Innovations throughout the entire value chain

These developments are all very exciting and they will raise customer service to the next level. But AI transformation has the potential to result in innovations throughout the insurers’ entire value chain. This would have profound implications like:

• AI will open up opportunities to make more efficient and focused use of internal data to provide personalized services.
• Real-time and geo-tracking approaches will enable users to have their needs met on demand (for example, because chatbots will handle conversations and interactions).
• Prevention through predictive analytics will cut costs. Given that AI will also result in innovations in the field of risk management.

How will AI transform your business?

AI isn’t just a vague concept that isn’t being used yet. The transformation is already happening. These are the four domains in the insurance industry where AI is being used the most today:

Claims automation

Automating claims results in reduced process cycle times, but you’ll also be able to free-up capacity for value-added work. So what does fully automated claims handling look like?

• Initial claims routing: This isn’t being used yet, but it is coming. Some repair services will be triggered automatically upon loss. This means connected cars will be able, through their internal software systems and recording capabilities, to register all events prior to a crash (just like a “black box” in an airplane crash). Notifying repair services and the insurer will be done fully automated since the circumstances of the cars are digitally recorded.

• Streaming videos will be used for loss description and estimated amounts: This one is already used today. Some East European countries are already filming everything that happens on the road from the dashboard of their cars. So, they are able to use these images to reconstruct the circumstances of the claims. Determining the amount of the repair of damage based on a simple photograph is becoming more and more common every day.

• Acting at the “human-in-the-loop”: Although studies say that up to 40% of the insurance jobs will be lost, we still need to look for the coexistence between AI and the human perspective. Even if AI is becoming so powerful that it would not need human intervention for certain cases. AI models are a “black box” not knowing what rules lead to a certain outcome. So human intervention will still be necessary to look at how the AI models behave in certain circumstances. It’s crucial if you want the AI models to be trained correctly. But that’s not it. Some AI models have been trained on limited and unrepresentative data. It also remains important for an insurer to not discriminate based upon personal characteristics. Not only from a legal or regulatory point of view but also from a commercial point of view.

Want to know how AI will transform your business?

Underwriting

AI enables mobile subscriptions and it quantifies the mismatch with the insurance portfolio. Up until now, the characteristics of an insured object (e.g. a house or apartment) were described by the customer based upon a long list of questions. If the “insured object” changed over the course of years, it was not always taken into account in the insurance coverage. By using AI, we can automatically identify the characteristics of the insured object (housing, car, …) which will not only shorten the underwriting process for the insurer but will also provide more accurate information. A win-win situation!

Customer service

One important part of the sales and marketing department of an insurer is to predict a customer’s churn and to improve the customer experience. With AI insurers will be able to predict their client’s behavior like:

• Which client will be interested in which product and when.
• Which client won’t be satisfied with his or her product.
• Which client will stop paying or which client will have damages.

But AI opens more doors to enhance customer service. Our new platform Undercover, for example, analyses the cross-platform customer usage data and statistics to learn detailed customer profiles to be able to offer personalized content and only relevant products. This improves customer satisfaction and churn probabilities.

Fraud detection

With the integration of AI, insurers can reduce fraud losses and stay ahead of emerging fraud scenarios. The algorithms can reliably identify patterns in the data and thus help to recognize fraudulent claims in the process. With their self-learning abilities, AI systems can then adapt to new unseen cases and further improve the detection over time. AI techniques are potential game-changers in the area of fraud. Fraudulent cases may be detected easier, sooner, more reliable and even in cases invisible to the human eye. This makes it the best-suited technique on the market to tackle this important “leakage” which is still a big concern for the insurance industry.

Are you interested in finding out what AI will mean for your insurance company and how it could change the way you do business? Ensure your future by getting informed by us!

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