I like to build models, which help me to understand a topic in an abstract way, as simple as possible but a way that captures the essentials from the chaos.
I was trying to build a model, which shows how the risk management system works in the banking organizations. It sounds too complicated to finish in a couple of days. While, I was determined to find out something towards this goal.
I do find out that the major classes of risk for a bank and the key risks are credit risk, market risk and operational risk. I also understand the core technology for a risk management includes
a good data management system (almost a data warehouse), which collect and store the data
a computational system to analyse the data and performance
a reporting system for generating reports or alerts for risk managers
The current vendors are formed from three different groups: the specialists who used to work for bank and now having their team to offer the software back to the bank; the giant enterprise application vendors who expand their offerings to risk management as clients request and the BI specialists who could take advantages from their data analysis experience.
It seems all make sense. Top 100 firms are listed in the Chartis Report 2007. Datamonitor predicts retail bank spending on risk management technology will reach $1.76 billion by 2012. So, great vendors, excellent systems and lot of dollars. Are the bank protected? Are they safe from all the risks?
JEROME Kerviel made international headlines earlier this year when it was revealed he had racked up losses of $US7.2 billion ($7.7 billion) at French bank Societe Generale, and he was able to get away with this because he found a way to work around the bank's risk management systems.
Is the risk system that fragile to break?
Criminal investigations have been launched against 17 companies in the fallout of the subprime mortgage collapse, the FBI disclosed late Tuesday.
It seems beyond the control of a risk system.
Alan Greenspan said this week : We will never have a perfect model of risk.
Risk management systems – and the models at their core – were supposed to guard against outsized losses. How did we go so wrong? The essential problem is that our models – both risk models and econometric models – as complex as they have become, are still too simple to capture the full array of governing variables that drive global economic reality.
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This, to me, is the large missing “explanatory variable” in both risk-management and macroeconometric models. Current practice is to introduce notions of “animal spirits”, as John Maynard Keynes put it, through “add factors”
"Animal spirits." Greedy. It is as simple as it is, which hit us all.