By Patrick O’Neill, Founder and President, Redhand Advisors
In today’s rapidly evolving business landscape, organizations are faced with increasingly complex risks that can have a profound impact on their operations and bottom line. To effectively navigate these risks, companies are adding artificial intelligence (AI) to their risk management arsenal.
AI has the potential to revolutionize risk management by enabling companies to identify, assess, and mitigate risks in real-time, with unprecedented accuracy and efficiency. Here are five key steps to developing an AI strategy for risk management.
1. Identify use cases and benefits
Take inventory of the potential areas where AI could help you. Consider both your current goals and the capabilities that you know AI has. Try to find as many synergies between the two as possible.
Remember, you can’t attack everything at once, so set short-, medium-, and long-term goals. Start with some quick wins and don’t be afraid to experiment while doing so.
Try pulling data out of your risk management information system (RMIS) and plug it into a few AI models to see if it can pinpoint trends in your data. Can it help to identify risk or claims outliers that are otherwise hard to find, or can it identify those outliers at a faster rate than you could previously do with just your RMIS or workforce?
For example, one of our clients outsources physicians for hospitals. Their business could use AI to review their claims data, compare it to benchmarking data across each state in which they do business, then determine which states are the best to do business in financially. Let’s say their largest book of business is in Florida, but the data reveals Florida is the state where high medical malpractice claims are trending. That information would be particularly valuable in determining their future business decisions when it comes to working with customers in Florida.
2. Determine data and technology requirements
A significant hurdle to successfully implementing AI for many organizations is bad data. So, before you engage AI, make sure your data is accurate and complete. Then you can collect and analyze your clean data using AI to create a better understanding and picture of your true business risk.
Consider the tools your organization has available, from your RMIS to external analytics tools and other in-house resources. You may even decide to take a hybrid approach. For example, plug your RMIS data into external analytic tools. Then bring all that data and its analysis back to the RMIS. With AI, you can pull benchmarking data from across the industry and then cross-reference that with your organization’s current data to determine where a spike in claims is likely to occur.
3. Identify the necessary resources and determine governance
Building the right team and establishing the appropriate governance structure are essential for the successful implementation of an AI risk management strategy. This includes selecting the right stakeholders from your organization, establishing a go-forward strategy for AI, and determining the high priority use cases, as discussed above.
Today, budgets for this type of implementation are shifting to the cloud — not supporting internal resources. Often, organizations now engage outside IT vendors to support internal staff during AI integration as well. Strategic partnerships with academic institutions can also provide this specialized expertise. Having the right structure and foundation in place is critical to success.
4. Create a flexible roadmap
When it comes to risk management and harnessing the power of AI, companies must create a practical, incremental roadmap for implementation that allows them to build on previous successes.
Articulating a clear vision and a corresponding set of business objectives on how your organization will leverage AI is a first step. Do the following to help achieve that vision:
- Assess how AI can support what you already have in place
- Define where AI fits into your organization
- Ask yourself where can AI be used
This type of roadmap will help lay out priorities for the immediate, medium- and long-term. Immediate goals should provide your organization guidance on what is possible and reveal the quality of your data; longer-term goals should focus on more complex AI projects with long-term benefits. Along the way, be prepared for the unexpected as things can and will change.
AI tools can always be configured to monitor your policies and data, but its secret sauce is the software’s ability to access raw data and find outliers that can impact your organization’s risk. By leveraging feedback loops and incorporating new data and insights, companies can enhance the effectiveness of their AI-powered risk management initiatives and stay ahead of evolving risks. Incorporating AI technologies such as machine learning, natural language processing and predictive analytics can help organizations gain valuable insights from their data, enabling informed decisions and proactive mitigation of risks before they escalate.
5. Deploy AI responsibly
Remember, an AI strategy for risk management is not a one-time implementation; it is an ongoing journey of learning and improvement. Organizations must continuously monitor and evaluate the performance of their AI models, identify areas for improvement, and refine their strategies accordingly.
While AI offers immense benefits for risk management, it’s important to consider the risks as well. Organizations must implement robust security measures to protect sensitive data and ensure compliance with regulatory requirements. Educating employees on responsible use will help maintain trust and credibility in risk management practices.
Embrace the future of risk management with AI
As organizations continue to face increasingly complex and dynamic risks, embracing the future of risk management with AI is no longer an option; it is a necessity. By developing a comprehensive AI strategy and leveraging advanced technologies, companies can transform their risk management practices, enhance decision-making capabilities, and gain a competitive edge in today’s volatile business landscape. Embrace the power of AI and unlock the full potential of risk management in the digital age.
To learn more about developing an AI strategy for your risk management program, schedule an inquiry call with Redhand Advisors today.