The financial crisis brought to light the shortcomings of existing risk measurement and modelling methods in financial institutions, and forced the need to seek new approaches to risk management in financial activities – banking activities in particular.

The financial crisis that began in the US at the end of 2007 completely changed the paradigm of managing financial institutions. The approach to risk measurement, budgeting, and financing of operations changed; in general, this applies to every important aspect of running a banking business. Earlier, it was thought that most major risk elements could be described and forecasted using econometric models, and that models that worked in one country would work in every other one. By starting to build the company’s budget for the upcoming year, managers would collect historical data in every possible cross-section of the company’s activity, and then, assuming that the stability of the market situation wouldn’t change, extrapolated historical trends into the future, sometimes correcting them using previously known one-off events that may occur.


Unexpected changes on the market

The forecast was: sales, cost or profit. Making a projection for several years enabled estimation of the goodwill of a company using the DCF method. Currently, this is still one of the basic ways of valuing a company. However, it turns out that in view of the huge difficulties with reliable planning of future results, this approach often proves useless. Unexpected changes on the market, exchange rate fluctuations, never-before-seen amplitudes of changes in stock and bond prices, the appearing and unexpectedly disappearing liquidity of markets – all of these make predicting the future extremely difficult or downright impossible. The projects of companies assuming that they’ll achieve profitability in the sixth or seventh year of operations are becoming a thing of the past, because no one believes that such long-range projections are reliable. In practice, most analysts are beginning to limit their analyses to a two- or three-year period.


Historical data and risk estimation

Historical data on the basis of which risk is estimated are often completely useless, as the market environment and business models have changed fundamentally. The collapse of the major investment bank Lehman Brothers showed that the theory of the existence of banks that are “too big to fail” is fundamentally untrue. Instead, it uncovered another truth – that a poorly managed, large bank or banking sector poses a huge risk to the economic security and stability of the entire country. The Eurozone crisis in 2010 proved to everyone that even developed countries are at risk of bankruptcy if they don’t have budgetary discipline and live on credit.


Stages of thinking about economics and the economy

An analysis of the research of the world’s leading economists shows various stages in thinking about economics and the economy. At first, there was an attempt to describe all processes using mathematical formulas, econometric models, applying economics as an exceptionally exact science. However, in the last twenty years there have been many papers that prove the behavioural basis of investment decisions, namely, they present a psychological rather than mathematical approach. Some of them have received great recognition, and the achievements of such outstanding behavioural economists as Herbert Simon and Daniel Kahneman were awarded the Nobel Prize in Economics (Simon for creating a theory about the irrational tendency of people to being satisfied, and not to increasing their utility, and Kahneman for research into decision making under the influence of indecision).


The uncertain future of the world of finance

After the recent crisis, the world of finance and banking feels lost and probably few people know which direction to go to properly manage risk, in particular operational risk. What if it’s impossible to define and assess the scale of this risk? Thus far, the focus has been on rational aspects of risk: investments, credit and political. At present, the analysis must also include the risk of natural forces (for example, the unexpected impact of Iceland’s Eyjafjallajökull volcano eruption on airlines, or the earthquake in Japan in 1995 on the bankruptcy of one of the oldest banks in Great Britain – Barings Bank), or man-made ecological disasters that may threaten entire economies (Chernobyl, the oil spill from a BP platform in the Gulf of Mexico).


Fast pace and dynamics of change

Account should also be taken of the lightning pace of change, as a result of which the usefulness of all historical data for analysing future phenomena becomes very limited. One should also take into account people’s fear and euphoria, irrational anxiety and unreasonable delight over some assets, leading to making investment decisions that in the long run may prove completely pointless. We’re also dealing with growing terrorism – it’s beginning to exert a significant impact on the global economy like never before.

Such a vast range of variables makes it reasonable to ask whether it’s even possible to quantify the risk of banking operations, and even more so manage financial institutions based on existing quantitative methods.