Risk Management Analytics

Nearly every move in the current business world involves some type of risk. These risks can stem from uncertainty in financial markets, project failures, legal liabilities, credit risk, or any uncertain or unpredictable cause or event. This is why organizational risk management and analysis is crucial in a business’s decision-making process. Risk management analytics tools are important for obtaining and understanding the most accurate and up-to-date risk-related information.

Risk management analytics is the implementation of data, statistical and quantitative analysis, in explanatory and predictive models to drive decisions and actions. Risk management analytics tools use extensive volumes of data to uncover patterns and identify risks and opportunities to provide outcome predictions and reach better-informed decisions.

Risk management analysis is a two-stage process. First, Individual events are processed by quants in order to uncover individual risks. Quants, or quantitative analysts, usually hold an advanced degree in physics, mathematics, statistics, or engineering, and are experts in complex mathematical and statistical methods. The Quants analyze pure data to provide data to systems that handle the risk management analytics.

At the second stage, the individual events are then processed at an organizational level by IT systems that apply business logic to aggregate and perform multi-dimensional analysis on the possible exposure levels. The insights that are received by the analytics tools can make a real difference in organizational risk management, which in turn improves an organization’s performance. Analytics provides information on why something happened, and this information can be applied as a model to help predict future implications.

Analytics is based on access to quality data, robust algorithms, and sufficient computation power. The capability to identify risks, predict trends, and anticipate events makes analytics an important and valuable tool for different organizations, from government offices to financial institutions.

Risk management analytics tools should:

  • Be an integral part of organizational decision making processes
  • Address uncertainty and assumptions
  • Be systematic and structured
  • Be based on data provided by statistical and quantitative analysis
  • Be customizable
  • Be transparent and inclusive
  • be dynamic and capable to handle change

ActivePivot system is a real time OLAP analytics platform that provides insight into complex and dynamic data. Its risk management analytics solution is customizable according to organizational risk management requirements. The system’s real time and in-memory capabilities allow fast aggregation and analysis of massive amounts of data to provide accurate and up-to-date information on possible risk without greatly affecting the system’s performance.

ActivePivot can perform analytics on different types of risk, including credit, market, counterparty or liquidity risk, as well as analyze a variety of ‘what if’ scenarios. The system’s analytics capabilities help understanding exposure levels and manage risk in order to make better-informed decisions as well as adhere to current regulatory requirements.

To try out ActivePivot’s Risk Management Analytics solution, see our live demo.

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