Financial Services

By: Tom Hannagan   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.  

By: Tom Hannagan 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 Reducing operational and overhead costs starts with the automation of tasks that would otherwise be performed by a human resource. By leveraging an advanced segmentation approach, it is possible to better identify accounts that will not require collector intervention. While automation is not a new concept to collections, significant benefits of modern systems include: • enabling more functions to be automated; • effectiveness of the automated functions to be validated; and • more changes made per year versus legacy systems. Fixing a bad phone number: The old way To illustrate effective automation, let’s use an example where an account is found to have a bad phone number. A common approach to this problem might be for the outbound collector to route the account to a skip specialist who can perform research. This often has the receiving party starting the process after the nightly batch process has transferred the account across departments. If a phone number is found, the account may be manually routed back to an outbound queue and if not, a no-contact letter may be generated. Additionally, there are tasks that need to be performed such as noting accounts that consume a collector’s time. Fixing a bad phone number: The new way A more efficient and cost-effective approach would be for the employee identifying the need for a new number to click a pre-defined button to let the collections system know of the issue. The system could then automatically call out to an external data source to: • collect the new number; • repopulate the appropriate field; • reroute the account back to the most appropriate outbound queue; • log a history of all automated functions performed, and • do all of this within just a few seconds! If the appropriate number cannot be located, the system would know which letter to send and then route the account to the most appropriate holding queue. Reducing operational costs After automation, the operational costs are further reduced by identifying which actions can be effectively replaced by lower-cost options that yield the same results, or even eliminating actions that present no substantial value. For example, why make a call when a letter will suffice? And what happens if we subsequently replace that letter with a text message or take no action at all? Intelligent features of modern systems such as champion/challenger testing can be employed to support a continuous learning process that increases the financial benefits of automation as experience and knowledge is gained. As new automation is introduced and validated as beneficial, other improvement theories can be tested and subsequently abandoned or adopted. Considering the possible impact of automation and action reductions on cost savings let’s assume that three dial attempts are made on the average delinquent account in the first 30 days at a cost of 25 cents each and on the fourth attempt there is a right party contact, which costs an additional $2.50 (assuming the talk time is five minutes). Adding one letter at 75 cents, we have a total cost to collect of $4.00 before the account hits 31 days past due. With 250,000 customers entering collections each month, we can save $200,000 each month in the early stage alone with just a 20 percent improvement. This result could easily be achieved by reducing talk time and eliminating unnecessary actions or unproductive call attempts. Annually that adds up to approximately $2.5 million dollars in savings, in this example. Champion/challenger tests, as well as, the improved functionality of modern systems can also be extended beyond the in-house work stream. Evaluating and comparing external agencies can significantly improve agency performance as well as enable the lender to better manage placement costs. For example, if a lender allocates 1,000 accounts to an external agency each month, with an average balance of $3,000, the total dollars allocated annually is $36 million. If 22 percent of the debt is collected and a 25 percent commission is charged, the net to the lender is nearly $6 million. Improving that return by a mere 4 percent through better allocation strategies, which is a conservative goal, we add another million to the bottom line each year. By factoring in the ability of next generation collections systems to automate most aspects of the placement process itself, including recalling accounts, we further improve efficiencies, free up valuable resources and allow management greater control of the process. Additional benefits of functionally rich modern systems also enable management to grant external resources various levels of remote access to the collections systems to better monitor activities and ensure that transactional data is properly captured. In addition to granting external agencies remote access, modern collections systems can also enable collectors to work from home-based workstations to further reduce operational costs. Many industry analysts see this as an emerging trend over the next few years, particularly when productivity can be monitored in real-time. My next blog will continue the discussion on the benefits of next generation collections systems and will provide details on improved change management processes.  

Here are a few more frequently asked questions. 1. Am I a “creditor” under the rule? The term “creditor” has the same meaning as under the Equal Credit Opportunity Act (ECOA) and is defined as a person who regularly participates in credit decisions, including, for example, a mortgage broker, a person who arranges credit or a servicer of loans who participates in “workout” decisions. The term “credit” is defined, as in the ECOA, as the right granted by a creditor to defer payment for goods or services. It is important to note that commercial, as well as consumer, credit accounts may be covered by the Rule. 2. We are an insurance company that uses credit reports to underwrite insurance. Does the Red Flags Rule apply to us? The Red Flag Rule applies to creditors and depository institutions and should not apply to an insurer when engaged in activities related to insurance underwriting. To the extent that you extend credit, however, you may be covered. For example, you may wish to examine whether you permit consumers to finance their premiums; whether you extend credit to vendors, independent agents or other business partners; or whether you extend credit in connection with your investment activities, including real-estate investments. 3. I am an auto dealer. Does the rule apply to me? If the business extends auto credit to consumers or arranges auto credit for consumers, the Red Flag guidelines may apply.  

By: Tom Hannagan 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.

Here we are in March, 2009, four months after the Red Flags Rules deadline OR two months until the Red Flags deadline…depending on your glass-half-full / glass-half-empty view of the world.  I can say with confidence that at this point in time, the Identity Theft Red Flags 'discussion' with our clients and the market at large continues in full earnest.  That said, however, the nature of our discussions has changed substantially.  A few months ago, the needs expressed by the market centered on education around the Red Flags Rule, Red Flag compliance and it's applicability to various markets and account types. I find that the majority of my daily conversations on the subject now regard efficiencies in process and cost combined with effectiveness and customer experience. Most of our clients 'get' what they need to be doing such as identifying, detecting and responding to Red Flag conditions.  Where we are still working closely with our clients is in how they can optimize their policies and procedures to ensure that the majority of Red Flag conditions are detected and reconciled in singular automated steps.  As I've said in previous blogs, detecting these conditions is the easy part. It's how you reconcile (a.k.a. respond to) those conditions that makes the difference in your bottom line. As May 1 approaches, now is a great time to be monitoring each step in your process in an effort to identify those areas that may still have room for efficiency gains and improved customer experience.

Address discrepancies aren't the end of the road, but they sure can be a bump in it. One of the handful of mandatory elements in the Red Flag guidelines, which focus on FACTA Sections 114 and 315, is the implementation of Section 315.  Section 315 provides guidance regarding reasonable policies and procedures that a user of consumer reports must employ when a consumer reporting agency sends the user a notice of address discrepancy.  A couple of common questions and answers to get us started: 1.  How do the credit reporting agencies display an address discrepancy? Each credit reporting agency displays an “address discrepancy indicator,” which typically is simply a code in a specified field. Each credit reporting agency uses a different indicator. Experian, for example, supplies an indicator for each displayable address that denotes a match or mismatch to the address supplied upon inquiry. 2.  How do I “form a reasonable belief” that a credit report relates to the consumer for whom it was requested? Following procedures that you have implemented as a part of your Customer Identification Program (CIP) under the USA PATRIOT Act can and should satisfy this requirement. You also may compare the credit report with information in your own records or information from a third-party source, or you may verify information in the credit report with the consumer directly. In my last posting, I discussed the value of a risk-based approach to Red Flag compliance.  Foundational to that value is the ability to efficiently and effectively reconcile Red Flag conditions…including addressing discrepancies on a consumer credit report. Arguably, the biggest Red Flag problem we solve for our clients these days is in responding to identified and detected Red Flag conditions as part of their Identity Theft Prevention Program.  There are many tools available that can detect Red Flag conditions.  The best-in-class solutions, however, are those that not only detect these conditions, but allow for cost-effective and accurate reconciliation of high risk conditions.  Remember, a Red Flag compliant program is one that identifies and detects high risk conditions, responds to the presence of those conditions, and is updated over time as risk and business processes change. A recent Experian analysis of records containing an address discrepancy on the credit profile showed that the vast majority of these could be positively reconciled (a.k.a. authenticated) via the use of alternate data sources and scores.  Layer on top of a solid decisioning strategy using these elements, the use of consumer-facing knowledge-based authentication questions, and nearly all of that potential referral volume can be passed through automated checks without ever landing in a manual referral queue or call center.  Now that address discrepancies can no longer be ignored, this approach can save your operations team from having to add headcount to respond to this initially detected condition.  

By: Tom Hannagan 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.

By: Tom Hannagan Part 1 It may be quite useful to compare your financial institution's portfolio risk management process or your investment plans , to the results of peer group averages. Not all banks are the same -- believe it or not. Here are the averages. You should look for differences in your target institution. About half of them beat certain performance numbers and the other half may be naturally worse. As promised, I have again reviewed the Uniform Bank Performance Reports for the two largest peer groups through the end 2008. The Uniform Bank Performance Report (UBPR) is a compilation of the FDIC, based on the call reports submitted by insured banks. The FDIC reports peer averages for various bank size groupings and here are a few notable findings for the two largest groups that covers 494 reporting banks. Peer group 1 Peer group 1 consisted of 189 institutions over $3 billion in average total assets for the year. Net loans accounted for 67.31% of average total assets, which is up from 65.79 % in 2007. Loans, as a percent of assets, have increased steadily since at least 2004. The loan-to-deposit ratio for the largest banks was also up to 96% from 91% in 2007 and 88% in both 2006 and 2005. So, it appears these banks were lending more in 2008 as an allocation of their total asset base and relative to their deposit sources of funding. In fact, net loans grew at a rate of 9.34% for this group, which is down from the average growth rate of 15.07% for the years 2005 through 2007.  The growth rate in loans is down, which is probably due to tightened credit standards. However, it is still growth. And, since total average assets also had growth of 11.58% in 2008, the absolute dollars of loan balances increased at the largest banks. Peer group 2 Peer group 2 consisted of 305 reporting financial institutions between $1B and $3B in total assets. The net loans accounted for 72.96% of average total assets, up from 71.75% in 2007. Again, the loans as a percent of total assets have increased steadily since at least 2004. The loan-to-deposit ratio for these banks was up to 95% from 92% in 2007 and an average of 90% for 2006 and 2005. So, these banks are also lending more in 2008 as a portion of their asset base and relative to their deposit source of funding. Net loans grew at a rate of 10.48% for this group in 2008 which is down from 11.94% growth in 2007 and down from an average growth of 15.04% for 2006 and 2005. And, since total average assets also had growth of 10.02% in 2008, the absolute dollars of loan balances also increased at the intermediate size banks. Again here, the growth rate in loans is down, probably due to tightened credit standards, but it is still growth and it is at a slightly more aggressive rate than the largest bank group. Combined, for these 494 largest financial institutions, loans were still growing through 2008 both as a percentage of asset allocation and in absolute dollars. Tune in to my next blog to read more about the results shown relating to credit costs, loss allowance accounts and the impacts on earnings.

At which stage of the application process does the Red Flags Rule apply? The Red Flag Rule would apply whenever you detect a Red Flag in connection with an application. This could occur as soon as you receive an application, for example: if the application appears to have been altered or forged; or the consumer’s identification appears to be forged or is inconsistent with the information on the application. Is the social security number (SSN) check a requirement? No, but an invalid SSN may be a Red Flag – i.e., an indicator of possible identity theft – and obtaining and verifying a SSN may be a reasonable means of application risk management to detect this Red Flag when opening accounts. You may be able to utilize your existing procedures under your Customer Identification Program under the USA PATRIOT Act.  

What to do when you see a Red Flag. Your Identity Theft Prevention Program should include appropriate responses when you detect a Red Flag. You must assess whether the Red Flag evidences a risk of identity theft. If so, your response must be commensurate with the degree of risk posed. Depending on the level of risk, an appropriate response may include contacting your applicant, not opening a new account or even determining that no response is necessary.  

By: Tom Hannagan Part 1 Beyond the risk management considerations related to a bank’s capital position, which is 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; Governance considerations; Executive behavior (for lack of better terminology); Management succession events 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 20% infusion of added tier 1 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 does not have voting rights like common shareholders, but the Treasury’s Securities Purchase Agreement – Standard Form includes at least 35 pages of terms, plus the required Letter Agreement, Schedules attached to the Letter Agreement and at least five significant Annex’s to the Purchase Agreement. It’s NOT an easy, quick or fun read. In the Recitals section, it states that the bank: “agrees to expand the flow of credit to U.S. consumers and businesses on competitive terms as appropriate to strengthen the health of the U.S. economy” and, later, “agrees to work diligently, under existing programs, to modify the terms of residential mortgages as appropriate to strengthen the health of the U.S. economy.” Fortunately, if you’re a banker, these topics are not (currently) revisited elsewhere in the document, period. However, these are examples of the new shareholder effecting business decision making without the need to be on the Board of Directors, or voting common shares. The Agreement covers a number of other requirements and limitations, such as executive compensation, dividend payments, other capital sourcing and retention of bank holding company status. None of these are particularly onerous, but they must be taken into account by management. Visit my next post to read about the very interesting Amendment clause that may represent an open-ended business portfolio risk management decision for the future.

We have been hearing quite a bit about the ponzi scheme that was created and managed by Bernie Madoff.  Almost $50 billion dollars was taken from those that were considered to be sophisticated and definitely not the typical type to be scammed.  So, what created the environment that allowed such large sums of money to be lost in such a basic con game as a ponzi scheme?  I believe there are a few basic factors that prompted these seemingly sophisticated people to invest in this ill-fated “investment.” A strong desire to generate investment returns when the typical channels were not delivering. The reputation(s) of the existing client list -- If they invested why shouldn’t I? The thought that if it paid off with smaller dollar investments, just think what could be made with larger dollars! Hmmm!  Sounds like how we got ourselves into today’s credit situation.  Basically, we were distracted by the items noted above and ignored the warning signs. Putting the items above into credit industry terms it can be summed up as follows: We have to continue to grow and we are pressured to find more opportunities.  If we go lower in the credit quality spectrum, it can generate immediate volume from the existing application volume. Other financial institutions have gone into this type of lending and they aren’t showing any signs of significant distress in their portfolios.  We need to do the same.  (Everyone in the herd in favor of this action please respond by saying “Moo.”) Our test portfolio has performed acceptably, so let’s increase the volume. Let’s continue the correlation between these two “problems.”  In the Madoff ponzi scheme, there were warning signs that cropped up - some earlier than others. These included: In 2000, the Securities and Exchange Commission received a letter from an outside money manager which warned of a possible scheme. In 2005, the Bostonian submitted an 18-page document to the SEC citing 29 red flags and indicated some level of corruption within Madoff’s investment company. The SEC’s own earlier investigation conducted in 1999, included an acknowledgement that they had received “credible allegations” but these allegations were ignored. So, what were the signs that were in front of us but we simply chose to ignore? Were the portfolios turning over so fast that we could not actually gather statistically valid data to support performance? Since we were selling off the loans, either individually or in bulk, did we ignore the actual risk that was taken by the industry? Were we appropriately monitoring the portfolio growth and performance, utilizing risk reduction and risk avoidance techniques, doing regular rescores and tracking potential behavioral issues? Whether the signs were visible to us or not, the fact remains that they existed in the past and they will likely exist in the future.  As we continue to clean up the mess of our past, we need to consider a few items: What we did in the past will no longer be acceptable going forward. We must change. We must improve. Regulatory pressures will increase and changes will continue to be made. We will not have the luxury of time to respond to these pressures and/or changes. We must act now. What is a financial institution to do?  Well, the worst thing we can do is wait for the regulators to tell us what to do because that is simply too late.  We need to act and act now. Assess the risk management methods that were employed in the past and determine deficiencies. Note the gaps between the historical tools and data sources compared with the updated credit decisioning tools and sources available in the industry. Develop a plan for implementing the new risk reduction methods and tools. Determine the estimated lift and manage/monitor your performance against your estimates. Don’t forget about the new additions to the portfolio. Once you have the existing risk identified, you should make the appropriate adjustments to the product risk parameters and terms and conditions to improve the overall quality of the new portfolio. Overall, the worst thing that we can do is nothing. Remember, “Those who do not remember the past are condemned to repeat it.” George Santayana, a philosopher, essayist, poet, and novelist

How do I know which Red Flags apply to me? The Red Flag guidelines that will apply to you depend on a number of factors including: The types of covered accounts you offer and how those accounts may be opened and accessed Your previous experiences with identity theft In order to determine the applicable Red Flags, you must consider these factors as well as various sources and categories of Red Flags identified in the Guidelines. There are many resources available to help you gain the upper hand on Identity Theft Red Flags. I encourage you to visit this site for more information including a white paper, webinar, data sheet and more.  

The difference between market risk and credit risk By: Tom Hannagan Market risk is different than credit risk. The bank’s assets are mostly invested in loans and securities (about 90% of average assets). These loans and securities have differing interest rate structures – some are fixed and some are floating. They also have differing maturities. Meanwhile, the bank’s liabilities, deposits and borrowings also have differing maturities and interest rate characteristics. If the bank’s (asset-based) interest income structure is not properly aligned with the (liability-based) interest expense structure, the result is interest rate risk. As market rates change (up or down), the bank’s earning are impacted (positively or negatively) based on the mismatch in its balance sheet structure. The bank can offset market risk by purchasing interest rate swaps or other interest rate derivatives. The impact of insufficient attention to interest rate risk can damage earnings and may, again, negatively affect the bank’s capital position. So, ultimately, the bank’s risk-based capital acts as the last line of defense against the negative impact from, you guessed it, unpredictable variability – or “risk.” That is why equity is considered risk-based capital. Good risk management, predicting and risk-based pricing leads to safer earnings performance and equity position.