05 Jan 2023
Leadership & Management
Insurance companies amass lots of data, but how can they best make sense of it? Will an AI-driven insurance industry pose ethical issues such as discrimination? Dror Katzav, CEO of Atidot, a leading AI company for the life insurance industry, shares his thoughts on the topic.
Host: Hi, I'm Cheryl from Vertex. I'm thrilled to have with me, Dror Katzav, co-founder and CEO of Atidot, to have a chat on AI and its role in the future of insurance. Atidot is a leading provider of AI and machine learning solutions tailored specifically for the life insurance industry. It enables insurers to grow customer lifetime value and create new revenue streams. Dror excited to have this conversation with you. Now, we see AI underlying technology is being deployed in all aspects of our lives. How do you think the insurance industry will be reshaped by AI?
Dror: First of all Cheryl, thank you for having me. Insurance is one of the industries that is having a lot of data, abundance of data and on the other hand, touches everybody's life. We see that anywhere from car insurance to life insurance. And one of the things that happen when you have a lot of data and you have a lot of customers, is that an individual cannot truly identify and see all the trends and all the behaviours in that data. One of those capabilities that machine learning and AI gives us is the ability to extract more value from this data. One of the things we see with insurance companies is that only about 20 or 30% of the data is even being used.
There is so much more that could be used to improve the experience that the customer is getting. All the way from getting the policies digitally and automatically with two different types of underwriting and different type of risk models to better customer engagement and consumer management all the time and all the way through the claim management.
We deal a lot with insurance companies, with improving the way consumers monetize their policies to the best extent. So a consumer bought a complex financial product that they now need to manage. And the insurance company doesn't necessarily know how to provide the service. And with AI, you can better identify it, policyholder behaviour, and better adjust that with the right product at the right time.
Host: What are some key problems now, with the life insurance industry, how does Atidot address these issues?
Dror: What we found interesting about life insurance is that in most cases in life insurance, you buy the policy from the agent. And the agency business is a tough business. Agents are churning, retiring. In many industries, insurance included. You have a situation where most of the people bought the policy from an agent, It's a complex financial product that they don't really know how to operate. Insurance companies don't know how to give the service and the agent is not. So that is probably the biggest thing that's going to impact insurance over time. We have a consumer that has the product and doesn't really have a relationship with the company. Policyholders buy, on average nine policies and only like one or 1.1 policies from the same insurance company. And the ability to provide better service, identify these opportunities, and engage with the customers with the right proposals at the right time.
Yeah. So one of the things that it does in that, in that manner is integrated with insurance company, get access to the data. We run AI models to identify consumers in certain situations. And then build engagement models on top of that to engage with the customer and communicate with them the issue.
So they can address that either by setting an appointment with an agent or with insurance company. The most easiest example is churn So there are a lot of situations where the consumer might lose the policy and they might close, the policy because of something stupid, small, or maybe some inherent problem, maybe not, maybe that product is no longer a good fit for their needs. By identifying that and approaching to the customer before the time. We have models that can predict who is going to, is going to churn, who going to miss a payment and so on and so forth. That is over 80 per cent accurate. So we can tell that this person would have an issue at that point in time in the very near future. By addressing before it happens and engaging with the customer, you can say something that the customer like. We see you have this situation. We believe there are certain solutions. Can we book you a meeting with the agent or can we book you Can we direct you to the right place at the services solution to fix that. Same goes for up-selling and cross-selling.
Because if you give better service, you can always generate more business from those customers, as well as. Displaying difference, this is protecting your existing customers. You can use the same insights for playing offence. If those are the customers that have issues with my insurance company, they probably are lookalikes.
People like them have issues with other insurance companies. We can try and approach them with a similar approach and try and bring them in to our insurance company.
Host: So we are witnessing an explosion in data with the sheer amount of connected devices coupled with AI and deep learning models. Now, all that data in the hands of an insurance company, new risk and ethical questions arise. How does a company like Atidot look to balance these considerations?
Dror: It's a great question. And many of the regulators that we meet on a regular basis is asking this question, how do we make sure that you've done to create this combination, the models, how do you make sure that the models are based on your own parameters that are allowed or not. Discriminating through some kind of a data proxy, something that we don't want to discriminate against. The easiest way to address that is by understanding what you're trying to protect. Insurance companies already asked of the question. They already know a lot about you. They already have ways to differentiate pricing, but those ways are considered legal and ethical.
For example, a smoker and a nonsmoker don't get the same price. A person with diabetes and without diabetes don't get the same price. So there are certain things that we feel more comfortable with. Certain things that we're not, as long as the regulation is very clear around that, it's very easy to address that with the models. A guiding principle for us is, is this creating value for the consumer. If the policyholder benefits from that, then there's a good reason to believe that there is value in that if its just a way for their interests, company and a broker to get a hand and the policyholder doesn't benefit from that. It's a different situation that we are trying not to get involved with.
Host: Can you share more on new developments and what's in the pipeline for Atidot?
Dror: Yeah. One of the things we started doing recently is partnering with the insurance company and helping them manage their existing customer base. So for example, one of our biggest customers is Guardian Life. With Guardian Life, we sell via a joint venture where we get access to their customers. One the models and help those customers get better service. One of the ways in which they get better service is by addressing them to the right agent at the right time to get the right. proposal. Those agents are three times more productive than they were before they started using our services. Some of the things we are now looking to do is to expand that, expand into other product lines within life insurance such as annuities, medical supplements and others. As well as to go deep in the relationship we have with the agents and the insurance company to make sure that the product is monetized to the best extent.
Host: Thank you so much truly exciting times for Atidot. Some people say that Insurtech will disrupt the insurance industry. What do you think about that statement?
Dror:I think the first wave of companies and insurance,we're trying to build everything from the ground up by themselves. It's easier to do that in car insurance, home insurance, harder to do in life insurance. One of the issues is that in life insurance, you give your money to a company that needs to pay back in 10, 20, 30, 40 years. So there is a lot of trust that is involved in the process to a lot of agents that are part of the process. So disrupting that from the ground up, setting up a new insurance company is a huge challenge.
On the other hand, partnering with the insurance company. And through that, getting access to the customers is the strategy that we've chosen. By partnering with a company, we can accelerate our way to get access to existing customers that already have insurance for 5,10,15,20 years and walk with them, which otherwise would have taken us many years to accomplish. So for us that was the right strategy. For other companies maybe different strategies. We do, we definitely see that the current trend is to partner with insurance companies and find way to do things together versus building an insurance company from scratch.
Host: Dror. It's been an absolute pleasure and thanks again for taking time to share all that insight on how AI is shaping the future of insurance. For our viewers, be sure to check out Atidot and thanks for watching.
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