement change.  Note, given this resistance, that the change will not happen as quickly and your timelines should be appropriately set. 

Another major resistance that may slow down the implementation of change is the lack of trust in the leaders enacting the change.  In these situations, management should build teams of trusted and respected people whose objective is to eliminate underlying resistance. 

Finally, providing facts and examples regarding the change is a necessity for a successful implementation.  Doing so can reassure employees that the change being made is beneficial to the organization.

The next post will continue with the additional two necessary steps that need to be taken in order to improve the success of an initiative that is causing change to an institution.

 

This post is a feature from my colleague and guest blogger, Barry Timm, Senior Process Architect in Advisory Services at Baker Hill, a part of Experian.

2008 has proven to be an unbelievably challenging year for the economy as a whole, let alone the financial industry.  Never before have we experienced the type and degree of turmoil that we did in 2008, even since the “Great Depression”.
 

These economic challenges have been quick, severe and widespread; and, from large corporations to the individual consumer, all have been impacted to some degree.  The stock market is down, unemployment up, consumer confidence down, delinquencies up ….not exactly a pleasant roller coaster ride. 
 

And, there is no longer any projecting as to when the “bubble” is going to burst.  It happened.   Decreased real estate values have occurred not only in high impact geographic regions but throughout the country.  While home equity products have traditionally been the “golden child” of consumer loan product offerings, recent economic changes have caused a shift in that perspective.  As a result, tightened underwriting standards have limited the availability of the product as a whole.  In some markets the product offering has even been temporarily halted.
 

We frequently hear the terminology “bailout” being used in the news.  While we all have expectations as it relates to the bailout approach, I thought I would “Google” the word “bailout” to see what would magically appear.  Interestingly enough, the first listing was titled “Walk away from your home”, with a link to the home page for a mortgage default legal team.  This is not exactly what I was expecting to find, but is definitely reflective of the times.
 

And, according to the FDIC, there have been 25 failed financial instituions in the year 2008.  This single year number equates to the total number of failed financial institutions between the prior periods 2001 through 2007. 

Okay … enough doom and gloom.  In spite of all that has occurred within the economy, some financial institutions continue to maintain a strong credit quality position in their consumer portfolios and have maintained profitability throughout all of the market volatility.  

What are the strong survivors doing that differentiates themselves from the others?

1. They understand their portfolio.  
Advisory Services frequently assists clients with various types of portfolio management analysis and often presents those findings to senior management.  We often hear that management is surprised by the results of that analysis. The point is that high-level management reporting is not enough these days. Additional detail and depth are necessary. 

More specifically, as opposed to evaluating payment performance at the portfolio level, it is important to consider the following:

• Do you know your delinquency numbers at the product level? 
• How do delinquencies compare to your product approval rates? 
• Do you routinely compare approval/decline rates and delinquencies to scorecard results and/or credit bureau scores?  
• Do you know where pricing exceptions are being made and are you receiving sufficient return for the level of risk?

2. A focused strategy is in place.
It is important to re-emphasize the specific, strategic direction and focus of your defined market.  Now is not the time to be “pushing the envelope” and extending into untested waters.  There is something to be said about focusing on your strengths, staying within your defined footprint and meeting the needs of your core, proven line of business while following sound financial risk management.

3. The underwriting process is under control.
This does not automatically mean that a “tightening” of underwriting standards is necessary.  It does mean, however, that stronger attention to detail is warranted.  It is important that underwriting criteria is reviewed and that you are sure that defined underwriting practices are consistently applied.  As noted in item number one above, this may require digging a little deeper and reviewing current and past decisioned loans (preferably with a critical eye of an independent third party).  Assessing the underwriting process becomes increasing complex and more critical with a decentralized underwriting approach.

Focus on the positive
Now that 2008 is behind us, let’s continue to focus on the positives to come in 2009.  Reflect on the past, but strive to center your attention on ongoing portfolio monitoring, financial risk management assessments and improvements for the future. 

 

Part 6

Peer Group 2 fee income
Non-interest income again, as a percent of average total assets, declined to .86 percent from .95 percent in 2007. For Peer Group 2 (PG2), fees have also been steadily declining relative to asset size, down from 1.04 percent of assets in 2005. A smaller, non-interest bearing deposit base with no other new and offsetting sources of fee income will lead to increased pressure on this metric.

Operating expenses
Operating expenses also put more pressure on earnings on these smaller banks. They increased from 2.79 percent to 2.83 percent of average assets. That’s four basis points on the negative. Historically, this metric has been flattering for this size bank and usually moves up or down from year-to-year. It was almost equal at 2.82 percent of assets in 2004.

As a result of the sizeable decline in margins, the continued decline in fee income and the slight increase in operating expenses PG2’s efficiency ratio lost ground from 59.52 percent in 2007 to only 64.72 percent in 2008. That means that every dollar in gross revenue cost them almost 65 cents in administrative expenses this year. This metric averaged 56 cents in 2005/2006. It’s amazing how close these numbers are for banks of very different size where you would expect clear economies of scale.

The total impact of margin performance, fee income and operating expenses, plus the huge increase in provision expense of 59 basis points leads us to a total decline in pre-tax operating income of .96 percent on total assets. That is a total decline from 1.58 percent pre-tax ROA in 2007 to .64 percent pre-tax ROA, a loss of 61 percent from the pre-tax performance in 2007. My same conclusion as above would hold regarding the pricing of risk into bank lending (although the smaller banks didn’t perform a badly as the larger in this regard).

Although all 490 banks are declining in all profit metrics, the smaller banks seem to have an edge in pricing loans, but not deposits. Although up dramatically in 2007, and even more in 2008 for both groups, the PG2 banks seem to be suffering fewer credit losses relative to their asset size than their larger brethren. Both groups have resulting huge profit declines, but the largest banks are under the most pressure through this period.

An interesting point, with higher loan yields and fewer apparent losses, is whether PG2 banks are somewhat better at risk-based pricing (for whatever reason) than the largest bank group. Results are results. The 2009 numbers aren’t expected to show a lot of improvement as the general economy continues to slow and credit and financial risk management issues continue. We’ll probably comment on 2009 as the quarterlies become available this year.

Part 5

This continues the updated review of results from the Uniform Bank Performance Reports (UBPR), courtesy of the FDIC, for 2008. The UBPR is based on the quarterly required Call Reports submitted by insured banks. The FDIC compiles peer averages for various bank size groupings. Here are some findings for the two largest groups, covering 494 reporting banks. I wanted to see how the various profit performance components compare to the costs of credit risk discussed in my previous post. It is even more apparent than it was in early 2008 that banks still have a ways to go to be fully pricing loans for both expected and unexpected risk.

Peer Group 2 (PG2) consists of 305 reporting banks between $1 billion and $3 billion in assets. PG2’s Net Interest Income was 5.75 percent of average total assets for the year. This is also down, as expected, from 6.73 percent in 2007. Net Interest Expense also decreased from 3.07 percent in 2007 to 2.31 percent for 2008.  Net Interest Margin, also declined from 3.66 percent in 2007 to 3.42 percent in 2008, or a loss of 24 basis points. These margins are 31 bps or 10 percent higher than found in Peer Group 1 (PG1), but the drop of .24 percent was much larger than the .05 percent decline in PG1.

As with all banks, Net Interest Margins have shown a steady chronic decline, but the drops for PG2 have been coming in larger chunks the last two years -- -24 basis points last year after dropping 16 points from 2006 to 2007.

Behind the drop in margins, we find loans yields of 6.53 percent for 2008, which is down from 7.82 percent in 2007. This is a decline of 129 basis points or 16 percent. Meanwhile, rates paid on interest-earning deposits dropped from 3.70 percent in 2007 to 2.75 percent in 2008. This 95 basis point decline represents a 26 percent lower cost of interest-bearing deposits. Again, with a steeper decline in interest costs, you would think that margins should have improved somewhat. It wasn’t meant to be. 

We see the same two culprits as we did in PG1. Total deposit balances declined from 78 percent of average assets to 77 percent which means again, that a larger amount had to be borrowed to fund assets. Secondly, non-interest bearing demand deposits continued an already steady decline from 5.58 percent of average assets in 2007 to 5.03 percent. This, of course, resulted in fewer deposit balances relative to total asset size and a lower proportion of interest-cost-free deposits.

Check my next blog for more on an analysis of Peer Group 2’s fee income, operating expenses and their use of risk-based pricing.

 

Part 4

Let’s dig a bit deeper into why Peer Group 1’s margins didn’t improve. We see two possible reasons: Total deposit balances declined from 72 percent of average assets to 70 percent. This means that a larger amount had to be borrowed to fund their assets. Secondly, non-interest bearing demand deposits declined from 4.85 percent of average assets to 4.24 percent. So, fewer deposit balances relative to total asset size, along with a lower proportion of interest-cost-free deposits, appear to have made the difference.

Fee income
Non-interest income, again as a percent of average total assets, was down to 1.12 percent from 1.23 percent in 2007. This was a decline of 9 percent. For Peer Group 1 (PG1), fees have also been steadily declining relative to asset size, down from 1.49 percent of assets in 2005. A lot of fee income is deposit based and largely based on non-interest bearing deposits. So, the declining interest-free balances, as a percent of total assets, are a source of pressure on fee income and have a negative impact on net interest margins.

Operating expenses
Operating expenses constituted more bad news as they increased from 2.63 percent to 2.77 percent of average assets. Most of the large scale cost-cutting didn’t get started early enough to favorably impact this number for last year. Historically, this metric has moved down, irregularly, as the size of the largest banks has grown. This number stood at 2.54 percent in 2006, for instance. We saw increase in both 2007 and again in 2008.

As a result of the decline in margins and the larger percentage decline in fee income, while operating costs increased, the Peer Group 1 efficiency ratio lost ground from 57.71 percent in 2007 up to 63.70 percent in 2008. This 10 percent increase is a move to the bad. It means every dollar in gross revenue [net interest income + fee income] cost them almost 64 cents in administrative expenses in 2008. This metric averaged 55 cents in 2005/2006.

The total impact of changes in margin performance, fee income, operating expenses and the 2008 increase in provision expense of 87 basis points, we arrive at a total decline in pre-tax operating income of 1.23 percent on total assets. That is a total decline of 80 percent from the pre-tax performance in 2007 of 1.53 percent pre-tax ROA to the 2008 result for the group of only .30 percent pre-tax ROA.

It would appear that banks have not been utilizing pricing enough credit risk into their loan rates.  This would be further confirmed if you compared bank loan rates to the historic risk spreads and absolute rates that the market currently has priced into both investment grade and below-investment-grade corporate bonds. These spreads have decreased some very recently, but it is predicted that more credit risk is present than bank lending rates would indicate.
 

Part 3

I believe it is quite important to compare your bank or your investment plans in a financial institution to the results of peer group averages. Not all banks are the same, believe it or not. In this column, we use the averages. Again, look for the differences in your target institution. About half of them beat certain performance numbers, while the other half are naturally worse. It can tell a useful story.

This continues the updated review of results from the Uniform Bank Performance Reports (UBPR), courtesy of the FDIC, for 2008. The UBPR is based on the quarterly required Call Reports submitted by insured banks. The FDIC compiles peer averages for various bank size groupings. Here are the findings for the two largest groups that cover 494 reporting banks. I wanted to see how the various profit performance components compare to the costs of credit risk discussed in my previous post. It is even more apparent than it was in early 2008 that banks still have a ways to go to be fully pricing loans for both expected and unexpected risk.

Peer Group 1 (PG1) is made up of the largest 189 reporting banks or those with over $3 billion in average total assets for 2008. Interest income was 5.25 percent of average total assets for the period. This is down, as we might expect, based on last year’s decline in the general level of interest rates from 6.16 percent in 2007. Net Interest Expense was also down from 2.98 percent in 2007 to 2.06 percent average for the year. Net Interest Margin, the difference between the two metrics, was down from 3.16 percent in 2007 to 3.11 percent as a percentage of total assets.

It should be noted that Net Interest Margins have been in a steady, chronic decline for at least 10 years, with a torturous regular drop of 2 to 5 basis points per annum in recent years. Last year’s drop of five basis points is in line with that progression and it does add to continuing difficulty in generating bottom-line profits.

To find out a bit more about why margins dropped, especially in light of the steady increase in lending over the same past decade, we looked first at loan pricing yields. For PG1 these averaged 6.12 percent for 2008, down (again, expectedly) from 7.32 percent in 2007. This is a drop of 120 basis points or a decline of 16 percent. Meanwhile, rates paid on interest-earning deposits dropped from 3.41 percent in 2007 to 2.39 percent in 2008. This 102 basis point decline represents a 30 percent lower interest expense on interest-bearing deposits. Based only on these two metrics, it seems like margins should have improved and not declined for these banks.

Check my next blog for more on the reasons for Peer Group 1’s drop in margins and an analysis of the fee income and operating expenses for these institutions.
 

Part 2

In my last post, I started my review of the Uniform Bank Performance Reports for the two largest financial institution peer groups through the end of 2008.

Now, lets look at the resutls relating to credit cost, loss allowance accounts and the impacts on earnings. Again, as you look at these results, I encourage you to consider the processes that your bank currently utilizes for credit risk modeling and financial risk management.

Credit costs
More loans, especially in an economic downturn, mean more credit risk. Credit costs were up tremendously. The Peer group 1 banks reported net loan losses of .89% of total loans. This is an increase from .28% in 2007, which was up from an average of 18 basis points on the portfolio in 2006/2005.  The Peer group 2 banks reported net loan losses of .74%. This is also up substantially from 24 basis points in 2007 and an average of 15 basis points in 2006/2005. The net loan losses reported in the fourth quarter significantly boosted both groups’ year-end loss percentages above where they stood through the first three quarters last year.

Loss allowance accounts
Both groups also ramped up their reserve for future expected losses substantially. The year-end loss allowance account (ALLL) as a percent of total loans stood at 1.81% for the largest banks. This is an increase of almost 50% from an average of 1.21% in the years 2007/2004. Peer group 2 banks saw their reserve for losses go up to 1.57% from an average of 1.24% in the years 2007/2004.

The combination of covering the increased net loan losses and also increasing the loss reserve balance required a huge provision expenses. So, loan balances were up even in the face of increased write-offs and expected forward losses.

Impacts on earnings
Obviously, we would expect this provisioning burden to negatively impact earnings. It did, greatly. Peer group 1 banks saw a decline in return on assets to a negative .07%. This is just below break-even as a group. The average net income percentage stood at .42% of average assets at the end of the third quarter. So, the washout in the fourth quarter reports took the group average to a net loss position for the year. The ROA was at .96% in 2007 and an average of 1.26% in 2006/2005. That is a 111% decline in ROA from 2007. Return on equity also went into the red, down from 11.97% in 2007. ROE stood at 14.36% in 2005.

For the $1B to $3B banks, ROA stood at .35%. This is still a positive number, however, it is way down from 1.08% in 2007, 1.30% in 2006 and 1.33% in 2005. The decline in 2008 was 67% from 2007. ROE for the group was also down, at 4.11% from 12.37% in 2007. The drops in profitability were not entirely the result of credit losses, but this was by far the largest impact from 2007.

The seriously beefed-up ALLL accounts would seem to indicate that, as a group, the banks expect further loan losses, at least through 2009.  These numbers largely pre-dated the launch of the Troubled Asset Relief Program and the tier one funding it provided in 2008. But, it is clear that banks had not contracted lending for all of 2008, even in the face of mounting credit issues and a declining economic picture. It will be interesting to see how things unfold in the next several quarters.