For financial institutions, the main technology challenge has been and always will be the problem of providing clear, relevant information on the whole enterprise to senior management. In large, multi-national institutions with multiple technology systems, gaining a coherent view of the financial position and risk faced by the organization will always be difficult. At the same time, this viewpoint is vital for effective risk management and improving performance.
The particular circumstances of the financial services sector make this challenge especially difficult for financial institutions. The increased speed and volume of transactions have led to the spiraling growth in the three Vs of data (volume, variety, velocity) and firms need to be able to process and respond to this data quickly to tackle risks and seize market opportunities. Regulatory pressures are also forcing firms to submit more information more often. Regulators have also introduced data management standards and have increased sanctions for non-compliance.
This means that while improving data management and business intelligence (BI) has been on the horizon of financial institutions for some time, it is now becoming a matter of urgency. Regulatory requirements mean that firms need to do more with less for compliance, ensuring that they are able to organize and submit more data at more frequent intervals. More importantly, there are pressing business needs. With profit margins under pressure and significant threats to the sector remaining, firms need to become risk intelligent to enhance risk management and improve performance.
To achieve this, financial institutions need to ensure they have an enterprise view of risk. This will need to be supported by reliable data to ensure that decision-makers get the information they need. The goals of data management and business intelligence systems must be first to ensure that all relevant data is collected, validated, and available, and then that this data is converted into practical information that is available to support senior management. This will mean integrating data from across the enterprise and breaking down silos.
This will require firms to invest in technology projects that have long been put off. Firms will need to invest seriously in robust data management and BI solutions that can give them an enterprise viewpoint. However, firms will also want to retain flexibility and not get locked into a legacy system. This report covers the competitive landscape for data management and business intelligence systems for risk management. The range of solutions and functionalities offered by vendors can make it difficult for buyers to decide which solution best suits their needs.
This report uses Chartis’s RiskTech Quadrant™ to explain the structure of the market. The RiskTech Quadrant™ uses a comprehensive methodology of in-depth independent research and a clear scoring system to explain which technology solutions meet an organization’s needs. The RiskTech Quadrant™ does not simply describe one technology solution as the best data management and business intelligence solution; it has a sophisticated ranking methodology to explain which solutions would be best for specific buyers and which vendors have better functionality in data or BI.
This report covers the leading vendors offering data management and BI solutions for risk management in financial services, including Axiom SL, Empowered, GoldenSource, IBM, Markit EDM, Misys, Moody’s Analytics, Numerix, OpenLink, Oracle, Panopticon, Quartet FS, SAP, SAS, Wolters Kluwer FS, and Xenomorph.