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Stress Testing Effeciency

Madison has been quite successful setting up custom stress test reports and analysis for clients. It seems that every organization looks at stress testing a little differently and therefore needs a solution that can be tailored to their specific requirements. Here is an example of a stress test report that we set up for a client. It took between 4 and 8 hours to prepare the stress test from their systems but only seconds once the Stress Test was set up in Madison.

Here is what they wanted to do.

  1. Look at the portfolio of commercial real estate loans based on four scenarios: the current portfolio with no stress, a 5% stress, a 10 % stress and a 15% stress.
  2. Create one set of stresses based on LTV and another set based on DSCR.
  3. For each stress scenario and for both LTV and DSCR separately, show the results broken out by three stressed ranges from least affected to most adversely affected.
  4. Group the data by the region in which the collateral was located.
  5. If a multi property loan had collateral in more than one region, allocate the loan balance to each region based on the most recent collateral value.

We set this up in a single report that presented all the information requested with the simple click of the mouse. It took seconds to produce rather than hours.

In addition, as additional value-added to the report:

  1. Results could be grouped by many other factors in addition to region – collateral type, loan purpose, loan type, loan officer, loan office, etc.
  2. By clicking to display audit details, all the loan-by-loan details were displayed so that the user could verify accuracy and understand how individual loans were treated. And most importantly, these results let the user see the loans that were most adversely affected by the stresses.
  3. An option also allowed the user to change the scenarios from 5% increments to any other increment they desired.

Stress testing is important, but bankers should be spending their time evaluating stress test results, not manipulating raw data to create the analysis. This custom report allowed the client to do just that.

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What Regulators Want – Slice and Dice the Portfolio

Our clients are telling us that the regulators are asking them to be able to address three important issues:

  • Slice and dice the loan portfolio
  • Stress test the loan portfolio
  • Maintain a computer based loan review system


We have comments on Stress testing before, so today we will address the first of these issues � Slicing and Dicing the Loan Portfolio.

A problem with many cores systems is that they do not capture the data needed to slice and dice the 0loan portfolio. A second issue is that they are often designed to efficiently capture information necessary for the accounting system, not for flexibly reporting on the characteristics of the loan portfolio. A further limitation is that data that is not directly related to issues such as accounting and regulatory reporting is often incomplete or missing.

When clients acquire a system that is capable of slicing and dicing the loan portfolio, they obtain a much more comprehensive and robust view of the portfolio, the first consequence of which is to discover that data in the core system is inaccurate, incomplete or missing entirely. So task number one is to clean up the data, determine what additional information is necessary to support analysis of the loan portfolio, and then get the new and cleaned up information into the system. This can be a formidable task, to say the least!

Once the data is cleaned up, the portfolio can then be sliced and diced by a wide variety of characteristics such as:

  • Geography (State, Region, Market, County, City, etc.)
  • Lending Office
  • Collateral Type
  • Industry
  • Loan Type
  • Department
  • Lending Officer
  • Loan Program
  • Loan Purpose
  • Relationships
  • Tenant Characteristics
  • Occupancy Rates
  • Tenants and Tenant Industry
  • Loan Rating Distribution (and rating upgrades and downgrades)
  • Lots more!


Also, it is valuable to evaluate the results of queries such as:

  • What is the exposure to the high tech industry both in terms of C&I loan to that industry and tenants in that industry that occupy properties secured by CRE loans.
  • Which loans are in a particular market and are secured by a particular property type?
  • Which loans have leases that expire in the next few months where the tenants occupy more than a specific percent of the property?


Needless to say, all this analysis and much more can be done quickly and easily with the Madison System�s reporting and filtering functionality. But be forewarned, the easier it is to slice and dice the portfolio the more you will find that you are presented with the need to clean up the data on which the analysis is based.

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Measuring Concentration Risk

Credit Concentration Risk

Concentration risk is the risk that a segment of the loan portfolio experiences a high level of loan losses, and that because the loan portfolio is highly concentrated in that segment, the losses may threaten the safety and soundness of the institution. Because of concentration risk, lenders monitor the concentration of the loan portfolio by loan type, collateral type, geographic market, borrower and tenant industry, and a variety of additional factors.

The ability to quickly and easily monitor concentration risk is a characteristic of commercial loan applications such as the Madison System. Concentration risk can be measured by the concentration of the current loan balance by segment, or of total exposure where exposure is the current loan balance plus the additional amount that may be drawn under existing lines. For example, if there is a high concentration in the Detroit market, if that market experienced significant economic weakness, the bank might have higher loan losses.

If the loan portfolio is further concentrated by other factors such as collateral type, potential losses could be even greater. If the portfolio has a high concentration of loans collateralized by office properties in the Detroit market, and there is a weakness in that segment, losses could have an adverse effect on bank capital. So it is valuable to be able to drill down into portfolio segments to gain a fuller understanding of concentration risk.

For commercial real estate loans it may also be important to measure exposure by the industry of major tenants. If there were a high concentration of tenants in the auto industry the portfolio might be riskier than if tenants were more diversified by industry.

Another key dimension of concentration risk is by borrower industry, especially for C&I loans.

Concentration Policy Limits

Because of the importance of concentration risk, most lenders have policy limits designed to prevent undue concentration of risk. So it is valuable to be able not only to easily view concentration risk, but also compare it to policy limits.

The Madison System includes automated features that allow users to measure concentration risk quickly and easily with the simple click of a mouse. The easier it is to see concentration risk, the easier it is to manage it, and present reports to the Loan Committee and Board of Directors.

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Bank Regulatory Policy Statements for Commercial Lending

From time to time the bank regulators issue guidelines as to what they expect form lenders with respect to risk management and administration of their commercial loan portfolios. A quick review of such pronouncements for the last several years reveals four statements that should be of interest to lenders. We list these here for easy reference. In the future these and other regulatory guidelines will be listed on the Madison Associates web site as a convenience to readers. We welcome your suggestions as to other regulations and guidelines that would be of interest.

Concentration in Real Estate Lending Guidelines � December 12, 2006. This statement describes what the regulators expect from the administration of commercial real estate loan portfolios. In particular, it identifies their expectations for lenders with higher risks in their commercial real estate loan portfolio. The guideline suggest that lenders should be able to stress test their portfolios, have more detailed reporting to bank management and the Board of Directors regarding the risks in the portfolio, maintain the ability to analyze or �slice and dice� the portfolio for easy analysis, and maintain automated systems for the management of their portfolios, among other requirements. For a copy of this guideline click here.

Update on Accounting for Loan and Lease Losses (ALLL)�March 1, 2004. This 2 page document contains a list of the then-current sources of GAAP and supervisory guidance for accounting for the ALLL that will be of interest to readers that are looking for a comprehensive listing of regulatory and accounting guidance for ALLL. For a copy of this guideline click here.

Interagency Policy Statement of Allowance for Loan and Lease Losses � December 13, 2006. This guideline is intended to ensure that banking regulations are consistent with GAAP (Generally Accepted Accounting Principles) for the Allowance for Losses on Loans and Leases. It updates and replaces the previous policy issues in 1993. For a copy of this guideline click here.

Interagency Appraisal and Evaluation Guidelines � December 2, 2010. This guideline was issued to address supervisory matters relating to real estate appraisals and evaluations used to support real estate-related financial transactions. It supersedes the previous guideline issues in 1994. The appraisal regulations require, at a minimum, that real estate appraisals be performed in accordance with generally accepted uniform appraisal standards as evidenced by the appraisal standards promulgated by the Appraisal Standards Board, and that such appraisals be in writing. This 45 page statement describes how lenders are expected to comply with the appraisal of real estate. For a copy of this guideline click here.

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Loan Rating Migration

It is important to be able to evaluate how loan ratings have changed over time. For example, what percentage of loans that were originally rated a 2 are still rated a 2, what percent have declined to 3, to 4, etc. Madison�s commercial loan software allows you to prepared detailed analysis of these trends for your commercial loan portfolio.

That analysis can be filtered by a variety of factors:

  • Loan Origination Date. If, for example, you feel that loans originated in the year 2005 and 2006 were underwritten more aggressively, you can filter the report to include only loans originated in 2005 and 2006 so you can better understand how the ratings of these loans have changed.
  • Collateral Type. How have the ratings of loans collateralized by a particular collateral type changed over time? You can filter reports by one or more collateral types.
  • Geographic Market or Region. Some geographic regions or markets may have experienced greater weakness than others so it will be important to understand how the ratings for loans from these locations have changed over time.
  • Other Filter Categories. The Madison commercial loan software allows you to filter by many other loan characteristics so that you can best understand how ratings have migrated.
  • Combine filters. Filters can be combined for greater depth of analysis. For example, you can evaluate loans in a particular market(s) that were originated in 2005 and 2006. Or loans collateralized by (a) office properties (b) in a particular market(s) (c) that were originated in a particular year(s).


For presentation purposes, the Madison commercial loan software provides a summary matrix that displays percentages, a summary matrix that displays dollar amounts, and a detailed matrix that shows the performance of each loan.

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Commercial Loan Risk Management – Regulatory Issues

Commercial Loan Risk Management- Regulatory IssuesIncreasingly, regulators are placing emphasis on automation and computer support for the risk management of commercial loan portfolios. Some of the features they expect to see at banks they are examining include:

  1. 1. Comprehensive portfolio risk reporting. That is, an automated process for preparing standard risk management reports such as watch lists, delinquency reports, stress test reports, trend analysis, missing or out dated information, etc.
  2. The ability to slice and dice the portfolio — the ability to quickly and easily prepare reports that evaluate the portfolio based on factors such as loan type, collateral type, loan officer, region or market area, and numerous other parameters.
  3. Portfolio Stress testing — the ability to stress items such as collateral income, collateral value, borrower income and expenses, increases in interest rates, and other factors to determine whether loans are strong enough to withstand the stressed conditions.
  4. Loan Rating Migration — how have loan grades changed over time. Is the distribution of ratings over time is an important measure of the credit quality of the portfolio as seem by bank management, and has important implications for the allowance for loan losses.
  5. Automation of the Loan Review process. In the past Loan Review Departments captured the results of their analysis on paper forms that made it difficult to then prepare reports that summarize the results of their analysis of a portfolio. Hand entry of data is also inefficient since much of the information about the loans is already in the bank’s core system.

The Madison System includes comprehensive support for these and many other features requested by regulators. The trick for banks is to be able to create the necessary information, analysis and reports with a minimum of effort so. A fully automated system for doing so is often the best solution.

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Stress Tests – Effect of Higher Rates on Coverage Ratios

Financial Stress TestWhile interest rates are at historic lows, many lenders are mindful that rates will not stay low forever. Increasingly, they are concerned about their ability to measure the effect of future interest rate increases on coverage ratios. The objective is to be able to quickly and easily get an understanding of potential exposure and risk.

Their first effort is to simply identify when loans will reprice or mature with indications of:


  • The loan balance that will reprice,
  • The current rate and spread,
  • The index on which the loan reprices, and
  • The current coverage ratios.


With this information in hand, clients are able to identify situations where the coverage is thin and will be significantly adversely affected by higher rates. They can also identify any concentration of repricing in future time periods — for example, do a lot of loans reprice in three years?

Once the repricing schedule is available, analytics can be applied to it to automate measuring the impact on future coverage ratios.

  • The current balance can be amortized down to the repricing date to better estimate the impact of higher rates on coverage.
  • Potential exposure from utilization of available lines can be measure.
  • Interest rate projections can be established, future loan payments can be recalculated, and stressed coverage ratios can be presented.
  • Projected coverage ratios that are below a user specified threshold can be identified for further analysis.


While all the information necessary to perform this analysis is resident in most core systems, the ability to create reports that present the information and perform the analytics is more difficult to achieve. Systems that easily provide this information to clients allow them to better measure this component of credit risk.

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Enterprise Risk Management

Enterprise Risk Management (ERM) has evolved over the years and taken on increase importance due to the current economic environment as well as increased regulatory attention. While there are many components to ERM probably the three major categories are Credit Risk, Interest Rate and Market Risk, and Operational Risk. The later is probably the hardest to get your arms around but there are systems that can help with this such as WolfPAC by Wolf & Company in Boston. For Interest Rate and Market Risk there are quite a number of systems that can help such as those offered by friends of ours at DCG Consulting in Newburyport, MA.

Probably the single largest risk category is Credit Risk, which is addressed by the Madison System. But, while credit risk may be the credit risk implications need to be evaluated along with any operational risk implications.

A well rounded ERM system will rely on systems such as the Madison System, and the others such as those mentioned above, to assist in the process of measuring the risk and the profit, as well as assisting in managing risk on a going forward basis.

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Stress Test Filtering


Financial Stress Test Filtering

Stress testing the commercial loan portfolio has been an important function for many years. Increasingly, we find clients are stress testing more granular subsets of the total portfolio. Here are some of the criteria we find clients using. See if any would make sense for you. The easier it is to select the desired sub group the more likely you are to conduct more granular analysis, and the less staff time is required to get the desired result.

Department and Broad Portfolio Types. These are very broad categories such as commercial real estate (CRE) loans, C&I loans, construction loans, asset based lending, etc. In many cases there is a lot of overlap between departments and portfolio types. Not only would the appropriate stress values differ, but the particular ratios that you many want to test will differ. For Example, you may want to stress LTV and DSCR for CRE loans but DSCR and loan interest rates for C&I.

Geographic Criteria. Different markets and geographic areas may have substantially different economic conditions, some may be strong while others quite weak. Geographic criteria would include region, state, market or city.

Collateral or Loan Type/Loan Category. Needless to say, different collateral and loan types exhibit quite different risk characteristics.

Loan Programs.  Loan programs may be directed at different customer groups and/or have different terms and structures that merit separate analysis.

Origination Period. Loans originated in periods when underwriting criteria were especially aggressive may exhibit heightened risk.

Participation Loans. Purchased participations were originated by another lender, so even though your organization also reviewed the underwriting of the loans, servicing will be by another lender and they will have more direct contact with borrowers and performance information. And Participations sold, while underwritten and serviced by your organization, may be larger implying worse consequences if they go bad but they may also have been underwritten against more rigorous criteria. Either way, the ability to look at participation loans separately from the rest of the portfolio is valuable.

Rate Reset Dates and Indexes. The particular characteristics of floating rate loans give rise to risks associated with higher loan payments if interest rates increase. The ability to easily identify situations where variable rate loans may reprice upward and evaluate the resulting potential DSCR is also valuable.

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Stress Testing Loan Covenants

Stress Testing Loan Covenants

Stress Testing Loan CovenantsOverview: It is important to be able to stress test many variables, applying various techniques to stress testing the portfolio. Stress testing loan covenants is one such approach that many find useful.

For a long time the Madison System has enabled clients to identify loans that violate loan covenants, or come close to violating the covenants. We have recently added a new feature to one such report – the ability to stress LTV and DSCR covenants by changing the value of collateral or businesses supporting loans to stress LTV, and by changing the income of collateral or businesses to stress DSCR (Debt Service Coverage Ratio).

In this report users may determine the amount of the stress to either collateral value or income, or both, and the Madison System will then recalculate the LTV and DSCR for each loan to display those that violate the covenants which are highlighted in red, or those that come within 15% of violating the covenants which are highlighted in yellow. The report can be set to display only violations, only violations and near violations, or all loans.