Operational Risk Management Systems for Financial Services 2013

<p>Over the past decade, operational risk management (ORM) has steadily risen in prominence in financial&nbsp;institutions. It has not only become an accepted part of the risk function, but senior management has now&nbsp;recognized it as a central and vital part of enabling financial institutions to operate profitably and effectively.</p>

<p>ORM initially came to the fore through the Basel 2 regulations, which instructed financial institutions to&nbsp;include operational risk in capital calculations and also included operational risk governance and disclosure&nbsp;requirements. Solvency II introduced equivalent requirements for insurance firms. The imposition of operational&nbsp;risk measures prompted some skepticism about the practical benefits and robustness of methodologies being&nbsp;promoted by the Basel Committee, but a number of high profile losses and pressure from shareholders as well as&nbsp;regulators meant that establishing ORM was unavoidable for financial institutions.</p>

<p>Since then, the internal and external forces pushing for more systematic ORM have only strengthened. The&nbsp;financial crisis, a series of rogue traders and process failures, and public demand for stricter supervision have led&nbsp;to regulators increasing the demands for ORM.</p>

<p>Moreover, inadequate controls and procedures have been implicated as among the causes of the financial crisis&nbsp;and as responsible for one-off loss events, such as JPMorgan’s ‘London Whale’ losses and the rogue trader&nbsp;Kweku Adoboli at UBS. Shareholders are seeking improvements in the way their institutions are run. These&nbsp;losses and recent rate-rigging and money-laundering scandals have also eroded public trust in the financial&nbsp;sector. The public assumes not that processes failed, but that banks and bankers are simply corrupt. This&nbsp;assumption can only be changed by improved practices.</p>

<p>As a result, financial institutions are starting from the bottom up to improve risk management.&nbsp; They realize that&nbsp;other risk disciplines and compliance and governance policies rely on successful communication, management,&nbsp;and execution. Without robust operational risk programs, well-intentioned and well-designed policies may not<br />
be effective. Firms need to get their processes and people in order before credit, market, or liquidity risk policies&nbsp;can be executed efficiently.</p>

<p>Simultaneously, firms are reversing the last decade’s trend towards greater centralization of risk management.&nbsp;With greater decentralization of operational risk responsibilities, firms are shifting investment from the second&nbsp;line of defense (risk functions) to the first line of defense (front office).</p>

<p>This report covers the competitive landscape for operational risk management systems. The range of solutions&nbsp;and functionalities offered by vendors can make it difficult for buyers to decide which solution best suits their&nbsp;operational risk needs. Consolidation of vendors, increasing requirements and demands from buyers, and<br />
continued innovation has altered the operational risk technology landscape.</p>

<p>This report uses Chartis’s RiskTech Quadrant® to explain the structure of the market. The RiskTech Quadrant®&nbsp;uses a comprehensive methodology of in-depth independent research and a clear scoring system to explain&nbsp;which technology solutions meet an organization’s needs. The RiskTech Quadrant® does not simply describe&nbsp;one technology solution as the best operational risk solution; it has a sophisticated ranking methodology to&nbsp;explain which solutions would be best for specific buyers.</p>

<p>This report covers the leading vendors offering operational risk solutions for financial institutions, including&nbsp;BPS Resolver, Chase Cooper, EMC-RSA, IBM, Mega, MetricStream, NASDAQ OMX-BWise, Oracle,&nbsp;Protiviti, SAP, SAS, SunGard, Thomson Reuters, Wolters Kluwer FS, Wynyard, and YarcData.</p>

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• Topics
• Quantitative Methods
• AI & Machine Learning
• Programming Languages
• Workflow/RPA
• GRC and Operational Risk