Business Intelligence for Risk Management – Part II

Following on from Part I we look at some of the ways that BI can enable firms to evolve their risk management capabilities and in turn realise game changing results.

The discipline of risk management covers many areas, from analyzing a trading portfolio, understanding historical market trends, looking at logistical or operational risks or viewing credit exposure to trading partners. In trading organisations both market risk and credit risk require detailed analysis of the trading portfolio’s performance and current open positions. With large trading books this typically requires a lot of computation and aggregating of many positions in various ways. Furthermore, when considering what-if scenarios and use of simulations to predict a worse-case of a particular risk measure, many millions, or sometimes billions of computations and aggregations are required. Organisations often deploy specialist software to perform these calculations. Typically these solutions have pre-determined reports and perform large-scale calculations in batch processes as part of an end-of-day process. This of course means a long period of waiting for calculations to be completed and a very rigid set of results. If inputs are wrong or requirements change it can often be hours, or days before new results can be reported.

Another key requirement in risk management is in the use of time analysis. Time analysis includes the ability to predict what might happen in the future, or compare trends with historical data. In credit risk there are many time-based requirements, from looking at an exposure through time in a “walk forward” scenario, to viewing limit utilizations through time, or finally to viewing peak exposures in future months including future payables, physical deliveries and key dates for title transfer of cargoes for example. In market risk terms, time analysis is used in VaR reporting, and again when considering historical prices to determine future market scenarios. A major benefit of BI is the ability to perform time intelligence on data contained within a cube. Time dimensions can be used to perform advanced calculations and hence makes BI a particularly good fit for many risk management requirements.

Add to this the need for different perspectives on the data for different risk user communities. For example, Risk managers, credit analysts and senior executives need to consume risk data in different ways, with different levels of detail. A senior executive would want to see an overall view of the portfolio with visual highlighting of specific risks, big exceeds or largest exposures. A credit analyst will want a more ad hoc, drill through view to get into the weeds of the data. BI visualization tools like PowerBI and Tableau on top of the Cubes can provide the portfolio level visual outputs for senior executive consumption, whereas Excel pivots on the Cubes allow for ad hoc analysis and detailed drilldown.

As we have seen, BI, and specifically cubes, are designed to perform data aggregation quickly and on demand. Due to this continued progression in technology, the need of pre-determination and batch-based calculations can be replaced with high-performance, on-demand aggregation and holistic reporting. For risk management, it is clear that BI is a perfect fit. It enables users to determine their risk analysis requirements on the fly and see the results immediately. This means a much more flexible and proactive approach to risk management can be achieved. In today’s volatile, cost sensitive trading environment there is no longer room for accepting the status quo when it comes to technology and services. Firms are demanding better solutions which enable them to gain competitive advantage in every aspect of what they do.

BI is the way forward.