Mitigating IT Risk for Financial Risk Analytics

Financial Risk Analytics has evolved beyond a secondary regulatory and cost-focused perspective, to become a core part of businesses. Today, Risk Analytics provides a competitive edge by enabling businesses to efficiently use capital and manage risk exposures with higher confidence to make better informed and timelier business decisions. Hence CEOs increasingly rely on their CFOs and their Chief Risk Officers (CROs) for strategic advice and active risk management.

Risk Analytics using simulation-based tools provides a powerful, flexible and accurate way of assessing credit, market and liquidity risks. Simulation techniques can effectively handle a wide range of market conditions, complex portfolios comprised of a variety of instruments including derivatives that involve collateral, margins and counter-party agreements.

Many firms view IT infrastructure investments for Risk Analytics as a competitive differentiator critical to promoting enterprise-wide sharing of risk information with holistic risk governance. But IT is also a source of risk - lack of adequate security, performance and disaster recovery must be mitigated.

IBM Algorithmics provides sophisticated analyses of different economic scenarios that help firms better quantify risk for a single department or firm-wide across a common set of market scenarios. With Algorithmics, firms have a better handle on their financial exposures, market and credit risks before they finalize transactions. Assessing intraday risks with greater confidence can help boost a firm’s profitability and growth.

The Mark-to-Future (MtF) methodology in IBM Algorithmics enables firms to fully simulate portfolio values over all instrument types across all scenarios and time steps to quantify risks with considerable precision. But with ever larger portfolios and scenarios, exponential growth of data, and more stringent regulations, MtF simulation requires a high-performance parallel computing infrastructure to eliminate performance bottlenecks in both batch and real-time calculations. But this further drives up IT risk due to manageability and complexity.

To get timely and trusted insights from Risk Analytics while minimizing IT risk and improving time-to-value, IBM is delivering an Application Ready Solution for Algorithmics. This integrated offering, anchored on a validated scalable high-performance clustered reference architecture, delivers the timely risk insights firms need to lower Tier 1 capital.

Firms should consider deploying this IBM Application Ready Solution for Algorithmics to achieve active and scalable risk management by distributing the computational demands of advanced risk analytics across a dynamic grid computing environment. With this Application Ready Solution, enterprises that deploy risk management can move from reactively measuring risk to actively managing risk based on timely insights drawn from more accurate analyses. This solution also lowers the total cost of ownership, improves time-to-value and mitigates IT deployment and management risks.