The paper discusses a multi-stage stochastic programming approach to the strategic financial management of a multi-company financial conglomerate. The planning system creates a comprehensive strategy which simultaneously covers a number of future scenarios within a multi-period planning horizon. Multiple conflicting goals may be specified for the group level, company level or individual business area level, and the decision maker’s preferences are allowed to change over time to reflect changing operating conditions and trade-off relationships between the goals. Special features include, among other things, full market valuation throughout the model, integrated treatment of different types of risks, explicit modelling of various types of intra-group transactions and relationships, extensive structures to deal with distressed assets and the covering of losses within the group, as well as consideration of potential portfolio effects of a diversified group structure on the cost of funding.
Recent years have witnessed a trend towards financial services conglomerates consisting of deposit-taking institutions, finance companies, other credit institutions, investment companies, securities firms, real estate firms as well as life insurance and property–liability insurance companies. The group may also include industrial and commercial firms, frequently organized under a holding company.
The management of this type of a conglomerate is a difficult task under the present day conditions in which future operating environments can not be forecasted with any degree of accuracy. From a strategic planning point of view the difference between a `conglomerate’ and a single financial institution is, on the other hand, in many cases smaller than what one might initially think. The `conglomerate' may consist of, say, two domestic subsidiaries and one foreign subsidiary. As the decision about the number of individual firms in the group is often arbitrary you might equally well think of a single company. It is obvious that if the management board of the company does not take a stand on the composition of the firm’s business portfolios and the risks related to these portfolios, it may ruin the company. Unfortunately this has also been the case in numerous real-world situations as the banking crises and failed institutions and groups of institutions have demonstrated in a number of countries. Furthermore, the crises in the financial services industry appear to continue and the process of covering losses within the group, for instance, has therefore become an important management issue. The diversification effects on the funding side, in particular, also justify a group perspective. There has, however been a lack of appropriate tools for dealing with the complex issues involved.
The paper therefore discusses a dynamic multi-stage stochastic programming approach to the strategic financial management of a multi-company group. The system is used to create a comprehensive strategy which simultaneously covers a number of potential future scenarios within a multi-period planning horizon.
The general area of strategic asset and liability management or strategic financial risk management has received increased attention in financial institutions during the last few years. For extensive reviews of stochastic models, scenario generation procedures, recent advances in solution algorithms as well as practical applications in this area see Mulvey et al. (1997), Mulvey and Ziemba, 1995, Carino et al., 1994 and Bunn and Salo, 1993, and Langen (1989). For a discussion of earlier applications see, for instance, Kusy and Ziemba (1986) and Korhonen (1984, 1987). Previous studies typically deal with strategic asset and liability allocation decisions at the level of individual institutions such as banks, insurance companies and pension funds. The present model extends the analysis to the management of a multi-company group with a multitude of intra-group relationships.
The traditional way of managing financial institutions is often based on a single and rather vague view of the future. Even assuming that the management might by some miraculous intuitive process have transformed this view into a set of optimal decisions (and this is a rather bold assumption), the mere fact that these decisions are based on one single scenario means that the resulting strategy will differ from a strategy that prepares the institutions for a wide range of eventualities. Multiple scenarios require precautionary measures which would not be necessary if the future were assumed to be deterministic or reasonably predictable. The consequences of the failure to take notice of this trivial fact have been dramatic in the financial sector of a number of countries.
Forthcoming versions of the present model will include, among other things, modules covering insurance liabilities.
