In the wake of widespread bank failures and losses in the early 1990s, internal risk management systems have emerged as a primary source of sustainable competitive advantage within the finance industry. Indeed, in the current environment of intense rivalry and deregulation, the survival of institutions and banks will be dictated by their respective abilities to achieve two crucial goals:
• Minimisation of the risk represented by income stream variability within investment portfolios
• Appropriate pricing of products within the maximum range set by competition and minimum return
required to profit over the long term in lieu of the statistical probability of loss.
Although these pursuits have historically represented the objectives of the funds management industry, they are relevant to any financial transaction or investment. In recognition of the fact that loans are a form of investment, banks have recently sought to flatten the cycle of losses by applying the more rigorous and systematic analytical techniques of funds management within the realms of risk-pricing transactions and constructing loan portfolios.
The primary objective of this paper is to review the basic theory of portfolio management and explore the manner in which these theories could be applied to the lending industry. To illustrate the practicalities of this endeavour through a case study, current initiatives to enhance credit and portfolio analytics at Queensland Industry Development Corporation (QIDC) are discussed in conjunction with a series of financial modelling examples. Specifically, the following broad topics are explored:
1. Theory of Financial Risk and Emergence of New Loan Risk Management Paradigms
2. Commercially Available Risk Management Options
3. Portfolio Rebalancing Alternatives and Industry Innovation
The research methodology consisted of interviews with Peter Germain, Head of Portfolio Monitoring at QIDC, and an extensive literature review. Due to limited volume of articles on this relatively new topic, it has been necessary in some instances to bridge theoretical gaps by providing illustrative examples of practices in the funds management industry where the theory of portfolio management is more firmly entrenched.
It was found that, generically, financial institutions subscribe to two types of models which differ primarily with regard to the origin of underlying data. External data-enabled models typically incorporate capital market or economic statistics on industry growth and volatility in portfolio optimisation models which, in turn, assist managers in setting diversification strategies and exposure limits by industry and region. Internal data-enabled models, based upon analysis of the historical loan book, tend to come in a wider array of forms such as models for credit scoring, borrower attribute correlation or calculation of loan provisions.
While external data-enabled models assist in setting universal portfolio objectives such as the desired mix of industries in the portfolio, internal data-enabled models are more useful in determining the relative creditworthiness of different borrowers. Thus, the two approaches are complementary. There are also a number of commercial risk management services and products which provide the option to wholly or partially outsource this function. A final element within the loan risk management equation relates to portfolio rebalancing alternatives. Industry innovation has resulted in a situation where exposures are increasingly being traded on secondary markets, priced against market indices, hedged with derivatives and rated by external agencies such as Standard & Poors or Moodys.