Chartis RiskTech Quadrant TM for Data Management and BI for Risk

Crartis Reseach recently published their Data Management and BI for Risk report.

The report covers the competitive landscape for data management and business intelligence systems for risk management. IBM  solution was recognized as a category leader.

IBM  is one of the world’s largest technology and software companies and its Risk Analytics business is part of its Business Analytics and  Optimization practice. IBM Risk Analytics comprises financial risk analytics from the acquisition of Algorithmics and GRC capability from its  acquisition of OpenPages. The practice has nearly 9,000 consultants, almost 400 researchers, and 9 dedicated analytics solution centers  all over the world.  The IBM Algo Integrated Risk Platform is a family of licensed supported products for data management and risk results visualization. The IBM Algo Integrated Risk Platform aims to help financial institutions address increasing regulatory requirements, enhance risk-informed decision making, strategic planning, and improve profitability by creating a single aggregated view of risk.

The Integrated Risk Platform will use IBM’s data management tools, Algorithmics’ analytics capabilities, and Cognos’ BI reporting assets in an integrated technology stack. The Integrated Risk Platform consists of end-to-end aggregated risk data management and a central data warehouse

of enterprise results, enabling risk reporting and access to risk data for decision support. It is important to note that this is a work in progress and the offering is scheduled to be developed further throughout 2013 and beyond. The Integrated Risk Platform is designed to be a single portal for risk results that will provide consistent risk results from trusted data across the enterprise. Using a common taxonomy will make it easily accessible and  comprehensible for senior management and other stakeholders who may or may not be risk experts, who can use it to make risk-aware decisions.

The platform aims to enable users to use risk-adjusted performance measures to manage the business and scarce capital more effectively and use a more transparent single view of risk to provide contextualized risk information on time to senior management.

IBM has the individual tools at leading maturity levels, in the areas of: pure play data management tools in all (InfoSphere) stacks; application and numerical calculation servers; business intelligence; network appliances and columnar databases for speed; predictive analytics servers; and capital market regulatory and operational risk IP.  One available component is the IBM Algo Integrated Risk Reporting Manager, which provides a hub for risk reporting and will use Cognos BI tools to provide consolidation and extensibility. The platform further utilizes Cognos’ dashboarding capabilities, providing visualizations of group-wide aggregated results data across the bank and its subsidiaries.  The solution includes a range of pre-configured standardized risk and regulatory reports. The platform was designed to leverage IBM Algorithmics Engines output to their reporting data warehouse (multiple data marts), but also to be risk engine agnostic, so it can ingest exposure information from any service, and track and aggregate the data. The use of a single platform is also designed to allow firms to amalgamate risk silos and data warehouses to provide a consistent source of results and to provide clear data lineage and a clear audit trail. The solution uses IBM’s data management tools and models to ensure data consistency and quality, data validation, and data reconciliation, while also ensuring data linage and  traceability. The platform is targeted towards Tier 1 and Tier 2 banks. It will be interesting to see what the appetite is, and how/if it can be implemented on a more component basis, as at least in the US and Europe there has been a renewed emphasis on reducing operational expense and the holistic target here is transformational opportunities.

Examples of IBM Risk Analytics’ key differentiators include common risk analytics across the enterprise, integrated stress testing and capital optimization; the shift by regulators to demand more robust analysis fits very well with the IBM Risk Analytics’ approach that combines breadth and depth of analytics. IBM Risk Analytics enables real-time risk management through in-memory analytics, and they have a powerful suite for Basel III including CVA and Liquidity processing.

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