Operational risk management (ORM) has long-been an imperative in the financial services sectors, due in large part to regulatory requirements and oversight. Yet the immaturity of ORM has been demonstrated, time and again, by high-profile instances of operational risk failures impacting the largest financial institutions.
Driven by new regulation, banks are soon expected to adopt a standardized measurement approach to operational risk that should enable them to model operational risk scenarios, analyze historical losses and predict future events more effectively.
The new Basel consultative paper on the standardized measurement approach (SMA) turns on its head the traditional ideas about why a bank would devote resources to operational risk capital modeling and evaluate business performance based on a return on capital measure. This methodology creates more meaningful operational risk analytics, including scenario analysis of top risks; scenario analysis based on external loss events; loss forecasting; and greater reliance in analytics on qualitative inputs such as audit scores, metrics and RCSA results. Moreover, this put greater focus on analytics will enhance the soundness of the control environment, including evaluation of control tests for control failures associated with large losses and near misses.
A pre-requisite to meaningful operational risk analytics is a data model that allows linkages between operational risk events, risk assessments, metrics and scenarios with other data objects – such as audits, control tests, vendor risk assessments, IT risk assessments and the output of other business and functional groups. To support valuable risk analysis, many are turning to advanced analytics that can help a firm streamline and automate its risk and control assessment processes; enhance collaboration across the three lines of defense; and, ultimately, gain a clearer view of operational risks across the enterprise.
We provide analysis of operational risk data and predictive analytics built on an industry leading reporting and business intelligence platform through pre-built dashboards, charts, and reports to help strengthen a financial organization’s ability to contain losses. Financial institutions can now unify risk and compliance to provide a holistic view to senior management. These advanced analytics also gives firms the ability to build many-to-many relationships across data objects, which allows for greater transparency in the relationship between risk assessments, risk events, metrics and scenario analysis.
Through these detailed analytics, organizations can analyze and compare assessment scores for all interlinked and interconnected risk disciplines against the firm’s risk appetite on a single dashboard, helping identify areas of weakness and vulnerability to different types of losses. Senior management can now be alerted to evolving situations requiring intervention through time-series analyses of performance trends and automated notifications.
Our services specific operational process reviews, risk management analysis and self-assessments (RCSA), heat charts, credit and collateral management, data integrity, analysis and validation, and business continuity planning.