According to the Cambridge Dictionary, insurance is defined as the agreement, between two parties, in which the insured pays a company money to gain access to security, and the company pays the costs if the insured suffers an accident, sustains injury, or endures loss. This, by default, means the event has happened, or is occurring randomly rather than according to plan. Whether you’re talking about life insurance or Property & Casualty (P&C), individual or group insurance, insurers collect premiums and issue unilateral contracts that will be executed if a random event occurs. The traditional business model relies on random facts and events, but are they truly random or just out of control today?

Traditional Insurance Business Relies on Lack of Knowledge

For centuries, humans believed in spontaneous generation, coherently synthesized by the well-respected Aristotle. Aristotle explains that lives generate spontaneously from non-living sources such as a piece of tissue. However, in 1859, thanks to a more rigorous experiment, Louis Pasteur inhibited bacterial growth and proved that life wasn’t generated spontaneously from non-living sources. Biogenesis, the generation of life from existing life, was born. Later we discovered that it was much more efficient to heal people by giving them a pill than performing bloodletting; which human characteristics were transmitted from parent to child via DNA; and, more recently, studies are demonstrating how ancestral climates may have shaped the human nose.¹ One day we will probably know how to treat cancer and maybe learn that the gender of a baby is not that random either.

In fact, after investigation, most random events can be explained as non-random. For example, an airplane crash is usually the consequence of technical or human failure that can be avoided or weather that can be anticipated thanks to meteorology. Even a toast landing butter-side down might not be that random, but depends on its weight, shape, and the table height. For years, companies worked hard to analyse and understand car crashes. Their self-driving cars have already driven millions of kilometres. They can potentially save lives and make traditional insurance less relevant.

The traditional insurance business model for the most part still assigns randomness to death, sickness, or accidents but this must change to a more deterministic criterion as our knowledge increases.

Digital Ecosystems Lead a New Era of Knowledge

Data generated by digital ecosystems is the key component for new knowledge. We now generate and record more data than we have for whole generations passed. This evolution improves our ability to acquire knowledge faster especially when we can make the data “talk” to deliver data-driven insight. Data collection has also become much easier since most is automatically generated, recorded, and shared without needing human surveillance or input.

Whether your data is shared by you or by someone else, digital ecosystems live track and record our entire life and its environment: habits, location, weather, health, wealth, family, friends … They know what we say, listen to, write … and some technology has even been announced to be working on reading our thoughts.² Finally, it’s becoming almost impossible for people to lie, cheat, commit fraud, or be fully anonymous when data are cross-checked: for example, according to Facebook³ insights, even if your status is set to “single”, the number and content of discussions will lead to the conclusion that you are dating someone.

The power of digital ecosystems is that they not only focus on specific industry data. They allow the user to use approaches and technologies such as business and artificial intelligence to analyse a huge amount of open and private data from a variety of applications, systems, industries, and government, which helps them to identify more and more sophisticated patterns. At first it might appear to be way too much information but they are not limited to a few characteristics to create groupings that can perfectly describe a person, an event, or an item to reduce margins of error. Even if only a very low percentage of those data are analysed today, they will later help to find new patterns and relationships between facts we ignore today. Compared to traditional insurance companies, big tech companies are much more advanced because of their access to this data and they can compare it over billions of customers.

Data doesn’t lie, but it only delivers the right insight when you know how to handle it. Insurance companies might have been one of the first industries to analyse data, life tables, and statistics to determine premiums with the help of actuaries. However, in this new race to data, knowledge, and sophisticated patterns, they must become data specialists, rely on data-driven insight, and become part of digital ecosystems if they don’t want to be bypassed by new players.

The One who Knows can Anticipate and Influence the Future

Analytics helps to understand what happened and improves knowledge. This knowledge forms different patterns, and can be very powerful: not limited to the past, it can lead its owner to anticipate and influence the future. Vaccines you get to avoid being sick is a good example of something that has been observed, analysed, and is now anticipating and influencing your future health. While some companies are looking to ship you a package before you even buy it,⁴ it’s easy to imagine many cases where data gives insight on what you want before you even ask for it.

Later, patterns might reveal that the formula used to calculate life expectancy can be replaced by a much more complex, accurate, and personal equation of life derived from a series of parameters including your DNA, eating habits, physical activity levels, location, employment, friends, happiness, and health conditions. We still have lots to discover, but remember that thanks to progress, increased knowledge, and better control on events we now live much longer. Crazy science fiction stories from books such as From the Earth to the Moon by Jules Verne or movies like Minority Report have become scientific fact. More recently, by watching eight factors, we discovered that artificial intelligence can predict heart attacks more accurately than the doctor can!⁵

Industry should also use knowledge and anticipation to improve its own processes: why ask people to fill out forms and require exams to get a quote when you can collect it? Why ask them again to claim when you can anticipate it? Those activities have no value for the customer and are “mudas”:⁶ meaning that the client is not willing to pay for that, doesn’t want to wait, and is already too busy or shocked, dealing with the loss of a relative, an accident, or a house fire. Data insight gives insurers the opportunity to anticipate a client’s expectations, bypass forms, process claims in seconds, or even “auto-claim” with smart contracts. This might mean more operational spending because more claims are processed, but it also means better customer satisfaction and less fraud. How high would customer satisfaction be if the customer received coverage without having to apply and get their refund and support without having to claim it?

The biggest value of data and knowledge is not understanding the past but anticipating and shaping the future. Knowledge will not only help to serve clients better, but will lead to big changes in the insurance industry’s business model, pivoting it to anticipation, streaming, real time, and automation.

Coaching, the Future of Insurance

Prevention is more effective than detection and reaction. Clients would be happier if insurers helped them to live longer, healthier, richer lives, while avoiding fire, robberies, and other incidents. For example, instead of paying the life insurance policy to your beneficiary after your death, your insurance company could send you to the hospital right before you had a heart attack. To make it possible, insurers will act as coaches: develop a strong and close relationship with the client, analyse their behaviour, give them instant feedback, and offer rewards to influence behaviour. They will share their knowledge to help others making better products such as food, drugs, cars, and tools, and influence the environment with strategic investments in organic food and healthy activities.

Do people want a personal coach? How will people react if they are tracked 24 hours a day and we tell them what to do? Do they want to know everything rather than preserve a bit of randomness and mystery in life? Coaching can train a bad driver but how do you react when genetics play a role, for example, with chromosome abnormality? What will be the consequence if a client refuses to follow coaching recommendations? Will it remain a recommendation or become mandatory? How will insurer robots deal with racism, sexism, and handicaps? Who will be responsible for decisions?

Moreover, any coach can make mistakes. As with spontaneous generation and many other theories “proven” … before being proven to be wrong. For decades, to prevent people developing potentially deadly peanut allergies, allergists recommended that the young avoid consuming them for as long as possible. However, a study conducted recently demonstrated⁷ that sustained consumption of peanuts beginning in the first 11 months of life was more effective in preventing the development of allergies. Worse, though, is that the previous recommendation of allergists might have contributed to the rise of peanut and other food allergies. How would insurers react if for decades they promoted a lifestyle choice that is then known to have a negative impact on the lives of those people? Beyond the legal challenges, the industry must address a lot of ethical issues.

Insurers should not be limited to only helping clients during the life event, they should also influence the whole life ecosystem. This new value proposition requires insurers to answer new questions, redefine the traditional business model, including key partners, activities and resources, customer relationships, segments, and channels.

Conclusion

Finally, insurance has been considered a good way to transfer and mitigate risks, but is now becoming good at limiting and even avoiding them. The traditional business model focuses on the reaction to adopt in case of a random event but it will not survive the techs. Because of their capacity to find relationships and patterns in the most random data and bring disruptive changes, the traditional insurance business model will be replaced by coaching. It will become a more proactive partnership where an insurance company will be well connected to ecosystems, to support its clients in accomplishing their personal goals, avoiding random risk, and influencing its environment. It will evolve and deal globally and to do so it must be based on trust and address important privacy and ethical questions.