Loan Modifications and Troubled Debt Restructuring A New Set of Challenges with the Allowance for Loan and Lease Losses (ALLL) by Geoffrey A Oliver, CPA, CMB While we are in a credit cycle that is challenging the financial services industry in a number of new and unique ways, questions are also being raised by Audit Committees, external auditors and bank examiners about the Allowance for Loan and Lease Losses (ALLL). Such questions involve critiquing the ALLL methodology for all loan types, assumptions used and the credit process ratings assigned to individual commercial loans. Given the uncertain economic future, the depth of the current recession and the untested performance of loans in the current or near future, auditors and examiners are being critical about the ALLL calculations being made by lenders. Lenders should assume that any previous methodology and assumptions used are not acceptable in today s market. Allowance amounts related to current performing loans are being analyzed more closely than ever as to what the probability of default will be. The traditional allowance percentages or the known loss concepts are being challenged by the lenders auditors and examiners. Known losses are being extended out, meaning that anticipated losses 12 to 24 months from now are being considered as known by some auditors, especially if the lender does not have data to prove otherwise. Loans in a portfolio are being analyzed by lender/servicers and their auditors/examiners in an aggregate or box car approach that treats all loans as similar despite major differences in the underlying characteristics of the borrowers, geographies, real estate values, average versus specific equity levels, cash reserves, employment, etc. Hilltop Advisors has been working with lenders to understand the data and analyze the loans at a much more discrete level. The box car approach will result in a train load of losses. Hilltop Advisors has developed a process methodology that utilizes various analytical software applications to produce a disciplined analysis of a loan portfolio s credit exposure and the quantified results to various alternatives. The methodology and analytics will result in a more specific, objective determination of overall loss exposure and triage the risk. The more detailed analysis of the loans, with current performance data (real estate values, borrower financial strength indices, FICOs, cash reserves and more accurate employment and income data) will help differentiate the portfolio of underlying borrowers. With better analysis and resulting actionable steps, the lender/servicer can tailor their loss mitigation activities to maximize the opportunities to keep borrowers in their homes and minimize overall losses. The methodology is likely to reduce the number of performing loans that auditors suspect as possible near term delinquencies given the better information about the borrowers. This comprehensive approach is more likely to identify the depth of issues and when the bottom has been reached. Poorly performing components of the portfolio may result in more severe loss estimates but such poor performance and the calculated losses would not be spread across all loans. Hilltop Advisors methodology integrates the credit loss models, the operational actions for loss mitigation and the accounting results into an actionable approach to addressing the current credit crisis. The Fact Based Loan Portfolio Analysis When applying the analysis of borrower data and updating such with current borrower and economic/real estate data, our approach to dissecting the loan portfolio (whether residential or commercial) reveals how a lender can approach the ALLL by segments of its portfolio. However, we
have also found that Hilltop Advisors approach to calculating the ALLL, using better loan level data about the underlying borrowers and the properties, will also provide solutions to some of the basic challenges that loan servicers are dealing with such as: - Not being able to contact borrowers - Negotiations for modifications, refis, or short sales are ineffective due to missing data - Getting investors/security holders to agree on restructuring portfolios has been unsuccessful. The loan and property data and comprehensive analytics necessary to demonstrate alternatives for the appropriate course of action and probable loss to investors/security holders has been severely limited. - Different default servicing approaches are not applied or justified. In many cases, the investor specified servicing methods are used regardless of success - Accounting results are not known or understood when the servicer is modifying/restructuring the loan - The impact of accounting for a troubled debt restructuring is often unknown by servicers - Identifying non-owner occupied loans. Borrowers who committed loan fraud and others who have attempted to game the system clearly the lender should not be trying to modify these loans Most lenders know what data would be helpful, the issue is obtaining such data easily, having it near real time and integrating such data into the model calculations. Such models need to provide the economic financial impact, the accounting result, the prioritized operational steps needed, and an overall assessment of the loan portfolio s status. Further, with many of the new loan types (such as payment option arms, subprime, stated income and/or stated asset loans), the historical loss patterns do not exist, so a continual update of such analysis is critical. Data analysis tools and public databases have made information about borrowers and real estate more available than ever a fact based loan portfolio analysis takes advantage of such available tools and information. Having the Right Data, Models, Personnel and Non-performing Loan Experience In this new economic environment, it is important to understand the position that the external audit firms and/or bank examiners now face. With the first real credit challenge in almost 20 years, risk levels relating to the financial statements have been heightened. Auditors and regulators respond to higher risk levels by being very conservative, usually ignoring best case scenarios and absent critical analysis and data, often using worst case scenarios. Applying this to the ALLL, auditors and examiners will look for much more data detail, loan level performance analysis, and third party data to support the calculations. Most financial services companies are ill prepared for this new perspective that their auditors and examiners will have. Given that most default/loss mitigation personnel have less than 15 years of experience, most will have never experienced a credit loss cycle (the last one being in the early 90 s). Every cycle has its own unique twist but many aspects are similar between cycles. The portfolio analysis focuses on the
basics of the borrower s ability and inclination to pay and the value of any collateral. Many lenders are disenchanted with the FICO score as a reliable indicator of a borrower willingness and/or ability to pay their loan payments. The underlying performance of the loan cannot be limited to one factor like FICO score. Thus, the portfolio analysis considers a number of factors, but are not limited to: - Borrower s current ability and/or willingness to pay: o Current employment o Likelihood of continued employment o Amount of compensation/disposable income real documented income o Attitude toward lender (whether they feel like the lender took advantage of them) o Treatment by servicer o Cash reserves or liquid investments to use in case of temporary distress o Is the borrower in too much debt mortgage, second, credit card balances, auto loans, etc? o Current FICO score o Other debt in default o Other investments, other properties owned - Value of the underlying collateral to support the current loan o Current value of property (CLTV) o Depreciation of property value since mortgaged/bought (borrower s equity) o Cross collaterized debt, if any o Likely continued value declines o Local or regional economic trends impact on values o Possible value recovery timeframes Lenders must utilize data sources that are available for all of the above information in public and fee accessed databases and obtaining new information from the borrowers. While some of these factors are the same data points that the lender may have used to approve the loan, the update of factors reflecting the current economic environment and the documented ability for the borrower to make a certain amount of payments will assist the lender with a different perspective of the loan. It is likely that the borrower s current ability to pay a certain monthly cash amount will not support the current loan amount. Only the most realistic assessment of the borrower s ability to pay will result in a successful restructuring and a future performing loan that is more likely than not to re-default. The loan modifications or restructurings to date have tried to modify term and rate. Unfortunately the history for this type of loan modification has shown poor re-default statistics up to 60%. In many cases, the loan
has increased from the original principal due to negative amortization and capitalized fees or other incurred costs. In many cases, the fact based analytics indicate that the borrower s ability to pay even at a reduced rate or increased term is still not achievable. One solution that lenders and the Government programs have not considered is a form of a long term equity share between the borrower, the lender, the security holder (if present) and the government. Of course the property value has to recover over a 10 or 15 year period to support this concept but historical real estate appreciation rates have generally supported such. The equity share could take several forms but would include reducing the loan principal on the primary loan and creating a non-interest bearing balloon loan payable upon the latter of a sale or the extended period (10-15 years). This solution would potentially include some payment of interest to security holders by a government subsidy which might alleviate the major securitization hurdles for restructuring loans. Further, the equity share percentage would be established based on the amount of principal concession and could include a first out for the equity share partners. Key Ingredients to the ALLL Calculations and Prioritizing Default Servicing Activities The loan level analysis of any portfolio is needed to be able to break away from the box car approach of assessing borrowers credit and ability to pay. Updated economic and property value data and indications of the borrowers ability/willingness to pay is critical to supporting the loan portfolio analysis. A data tool to assemble the disparate pieces of data about the borrower and the property is essential to facilitating actionable decisions. Experienced personnel need to use the data, the analytical tools and manage the inputs/assumptions to the models. The resulting models can then dictate default servicing activities, calculations of the allowance for loan and lease losses and identifying alternatives to troubled debt restructuring accounting where possible. As mentioned above, the same analytics and data inputs can and should be used to - analyze loan alternatives such as modification, restructuring, refis, short sales or foreclosure - prioritize which borrowers, both currently paying and delinquent, will result in successful financial restructuring and not default - reduce the number and cost of delinquent calling programs and streamline default servicing. These changes can lower servicing costs on many loans with better prioritization and results oriented management. (A 10-15% cost reduction is very possible if the results can convince the investors that their interests are being considered with these alternative servicing processes.) - understand the financial statement impact of offering alternatives at the loan level (accounting for any troubled debt restructurings and recording losses if any on restructuring) - track financial results and forecasts by more discrete components of the loan portfolio There are a number of analytical tools or databases available in the market that can: - provide valuation/cashflow analysis, - calculate ALLL for residential or commercial loan portfolios,
- provide current real estate values, - provide current FICO scores, - provide other economic factors by geography, - provide estimated income levels by job type and geography, - provide wealth/investment index levels by zip code, - provide spending per capita by zip code, None of these analytical models and/or databases integrate all of the components into a comprehensive borrower and property picture that provides an indicator of the ability and willingness to pay and the likelihood of recovery upon default. Thus to be effective, the lender/servicer must either have experienced personnel or hire the right advisors who have the experience to assemble the analytics, analyze the results and turn such into actionable steps to reduce the potential for losses within the lender s portfolios. Auditors and examiners may look to third parties hired to do such analysis as independent, objective and detached (no financial impact to them as a result of the analytics results) and welcome their perspective. The lender with the best analytics is nothing more than a company with excellent spreadsheet capabilities, unless the tools are used by the right professionals. Background of Geoffrey A. Oliver, CPA, CMB and Hilltop Advisors, LLC Jeff Oliver is Chief Executive Officer and Managing Partner of Hilltop Advisors, LLC. Hilltop Advisors, LLC is a boutique consulting and accounting advisory firm that is exclusively focused on the financial services and real estate industries. Hilltop Advisors specialty is focusing on all aspects of the lending, loan servicing and mortgage/asset backed securities aspects of the industry. Our Partners average 30 year careers with extensive working relationships with the top lenders, servicers, GSEs, regulators, and other industry stakeholders.