Commercial banks have experienced a recent period of robust earnings. These gains are the result of three factors: declining loan losses, increased operating efficiencies and a favorable interest rate environment. There are indications that income gains may be slowing, however. Profits are being squeezed because of intense competition for new business and declining loan spreads. In this environment, bank managers continue to explore new profit opportunities.
One area often overlooked in the effort to boost profitability is the bank's existing loan portfolio. Rather than look for new marketing opportunities, bankers should take Shakespeare's advice and look "not in our stars, but in ourselves." Modern portfolio theory (MPT) and new tools for analyzing risk and return offer opportunities for bankers to improve profitability without incurring additional risks or costs.
Portfolio management is not a new concept in finance. Mutual fund managers and investment advisors have used it for decades, while commercial bankers have been slower to embrace sophisticated portfolio management techniques.
Quantitative portfolio theory emanated from academic research begun in the 1950s that focused on rates of return in the stock market. Using quantitative models and high speed computers, academics from Harry Markowitz to James Tobin to William Sharpe tracked stock prices and their covariances over time. The research of these and other academics culminated in what we now call MPT.
applying mpt to banks
Using volatility of return as a surrogate for risk, these authors launched an assault on conventional investment thinking. The paradigm they constructed focused on expected value (the "return") and standard deviation or statistical variance (the "risk"). They plotted risk and return along two axes and graphically showed how an artful portfolio manager could construct an efficient frontier or optimal portfolio that minimized risk for each level of desired return.
The culmination of nearly two decades of academic work on portfolio theory was the Capital Asset Pricing Model or CAPM. The CAPM included the concept of Beta-the degree to which a stock's volatility is linked to the overall stock market-now used routinely in corporate finance as well as on Wall Street. The ValueLine Investment Survey, for example, generates a beta for each stock it follows.
Although intuitively intriguing, portfolio theory has been difficult to apply to banking. Banking assets consist of loans, which are not as uniform or measurable as stocks. Furthermore, unlike securities, loans prepay, are restructured and have fluctuating payment streams caused by variable interest rates.
In the past decade, analysts and academics have made some progress in applying portfolio theory to banking. Large banks are beginning to hire or establish portfolio management units to oversee bank loans on an aggregate basis. The San Francisco-based consulting firm, KMV, was one of the first firms to attempt to quantify loan risk by using portfolio theory. KMV's model measures an expected default frequency, or EDF, which can be calculated for most publicly traded and many privately owned firms. Although the theory is slow going to the layman, banks are warming now to KMV, particularly in the syndication desks of money center and foreign banks.
Recently, a bank and vendor group led by J.P. Morgan unveiled CreditMetrics, a mechanism for calculating credit value-at-risk. The group expects the CreditMetrics methodology to become the industry standard. CreditMetrics tackles one of the last resistance points to portfolio theory in banking -the fact that loan losses are not evenly (in statistical terms, normally) distributed. The volatility of stock prices conforms reasonably well to a normal distribution; default behavior for loans does not. CreditMetrics provides a mechanism to assess value-at-risk due to credit in a manner that facilitates greater use of portfolio management techniques in banking.
Loans constitute the primary earning asset at commercial banks. Loans account for nearly three quarters of an average bank's earnings and about two-thirds of the balance sheet. The remainder of the balance sheet is made up of non-earning assets (cash, fixed assets, etc.) and investment securities. Portfolio management techniques have been applied to investment securities portfolios for some time.
Bank loans fall into four categories - real estate, commercial, consumer and other. Real estate loans include construction, residential, commercial real estate and land loans. Commercial loans include commercial and industrial, agricultural, loans to banks and bankers acceptances. Consumer loans include installment credit, personal loans, credit cards, auto loans, etc. Most of these categories come directly from the regulatory call report definitions. The fourth category includes all other loans, such as loans to foreign governments, and political subdivisions, lease financing, and other items.
For portfolio management purposes, there are three ways to look at these loan types: in terms of their distribution or volume, by their riskiness and profitability or return.
study segments, distribution
A loan portfolio management system should investigate each of the above segments in a variety of ways, including by loan type; borrower; borrower's location; collateral type; location of collateral; loan maturity date; risk rating; industry segment or SIC; loan size; bank branch or division; loan officer; loan interest rate; country of domicile; currency
Understanding distribution of loan balances is extremely helpful in setting and managing exposure limits and controlling concentrations. A comprehensive concentrations policy is essential for smooth bank operations. Bank management, including the board of directors, should be interested in how assets are distributed in terms of geographical clustering (particularly for CRA purposes), for instance, or by industry concentrations, collateral or risk rating.
In addition, stratification into sub-segments is useful for marketing purposes. Careful examination of a loan portfolio's distribution can reveal cross-sell opportunities or previously undetected relationships. Knowing what types of loans are clustered in which offices, for example, is useful in determining future branching and branch staffing needs.
In a similar manner, the above sub-segments can be applied to risk and return. This is the heart of successful portfolio management and facilitates the application of MPT. Most banks today use a numerical risk grading system to estimate the repayment capacity of their borrowers. These systems are primarily subjective in nature, although in recent years banks have expended considerable resources in attempting to quantify their risk grading methods. Much of the work has been done in credit scoring and market-based models by firms such as KMV. As a result, risk grading is becoming more mathematical.
Dissecting a loan portfolio in terms of profitability is equally useful. To do this a bank must first have devised an internal transfer pricing system that fully values the risk adjusted return and cost of each loan. Some banks use a risk-adjusted return on capital (RAROC) model for this purpose. Whether they do or not, the essential point is that each borrowing relationship must have a specific yield assigned to it that not only reflects the revenue generated from interest and fees but also includes the costs of making the loan, an adjustment for its risk grade and an allocation of capital for expected losses.
Profitability can be viewed along the same 14 sub-segments introduced earlier, with the goal of arriving at a risk adjusted return on the overall loan portfolio. Using the above paradigm, one would then want to investigate returns within individual sub-segments. As an example, one might question how the profitability of one branch or officer compares with another, or whether one industry is more profitable than another. By examining these relationships in detail, a portfolio manager's attention is focused on opportunities to enhance earnings by reallocating resources among market segments or by improving the performance of specific business units.
MPT brings the two concepts of risk and return together in the disarmingly simple concept of the efficient frontier. The chart below is created by mapping the return vs. the risk rating of a series of assets. (see Figure 1).
Under-performing assets are clearly identified as those below the line. The vertical line in the chart indicates that the bank is not willing to accept any loans that are below 6 in risk grade. Even more sophisticated portfolio management techniques can be applied to most bank portfolios, including covariance analysis, stochastic dominance, mean-variance analysis and utility theory.
Enhancing Bank Profitability
Portfolio management techniques can increase profitability in several ways:
n Identify and manage concentrations. By uncovering concentrations of credit within an organization, active portfolio management can anticipate potential non-diversified areas of risk. This would have been useful for many institutions in the 1980s that haphazardly invested in commercial real estate or LBOs without knowing the full extent of their exposures. The portfolio process also helps in setting statistically valid limits and managing limit excesses.
n Isolate and remove outliers. Portfolio management techniques result in the construction of an efficient frontier. Assets or groups of assets that are not on that frontier are considered under-performers or outliers. By identifying and either removing or rehabilitating outliers, the portfolio manager can realize very quick earnings gains.
n Exploit negative correlation. Once concentrations are identified, portfolio management can facilitate improved earnings by taking advantage of individual assets or asset groupings that are negatively correlated. One industry, for example, may behave counter-cyclical to another. Putting the two industries together in a portfolio actually reduces portfolio risk and therefore improves profitability at that risk level.
n Increase cross-sell opportunities. Portfolio management is based on data base management. An analysis of how loans are distributed can uncover opportunities to cross-sell products based on borrower demographics, common ownership or profitability.
n Proactively manage the balance sheet. Improving profitability is not only reserved to the numerator of the ROA equation. Portfolio management also attacks the denominator, which is nothing more that average assets. Portfolio management techniques allow the manager to identify and shed assets in such a way as to enhance portfolio return. This facilitates the use of credit derivatives, asset sales, securitizations, syndications and the like. Alternatively, in times of desired growth, portfolio management techniques identify which areas are truly profit-enhancing.
n Promote profitable loan growth. By understanding which combination of assets reduces portfolio risk, an active portfolio management system can increase loan production. Loans that are turned down purely for pricing reasons may have more appeal when shown to be correlated negatively with other loans. The overall portfolio risk adjusted return may increase although the individual loans appeared unacceptable on a standalone basis.
n Enable goal setting and planning. Portfolio management is a tool that allows complete control of a group of loans in a manner that is forward looking and proactive. The portfolio manager knows the precise risk adjusted return of each asset in the portfolio and how that return relates to other assets within other industries at other locations in that portfolio. Having that information allows the manager to construct clear and measurable performance goals such as return on portfolio, aggregate weighted risk grade of the portfolio and total assets. Managing to goals is a proven method of improving performance.
n Reduce costs/ eliminate redundancies. Portfolio management can stratify loans by size and profitability. The result may show that loans below a certain level cannot be made profitably using traditional techniques and will require less intensive marketing or new "productive" methods such as credit scoring. The savings through organizational changes can be substantial.
Goading from Regulators
Banking regulators are beginning to take an interest in loan portfolio management. On March 11, 1997, the Office of the Comptroller of the Currency (OCC) issued Advisory Letter 97-3 reminding bankers that even in these good times it is imperative that they remain focused on credit and portfolio management issues. The Advisory Letter followed a speech given by Comptroller Eugene Ludwig on December 10, 1996, wherein he voiced concern about evidence of an easing in underwriting standards.
The Advisory Letter asked that banks continue to be vigilant in tracking individual loans and also begin viewing risk management in terms of a portfolio approach. Only the largest money center banks currently do this to any extent. According to the OCC, the essential elements of a portfolio risk management system are: assessing the credit culture of the institution: setting portfolio objectives and risk tolerance limits: portfolio MIS: portfolio segmentation and risk diversification objectives: adequate analysis of loans originated by other lenders: setting aggregate policy and underwriting exception systems: subjecting portfolios to stress tests: maintaining independent controls: and analyzing portfolio risk/reward trade-off.
The Comptroller is looking beyond individual loan grading by suggesting that banks embrace an effective portfolio credit risk management process. "Such a process," he states, "should enable bank management to identify, measure, monitor, and control loan portfolio credit risk."
A portfolio management system entails the analysis and synthesis of large amounts of data. Access to data, however, is becoming a double-edged sword. Managers have more data at their fingertips today than at anytime in history. Decision makers are in danger of becoming numbed by this sea of data, with little time to digest it.
Although banks have reliable MIS systems that can generate substantial amounts of loan information, most bankers do not receive this information in a user-friendly, consolidated or real time manner. Rather, analysts produce reports, sub-reports and spreadsheets that may not even share the same data source. What is needed is a method to present data to the end- user-in this case the portfolio manager or the company board member-clearly and concisely.
Computer scientists have come up with a partial answer to the data overload problem - data visualization. By visualizing complex data sets, an analyst can understand relationships that become blurred in standard report packages. For example, the following table presents data on maturing loans at a hypothetical bank.
The information is valuable and can lead to other decisions. However, in tabular form, it is unexciting and drab; in 3-D graphical format, it comes to life. (see figure 2).
Data visualization techniques will soon become an important tool to assist portfolio managers who are, or soon will be, expected to monitor large amounts of data and arrive at meaningful decisions in a timely manner. This is not to suggest that loan portfolio management will become an arcade game. On the contrary, new data visualization and animation techniques are intended not to entertain the decision maker but to free up a decision maker's valuable time for more pressing projects.
Portfolio visualization may provide insights into heretofore unknown areas and hopefully will highlight relationships that were obscured in the past. For example, showing single family real estate loans on a grid or map might reveal pockets or patterns of non-performance. By inserting red flags in certain areas - CRA loans or past due loans, for example - might provide early warnings of potential problems. Color coding can reveal geographical trends in an intuitive manner, more the way the human brain works.
Another useful data visualization device is the use of "drill-down" screens. At each point in a display, the user is given the opportunity to expand to the next level of detail. For example, suppose an analyst is viewing all commercial loans and wishes to see loans over $500,000, or loans that are secured by real estate. The technology allows the analyst to double-click to see different levels of detail, then re-sort the data by other parameters, such as maturity date, past due status, loan grade or collateral type.
Loan portfolio management is an area of increasing focus for bankers and regulators alike. The transition to a successful portfolio management system can have a dramatic impact on a financial institution. It clearly can help risk assessment and risk management. But perhaps more importantly, by shuffling assets and maximizing risk-return relationships, managers should be able to improve the bank's earnings.
The transition will require new ways of looking at portfolio information. The new style of portfolio manager must move from reactive to proactive. To do that, he will need tools to observe, adjust or maximize the portfolio. An active portfolio manager with an accurate and clearly presented data base program can go a long way toward meeting the regulators' expectations in this area and hopefully improve profitability.
Carl Hyndman is a principal in the Los Angeles office of The Secura Group, a financial institutions consulting firm with headquarters in Washington, D.C. Prior to joining Secura, Mr. Hyndman was a vice president in commercial lending at Citibank and Wells Fargo.