We are currently experiencing a fundamental change in the way we live and work. Recent years have shown exponential growth in the exploration of artificial intelligence and its potential to alter all aspects of our lives. A lot of companies are already using advanced algorithms to predict the best time to reach you, on what device, and tailor email messages based on your online behavior.
Here are some examples:
Amazon has released one of the most effective voice-activated personal assistants in the media space, and Facebook is developing chat-bots in their instant messaging platform so brands can converse with consumers. Deep learning is also part of Facebook's efforts to improve filters on the posts and ads you see. Google uses RankBrain - a machine learning technology - to analyze spoken or written search queries and is able to process them into search results that are most likely to be what you're looking for.
Customer experience can be massively improved. Insurers might be able to cut their claims processing time down from months to just a matter of minutes by using machines. The increased speed and sophistication of the models delivered through Machine Learning is particularly useful in terms of accuracy when non-linear relationships are involved. The insurance industry has always tried to find patterns in data. What we can do now is automate that pattern finding. Then, we can be more sophisticated and use more complicated algorithms than humans do.
Also automated processes are often more accurate than humans. This helps insurers to cut down the number of refusals that result in appeals they may ultimately need to pay out.
With a significant part of an insurer’s cost structure coming from human resources, there is an increasing need to shift to automation in order to deliver significant savings.
One of the other opportunities for insurance companies is to focus their attention on the agent channel and support them with solutions that reflect the needs of their target customers. This includes artificial intelligence and so-called Robo-Advisor.
This does not mean that robots are taking over the advisory role, rather they are able to assist an agent with a huge amount of product details, regulatory input and customer insights.
We like to think that our beliefs, judgments and opinions are based on solid reasoning. Behavioral science shows that there is no such thing as a decision purely based in logic. Therefore the future belongs to people who know how to build relationships and understand the emotional component of taking decisions. I am convinced that there will be a premium on people who know how to deal with the emotional elements of the advisory role. In a world full of machines and automation, people want and will continue to desire human relationships.
Our success in the future will lie in the combination of human and artificial intelligence. We are now at a point where we are moving from using tools (like an axe or hammer) as passive extensions of ourselves, to working with them as active partners.