Insurers must embrace Artificial Intelligence technology to successfully navigate today’s emerging transformative trends that are shaping the insurance landscape. An aging population, reliance on AI, and new technological, environmental, financial and social risks, are top of mind issues for many claims leaders. See How Digital Trust, AI & IoT Technology Can Help Insurance
An aging claims workforce, coupled with growing loss costs and expenses, have resulted in record high combined ratios. This presents insurers with a unique dilemma: how to ensure proper claims outcomes and lower claims spend, with an increasingly less experienced and knowledgeable talent pool.
In fact, developing a comprehensive claims AI strategy, which reimagines an organization’s plan for people, process, technology and risk, is critical to achieve some of the estimated $100 billion in gross written premium, as well as associated expense savings.
To better understand where and how to infuse AI in the claims process, take a step back and look at the current drivers of claims quality. See How AI Technology Helps Insurers Enhance the Customer Experience?
Understand the risks of AI
Technological risks are those inherent to the AI solution and independent of human interaction. Because AI collects, stores and processes personal data, data privacy leaks can occur creating data confidentiality risks. AI may also be vulnerable to security risks. Algorithms are the parameters that train AI to develop insights. If an algorithm is leaked, the model can be copied, therefore compromising data. Finally, most AI solutions currently do not effectively track how it makes decisions. This lack of transparency makes it difficult to fix systems when unwanted outcomes occur. This can be problematic in the highly regulated insurance arena, especially when responding to inquiries or audits.
Usage risks are those that result from human interference. AI depends on the learned or trained data. Incorrect or biased data will produce inaccurate or distorted results. Additionally, there is potential for incorrect AI output. Users often lack awareness of what AI is, what it does and how it performs. Finally, AI could be used for a purpose outside of original intent, and thus compromised, causing adverse outcomes.
Although AI risks can be significant, implementing structured governance will help mitigate these threats. Effective governance consists of:
Tracking all business objectives;
Determining if the objectives are being met;
Assessing whether modifications are needed; and
Implementing and testing any modification.
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