Top 3 Predictions in 2018 About AI in Insurance: Hits or Misses?

By March 14, 2019 February 17th, 2020 Blog
AI and ML in Insurance

AI and ML (machine learning) were the big buzzwords in 2018. There were predictions regarding the increasing adoption of AI and then there. So far, AI has been adopted across various insurance processes, such as claims settlement, sales and distribution, product development and design, policy management, customer service, and even underwriting.

 Here are some AI predictions from 2018 and my viewpoint on how they fared.

1. AI Will Be the Magic Wand and Bring Higher Value Than Expected

The Claim:  AI and ML will start bringing in value from the day an insurance company implements it.

The Reality: Barring a few success cases, most of the AI product and platforms are still in the experimentation, evaluation & prototyping stages. Significant value expected in 2018 is still not visible / realized by the companies that have invested.

The Impact in 2019: As AI and ML will emerge from their experimenting phases to Operationalization, we will be able to see their effect on the industry & outcomes. The focus will be on proving the technology’s worth and making it even more accessible. Stakeholders will look to see the theory turn into reality.

2. Exponential Insights for Insurers from the Capabilities of AI

The Claim: Machine learning will take your data and turn up miraculous insights, as soon as gets trained on your industry’s data patterns, which can be sped up with more complex algorithms.

The Reality: It turns out, training an AI algorithm takes time. Even plug and play systems need to pre-train their neural networks on industry data if they wish to show results quickly. However, this need to train neural networks quickly has given rise to innovative new solutions that are rethinking basic computing models.

The Impact in 2019: With the hype around AI diminishing, we will actually be able to witness the real value that machine learning can and will provide. Platforms with pre- trained networks will be able to get a leg up in the industry, as compared to the products with newer algorithms but no training. Reinforcement learning will play a key role. Better AI training solutions will show up and make complex insurance processes more streamlined.

3. Better Customer Satisfaction Through Efficiency in Claims Settlement

The Claim: Most major insurers will adopt AI, and the consumers will finally reap the benefit in terms of hassle-free claims settlement and better customer service.

The Reality: While AI has made the process more streamlined, we are still some ways away from “touchless claims.” The drone capture of the accident site may have begun, but there’s still some time before a completely seamless AI-driven process takes over claims settlement.

The Impact in 2019: It is entirely possible that an AI platform autonomously starts taking care of claims. However, as an industry that is wary of all things new and innovative, it is possible that more regulation may arrive to govern the use of data and the role of data scientists. A transparent system that can show how data is collected, standardized, and managed, will be able to move along the adoption of AI in every step of the process much faster.

And the Burning Question!

The Claim: Many jobs will be lost to AI as it moves across industries.

The Reality: The application of AI will create more jobs rather than take them away. It will mostly make redundant the cumbersome process of collecting and analyzing data, mainly those aspects that are prone to human error and are impacted by human computation limits.

The Impact in 2019: We will need more people who can think outside the box in ways to make the algorithms more robust and efficient. We need people to train AI. As data volumes increase around the globe, we will only need more people to work with it.

AI technologies are here to stay, and they are making a massive impact on the insurance industry and its various value chains. The effect may take a while to register, but it is sure to expand exponentially. The key to staying relevant and not getting drawn into the hype is to focus on your needs and find the right AI solutions that can deliver it without adding to your cost of ownership.

Gopal Swaminathan

Gopal Swaminathan

Gopal is a dynamic leader with 18 years of Data & Analytics experience, enabling business outcomes through information insights. Since 2008, his focus has been P&C Insurance companies. Therein he drives ROI maximization and enhancing customer experience using Advanced Analytics, Artificial Intelligence, and Machine Learning solutions. As a Director of Products, he spearheads the Product Development for Insurance Analytics. Additionally, he is responsible for Business Development of existing and new accounts in the Greater Phoenix Area.Read More Posts

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