With the growing number of fraud and risks, the need for proper risk analysis has also moved upwards. As a result, to mitigate such forthcoming losses, advanced technology with the combination of statistics and Artificial Intelligence has been put to use in every possible domain. One such profound technology is Risk Assessment Analytics which makes strategy formulation a flawless process in the organization.
What is Risk Assessment Analytics?
Undoubtedly, the right statistical solutions when blended with Big Data have helped several organizations in predicting trends and outcomes. Similarly, Risk Assessment Analytics refers to the process of applying data analytics to risk assessment to identify threats and develop risk assessment strategies. Such profound strategies so formed help to remediate and respond to threats effectively. The scope of the Risk Assessment Analytics ranges from basic statistical modeling at designing phase to Machine Learning models for painting the clear picture of dynamic organizational risk based on large sets of data.
Importance of Risk Assessment Anlaytics
The right risk management plan comprises analyses drawn from all potential risks that the organization is expected to face. To leverage a health risk assessment plan it is broken down into categories by assigning risks and consolidating distinct data. Hence, the risk mitigation efforts become worthwhile. Some of the key use cases of Risk Assessment Analytics are as follows.
|Avoiding Repetitive Losses||With effective Risk Assessment algorithms in place, the red flags and trends can be identified to avoid organizational losses. Moreover, the organizations also become potent to recognize the specific area, department, and season to run a root-cause analysis and discover the potential solutions. Hence, the cost involvement in similar claims reduces significantly.|
|Improving Reporting Mechanisms||The use of in-depth Risk Assessment Data Analytics allows reporting on relevant industrial and organizational factors to thoroughly diagnose issues. Thus, the improved risk reporting mechanism helps to make data more understandable, actionable, support mitigation strategy, and accelerate business ideas.|
|Establishing Healthy Insurance Premiums||The Risk Assessment is the key job of the Insurance Providers. It means planning any insurance products and deciding premiums on such policies remains incomplete with the absence of proper risk analysis. As per the general observation, individuals with more risk ought to pay higher premiums for better loss coverage.|
|Forecasting and Monitoring the Organizational Risk||The consistent use of Risk Assessment Analytics helps managers to identify red flags and accordingly discover the right business strategies and avoid risky scenarios in the long run. The early risk assessment helps to ensure seamless work performance and target growth and goal achievement.|
Applications of Risk Assessment Analytics
Risk Assessment Analytics for Risk Management
While planning effective Risk Management solutions, Risk Assessment Data Analytics plays a phenomenal by tailoring specific industrial needs and data requirements. Hence some of the key steps involved in the process are:
- Classifying the data as public or private (restricted) for risk assessment.
- Ensuring consolidation of business goals with the available data sets.
- Identification of compliance needs to determine the salient feature of the potential risk and take required measures.
- To develop required measures the risk library with risk assessment plan and data analytics is used and gathering required insights becomes convenient.
- The important step is to build a risk Assessment Matrix to rank the impact, and severity of the risk and identify Key Risk Indicators (KRIs).
- After picking the right tools and techniques the quantitative measures are taken to derive a comparative study and analysis.
- The complete process leads to effective visualization of the risks and communicating the findings to respective authorities across the organization.
Risk Assessment Analytics for Data Protection Planning
In the organization, controllers are bestowed with the responsibility to assess the risks with respect to personal data processing. Here, Risk Assessment Analytics provides support to ensure the protection of personal data by addressing all the risks associated with it. In pursuant of the Risk Assessment process, the consideration of the General Data Protection Regulation is necessary. Some of the Risks associated with the data are:
- Freedom and Rights of Data to be used
- Damages arising out of the processing of data
- Becoming a Fraud Victim
- Social Disadvantages
- Financial Losses
Thus, the Data Protection Impact Assessment which is one of the tools of analyzing Risk Assessment Analytics help controllers to ensure data processing without the association of risk to it.
Risk Assessment Analytics for Auditing
The identification and analysis of relevant risk is the general task that is used to achieve an organizational objective. Therefore, the concept of Risk Assessment Analytics is used to reduce risk at manageable levels. Since Internal Auditing uses the risk-based approach, Data Analytics prove helpful in reviewing and analyzing budgets, proposing a budget plan, and evaluating the organizational risk factors. Using Risk Assessment Analytics, the general two–year plan is adopted in consideration of potential risk.
Risk Assessment Analytics for Banking
With the inclination of banking operations largely towards digitalization, the convenience does come at the doorstep but the risks and threats can be avoided either. Thus, Fraud Managers and Analysts in Banks and other Financial Institutions have to be required to make use of Risk-based Analytics for testing approaches and letting Machine Learning algorithms make necessary predictions to help develop useful risk management insights. Some of the common frauds in Banking and other Institutions requiring the attention of Data Analytics are:
- Account Takeover Fraud
- Payment Theft
- Weak Application Security
Risk Assessment Analytics for Controlling Incident
To control the risk associated with a particular event or incident, Risk Assessment Analytics are required to create a more detailed analysis of the incident risk. Based on such analysis the strategic and tactical actions are taken as per the requirement of the situation. The Incident Commanders carry out a dynamic risk assessment and help identify hazards by evaluating the risk and continuing the reviewing process with the help of situational awareness. These risks can be an occurrence of Fire, Accident, Earthquake, Tsunami, or other such calamities where prediction plays important role in reducing the quantum of all forms of losses.
Metrics Used for Risk Assessment Analytics
Since every Project Management begins with Risk Management. Thus, the importance of assessing of all forms of potential risks cannot be underestimated at any organization. However, the process of analyzing and measuring the risk is quite challenging, therefore the right set of metrics are used to evaluate project risk.
|Nature of Risks||The nature of the risk is the primary factor to consider while planning effective Risk Management. It could be an identified, actual, and unanticipated risk but in all these cases Risk Analytics work unbiased.|
|Severity of Risks||It refers to the seriousness of the threat or loss expected to arise out of risk. For this purpose, the risk manager evaluates the project and takes adequate measures to reduce the intensity of the risk and loss arising out of the same. To act as well- equipped solution for risk assessment Data Analytics has proved worth considering.|
|Frequency of Risks||The Risk Assessment Analytics uses the frequency of occurrence of Risk driven incident or event and help plague it at various stages through required Risk Management solutions. The higher the frequency of risk stronger is the planning required.|
|Cost Involvement||However, Risk Management strategies are often seen as the way to mitigate risk but besides this, the additional aim of such solutions is to ensure the cost-effectiveness in managing the potential or anticipated risk. To reach a full-fledged solution comparative study between project timeline, expenses involved, and implementation rate is thoroughly analyzed.|
|Effectiveness of the solution||After the risk mitigation solution has been prepared and placed, the effectiveness of its execution phase is examined, and based on its speed the impact of the solution in mitigating risk can be tracked too.|
Top Risk Assessment Software
According to the PMI study, it is analyzed that 86% of the organizations use some of the other Risk Management methods. Moreover, Mckinsey’s study indicates that 70% of the senior managers have started to adopt Digital Risk Management practices such as Risk Assessment Analytics to make the Risk Assessment process less time & cost consuming and reliable too. Thus, the popularity of the Risk Assessment and Management solutions which are mentioned below has increased over time.
|Resolver||Time Camp||AI Tracker||Synergi Life|
|Safesite||SAS||Master Control Risk Analysis||Audits.io|
|Qualys||CURA||Pims Risk Management||Opture ERM|
|Predict 360||Reciprocity||ARC Cyber Risk Management||Optimal Risk Management|
There are some of the key considerations which play important role in evaluating and selecting the suitable Risk Assessment Software.
- Compliance Management
- Incident Navigation
- User Interface, Reporting
- Prediction Capabilities
- Value for money.
There are diversified domains where Risk Assessment Data and Advanced Analytics have proven extremely useful. Thus, the proper understanding of the risk, its nature, and mitigating alternatives shall be ensured to allow technology to give refined results and better risk prediction for the betterment of the organizations.
Topics in Data Analytics
- Advanced Data Analytics
- Clinical Analytics
- Credit Risk Analytics
- Cyber Risk Analytics
- Data Analytics for Customer Behavior and Customer Experience
- Data Analytics for Customer Journey
- Data Analytics for Fraud Detection
- Data Analytics for Human Resources
- Data Analytics for Logistics and Supply Management
- Data Analytics for Risk Management
- Data Analytics for Talent Acquisition and Management
- Data Analytics in Asset Management
- Data Analytics in Digital Marketing
- Data Analytics in Healthcare – Use Cases, Metrics, Techniques, Companies and More
- Data Analytics in Manufacturing
- Data Analytics in Pharmaceutical Industry
- Descriptive Analytics – Definition, Types, Examples, and More
- Digital Analytics
- Financial Data Analytics
- Financial Risk Analytics
- HealthCare Claim Analytics
- Insurance Risk Analytics
- Insurance Risk Analytics
- Population Health Analytics
- Portfolio Risk Analytics
- Revenue Cycle Analytics
- Risk Assessment Analytics