Banks have to manage a variety of trading risks and over the past 20 years a number of the tools have been developed to better quantify these risks and their potential impact on the bank. Of these the most widely used is the “value-at-risk” approach, commonly referred to as VaR and sometimes as VAR. For the sake of clarity we will use VAR to denote the actual value at risk and VaR the technique itself in this text. VaR has the following features:

VaR uses historic data to determine past price volatility and relationships between variables.
It depends to a large extent on historic correlations between instruments being maintained.
VAR is usually quoted as an absolute dollar amount.
VaR requires that the time frame over which the VAR estimate is made be specified. This  time frame is often referred to as the holding period.
VAR is defined at a specific confidence level expressed in terms of probabilities.
VAR is also highly model dependent and two banks estimating VAR for an identical portfolio of financial assets will almost always end up with different estimates even though the same holding period and confidence level have been specified.

This is the risk radar that investors switch off when they buy a company based on perceived reputation. Reputation is used instead as the proxy for risk management. Thus, many investors went into Enron, Worldcom or Equitable Life because they were regarded as good pedigree companies. Long-Term Capital Management, adorned with a Nobel prize-winner on board, had a total market exposure estimated at $1250 billion against its capital of $800 million.
Many people just want rapid profit, but they do not have a clue about real risk management. Setting an investment project goal with a risk limit is essential; it is not an optional extra. A predefined project by RAMP methodology has goals, expected performance and variance reporting. This puts adverse CEO spotting back on the project agenda.
Finding the company on our corporate AEW radar can warn us that the company is about to “blow”. This organic-based system uses both figures and mathematical techniques, but is more about the manner in which human beings operate. The forensic evidence can be tracked down in audit trails. There are scents given off by CEO sharks associated by red flags alarm signals for indicating weak banks.
There are essential tools to identify weak banks using early warning techniques. This subjects the supervisor’s data on the bank to a stress testing process, of the bank’s expenses, asset quality of portfolio and their funding. Then we can derive a better risk-discounted picture of the earnings, capital and solvency. This is followed by qualitative (note not quantitative) modelling:
Qualitative data
Management/board of directors have oversight administration deficiencies; the oversight committee may not be empowered, or it is too chummy with the CEO.
Risk management has deficiencies in resourcing, empowerment and skills.
Strategic mistakes have been made by the board into the market.
Quantitative data
Performance-related rise in declared profits, asset value, sales.
Aggressive growth and expansion strategies.
Sudden and major deterioration in earnings.
Basel II recognises that such operational risk weaknesses cause big problems for the investors. Its AEW10 system also focuses on warning signs in:
Board management quality.
Effectiveness of policies, procedures and planning.
Execution of risk management controls and audits.
Quality of MIS systems and reporting processes.