Blog 2 : Implementing Artificial Intelligence

The MAIF Case

When addressing the rise of Artificial Intelligence, people forget that this is not a new concept. The beginnings of Artificial Intelligence are traced to philosophy, fiction, and imagination. Early inventions in electronics, engineering, and many other disciplines have influenced AI. 

Artificial intelligence is based on the assumption that the process of human thought can be mechanized, but it is only in 1956 that the field  of Artificial Intelligence research were recognized as an academic discipline. 

From the 1950s to the 1980s, we were talking about Artificial Intelligence, that is to say intelligence exhibited by machines, whereby machines mimic cognitive functions associated with human functions. The era between the 1980s and the 2010s was dedicated to machine learning : data-driven predictions, reinforcement learning, supervised and unsupervised learning. Since the 2010s we are talking about Deep Learning (DL). It connects artificial software-based calculators that approximate the function of brain neurons. 

When talking about AI, the Insurance Sector is not the one that come up first in our minds. However, in reality, it is one of the first to embrace change.

The insurance market is dominated by massive national brands and legacy product lines that haven’t much evolved in decades. The significant development of AI has forced the field to embrace change. For example, a 2015 KPMG report has predicted “radically safer” vehicles entering the market in the following years, including driverless technology. Such a huge move in the market will lead to a shrink in the auto insurance industry by a whopping 60% over the next 25 years. The catastrophe resides in the fact that more than 40% of insurance industry is solely supported by auto insurance.

Let’s focus on the three main trends that will shape the insurance landscape in a more or less close future. 

First, Behavioral Policy Pricing. Ubiquitous Internet of Things (IoT) sensors will provide personalized data to pricing platforms, allowing safer drivers to pay less for auto insurance. Such a way of doing things is called “user-based insurance”. Moreover, connected bracelets will be able to transfer health data to insurances companies that will be able to increase or decrease the insurance price of clients according to the risk their lifestyle is provoking. 

In second we will talk about Customer Experience and Coverage Personalization. In this scenario, AI will enable seamless automated buying experience, using chatbots that can provide customers’ geographic and social data for personalized interactions. The number of agents will decrease and the remaining ones will have a new role as process facilitators and product educators. Agents will use smart personal assistants to optimize their tasks as well as AI- enabled bots to find potential deals with clients. These tools will help agents to support a larger client base while making customer interaction shorter and more meaningful by mixing  in-person, virtual and digital). 

The insurance sector has a wide part taken by claims of all sorts. These types of procedures generally take time to be seen through with a little risk of human mistake (lose of file, wrong description of events, etc.). Online interfaces and virtual claims adjusters will make it more efficient to settle and pay claims following an accident, while simultaneously decreasing the likelihood of fraud. With AI, the turnaround time for resolution of many claims will be measured in minutes rather than in days or weeks. In the future, human claims will focus on a new areas : complex and unusual claims, contested claims where human interaction and negotiation are empowered by analytics and data-driven insights, claims linked to systemic issues and risks created by new technology.

Regarding the Insurance sector adaptation to our way of living, the following paragraph will propose a strategy that might be interesting for MAIF, a French insurance company.

The first step is to create awareness among employees and, above all, among senior management. Such an incremental change, that will be implemented through years, must come with a Top-Down change management. Employees must understand the stakes for established companies : they will disappear if they do not evolve. This change will be implemented with a directive management style as employees must be trained, learn about new objectives and new challenges. 

Board members ad customer-experience teams should invest the time and resources to build a deep understanding of these AI-related technologies. They must be seen as change champions. Management should deploys monitoring tools to make sure people are at ease with new AI tools and completing objectives.

LEWIN’s model might be very useful for insurance companies. The unfreezing step represents the awareness that change is required and vital. A good communication about the state of the market, the main changes that will occur, what AI is and, above all, a comforting tone when talking about the future of job : ensuring people that they will not have to find another job is essential for the good implementation of change.

The movement step takes place when people are being trained and when things are moving and being adjusted. In the insurance sector, we are talking about training sessions, new sets of objectives, a rethinking of the customer relationship and the value proposition of companies. 

Finally, the third step is called refreezing. At the end of these years of changing and adjusting a sector that has not known tremendous change for decades, management needs to set up good practices and get rid of bad ones. AI has to be seen as a useful tools that will change not only the insurance sector but also its consumers’ life. 

To conclude, we could say that AI has a bright future ahead of it. Companies and people has to avoid the pitfalls that come with such technologies. Human beings tend to rely too much on tools that fit perfectly with their lifestyle. AI must be seen as a tool designed for human needs, and not a completely independent entity that would have the last word over claims and others contracts problems.  

The insurance sector possesses all the competencies and resources to face the challenges that will appear and are appearing thanks or because of AI. Thank you for reading this blog and don’t hesitate to leave a comment, we will surely answer quickly.

Loona LOCHARD

2 réflexions au sujet de “Blog 2 : Implementing Artificial Intelligence”

    1. Hello Jamélia !
      Yes indeed, the car industry is one of the most innovative and changing nowadays. But implementing change in these companies is not an easy thing. Moreover, car manufacturers are designing more and more autonomous and « intelligent » car which will deeply change the way we will drive in the future. It is a hot topic and a fascinating subject that I will be happy to write about later !
      – Loona

      J’aime

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