In recent days, digitization has been gradually spreading across various sectors, notably the insurance industry. It has experienced significant transformation driven by digital technologies. One of the key drivers of this transformation is the availability of AI, which has become more accessible to users, whether for free or at a cost.
Artificial Intelligence (AI) and Machine Learning (ML) models are being integrated into industries to aid in enhancing the accuracy of risk evaluations, enabling personalized insurance solutions, ultimately leading to improved pricing and better-informed decisions.
At the InsureTech Summit, Michael Michie, CTO of Everse Technology Africa, delved into the critical role of AI and ML in transforming Risk Assessment, customer service, and fraud detection.
While chatbots and virtual assistants have become common applications of AI, more complex uses are emerging, with a focus on addressing critical challenges such as fraud detection and prevention. Insurance, in particular, faces the challenge of fraudulent claims and wrongful evaluations. AI, powered by computer vision, can now analyze images and videos to assess the conditions of insured assets, ultimately enhancing accuracy in determining the value of assets and preventing false claims.
With ML, one is able to train new models from the pre-existing model, prepare new training data, and assess whether there has been an enhancement in the overall performance score. AI, powered by computer vision, can now analyze images and videos to assess the condition of insured assets.
However, despite the advances in AI technology, one can never be too careful. The existence of deepfake technology, for instance, can generate convincing fake images and videos, making it challenging to distinguish between genuine and fraudulent claims. This technology poses a threat to the insurance sector, as malicious actors can exploit it to falsify claims and receive payouts they don’t deserve.
The risks of data protection and cybersecurity shouldn’t be overlooked. As the insurance industry embraces AI, it must also prioritize cybersecurity and data privacy. As a model becomes more complex, more data is needed, and the right insurance tools need to be set up to ensure no data breaches occur.
“The more complex your model is, the more data you need to feed it, and more questions arise around privacy and data protection. It’s always very important to ensure that you have set up the right data, , and the data is accurate ,” Michael stated.
Insurance industries are urged to be vigilant and not rush to use AI without a clear strategy, which may lead to failed implementations. When integrating AI into insurance operations, organizations must carefully determine a viable use case, ensure they have access to the right data, and build the right pipeline for deployment.
AI is streamlining and automating processes in the insurance industry. Cumbersome tasks like claim form processing are now being handled efficiently by AI assistants. These AI-driven assistants can engage with customers, gather information, and auto-fill documents, making the claims process smoother for both customers and insurance staff.
To harness the power of AI, insurance companies must carefully plan their AI initiatives and prioritize data security while staying vigilant against emerging threats.