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March 21, 2010
Transformation of Risk IT Function
IT traditionally has been supporting Risk function by providing framework for Calculation, reporting, enablement of workflow, analytic framework and Risk adjusted performance parameters. However due to enterprise data challenge and regulatory deadline pressures IT function has always been in “Catch up” mode with the changing landscape of Risk. After recent financial meltdown when the industry is taking a step back to relook and revalidate the whole risk arena, how IT solutions and products supporting Risk function would change to face the paradigm shift and challenges ahead? The IT function is expected to evolve from support function to provide more predictive model and patterns to enable more forward looking and proactive support to Risk function – a transition that would be eminent for the eventual survival of the Business.
How Predictive is Risk now ?
Perhaps the biggest hurdle a risk officer has to thwart and strategize is to overcome the randomness associated with the financial business. Risk IT department is also facing the insurmountable pressure to consolidate, rationalize and integrate all their systems and platforms but behind all these transitional changes the fundamental question that would crop up - can we have a Risk solution that can help Predict disaster before it strikes?
Can IT solution provide a predictive framework so that one can get an indication of Tsunami ahead of time?
Can we create an analytical platform which would enable detection and recognition of patterns that can give early warnings of risk events that might occur in future so that early precautions can be taken? It is like a Seismic detection system which aims to give early warnings. There are Business scenarios and indicators that can help design a predictive system.
The BCBS recommends scenarios which can definitely act as early-warning indicators, some of them are as follows:
• Rapid asset growth, especially when funded with potentially volatile liabilities.
• Growing concentrations in assets or liabilities.
• Increases in currency mismatches.
• Stock price declines or rising debt costs.
• Widening debt or credit-default-swap spreads.
• Increasing redemptions of CDs before maturity.
• Difficulty accessing longer-term funding.
• Difficulty placing short-term liabilities (e.g., commercial paper).
If we relook at the past and focus on failures of financial institutions (e.g. LTCM), the then macro and micro scenarios can potential get added to the list above. Monitoring of Intraday Liquidity and Collateral Management can also give some potential patterns as well. Analysis of market behavior can lead to detection of unusual behavior like “Herding” , “Domino effect” etc.
Eventually collection and assimilation of all these data can lead to design and build of expert system which would continuously enhance the Risk knowledge base . With the aid of this Knowledge base assessment of the current situations would be possible and can lead to issue of warnings and alerts using sophisticated workflow system to senior leadership and Board members for appropriate and timely actions. Though past is just an indication of future but such knowledge base can still provide good indications of what might come in the future. The predictive model hence would be more diagnostic by nature though eventually it can suggest remedial and self healing steps as well.
What are the impediments?
Data Challenge
Enterprise wide right data definition and accuracy continues to haunt large financial institutions. Success of such expert system and knowledge base driven approach can only be successful if right data is available at right time.
Analytic & Reporting
Complex Analytic routines would demand high system design skills. Right choice of technology stack would also be key. From my past experience of BASEL 2 Implementation for a large European Bank, I have seen 500+ reports were written by a vendor but simple report like in a single day what is the exposure the bank has globally across all asset classes for each market was missing , one needs to manually combine 4 -6 reports to get a single view like that. Later the vendor was awarded the contract of writing such “Simple” reports.
Computing power and right Infrastructure
Such expert system would require high end computing power and right Infrastructure support to make it successful.
Right understanding of the Business
Right understanding of the Business is key to develop a solution that caters the need of the Business. Poor understanding of Business and its needs results into poor functional specification and that is the single biggest source of trouble for all software solutions.
Understanding of each of the scenario, its business significance and relevance would be key to generate the right knowledge base and its applicability to the current situation.
Road Ahead
Regulators globally have already come up with scenario based guidelines so such expert system and solution is no more wishful thinking but going to be real happening in future. However one word of caution it has been seen in the past that all sweeping changes in regulations have only enhanced the revenue of technology and consulting firms in manifold but the predicament of the financial industry and eventually its cascading impact to the miseries of the world economy continues.
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