Risk management is always the primary concern for any business. The management of many businesses are recognizing its importance for their business. The organizations are at several risks like damage of reputation and loss of customer loyalty when risks are not properly managed. So, many executives are looking at risk management analytics to get the help.
How Risk Management Analytics Is Done?
Risk management is done with employing the analytics tools across the enterprise at various levels in the risk management process. The technologies apply right from identification to mitigation. The analytics usage and application varies from stage to stage in risk management process as the inputs and outcomes vary at each stage in the process.
There are five stages in the risk management process and each stage has different usage of risk analytics tools, models and solutions.
- Risk identification: The organization faces several risks from both internal and external sources, and these risks affect the organization functions and goals badly. As the organizations now a days are growing bigger in size, so also the data that must be analyzed to identify the risks. The combination of big data and risk management analytics solves the problem of reviewing the large amounts of data to identify risks. Various tools like web scrappers and data visualization solutions can be used in this stage for risk management analysis.
- Risk assessment: The risks that are identified must be assessed in detail to evaluate their effects on organization performance. This assessment is key to prioritizing the risks, and then plan to act on the risks. Creating a risk profile based on impact and likelihood can be done with use of risk management analytics. The analytical framework developed can perform a realistic assessment of the impact of various risks. You ca apply data models and data ingestion solutions at this stage.
- Risk mitigation: This stage involves designing mitigation strategies for the risks identified. The risk analytics solution can be used to test various mitigation plans to assess their effectiveness in controlling the risks. Based on the findings, you can finalize the best mitigation plans for various identified risks. Risk modelling techniques are helpful here. These techniques can work along with AI and machine learning applications to assess the effectiveness of mitigation strategies.
- Risk monitoring: Though risk mitigation strategies are deployed, it is important to monitor risks in real-time to act immediately when a risk arises. Risk management analytics solutions can apply workflow modeling techniques to send alerts to risk management professionals whenever any risk arises. This enables the management to act immediately and prevent damage. You can apply a workflow solution along with an appropriate visualization framework at this stage.
- Risk reporting: Reporting of the risks at enterprise level is important for effective risk management. You can generate scheduled and ad-hoc risk reports. You can use an integrated technology solution along with risk management analytics tool that works across the entire risk management process to generate various risk reports.
Benefits for a Business from Risk Management Analytics
Risk management analytics help a business in the following ways:
- Improved risk prediction: Various analytical techniques available make it easy to measure, quantify and predict risks that the business should be aware of to prevent their occurrence. This has reduced the dependency on the intuition of executives and led to a scientific approach to risk management.
- Easier risk management: The analytics helps measure risk at various levels and in various sections of the enterprise. The data is gathered and findings are presented in a single system for time to time review by executives. The identification, assessment and managing the enterprise risks has become easier now.
- Unified view of enterprise level risks: The analytics tool gathers data that is both structured and unstructured and gives passible insights necessary for decision making. The availability of the enterprise data in a single system offering unified view enables enterprise-wide approach in business strategies and decisions.
Related Topic
Data Analytics for Risk Management
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