The scenario opened by big data is revolutioning our landmarks and models we are used to think, act, dream, and which have usually built our personal and professional identity. The exponential increase in information sources also pushed companies as well as individuals to evaluate analytics as an alternative model of business growth, rather than an asset or an operating plus.
The Mutualization
This radical metamorphosis poses some basic questions also on the insurance activities, especially when we talk about “mutualization”. So far, this concept has indicated the common sharing of risks and commitments among different actors (the guarantors): but, nowadays, is this process still possible? Does it make sense to talk about mutualization at big-data time?
This scenario is just at the very beginning, but algorithms keep multiplying and are more and more able to calculate what we like to eat, how we prefer to manage our free time, what are our shopping tastes, or even giving us advice on travelling, on how to keep fit and live a healthy life, on our driving attitudes, etc.
How does big data really work? And how did we come to this point?
Starting from the digital traces we constantly leave on the web every day through computers and electronic devices, mathematicians, engineers and analysts are able to write and collect algorithms and data providing insights, intercepting and conditioning our choices.
That's why we get advice and information about which city we would like to visit, which pair of shoes are fashionable this year, which restaurant we booked and how many steps we did in one day.
Usually however, the outputs of these mathematical models are quite rough, though they rapidly improve with the self-learning mechanism.
According to this scenario the principle of mutualization, as we know it today, would no longer exist and be considered as extinct. Still, the insurance industry bases its reason of being on this principle. By “mutualizing” – namely sharing risks with other actors - the price we pay is proportionally lower than the possible damage we could suffer from if a destructive event would occur. But if it becomes possible to determine with a high precision level the price of the risk, then the principle of mutualisation decays.
The Big Transformation
Each of us quantifies a price for each possible risk, which corresponds to the price we are willing to pay for that. But this is also the context in which insurance companies should move, by developing skills on prediction-based analysis relying on big data, something that has never been done before.
The skills required are therefore radically different from those this industry was founded on. As for car companies, which are preferring mechanical engineers to IT, electronics and software experts, in the future of insurance companies, the new required skills will focus on data analysis and on the construction of predictive algorithms. At the same time, the communication must have a social approach, through an empathic attitude that allows to understand where, when and how the client wants to be protected.
A historic change both for the individual resources as well for company's ability to react and rapidly adapt itself to new standards. Another fundamental aspect of this change is not just about its size, but the speed it has to be implemented with: the world around us is changing like never before. Being "connected" 24/7, shopping online, having a job that only two years ago did not exist and having class-mates coming from all over the continents, is nowadays just normal.
We live in an era of "exponential" change where habits continuously change until this will become our "normal routine".
Thus, a first point of reflection arises since human being is linear by nature and interprets changes geometrically: by passing a certain time (X), things are expected to change (Y) predictably, since it is believed to know the first derivative, namely the speed of change that reflects our expectations, experiences and learnings. Shifted into the new context, however, this logic increases the likelihood of making mistakes and making incredibly wrong decisions with exponential repercussions.
Hence the fierce contrast we all live and perceive: on one hand, the need to innovate, test and learn by mistake; on the other, the atavistic aversion to the error that exists in Italian industrial culture.
Anglo-Saxons reinterpreted the word FAIL (Failure) in First Attempt In Learning. In this simple reinterpretation of a word lies a huge cultural change: only companies that will re-interpret themselves, risking and developing an entrepreneurial culture - and so reinventing themsleves- will survive.
In order to be always updated on the innovation topics, please visit natiper.it.
About the author
Gianluca Zanini graduated in Management Engineering at Politecnico di Milano with an E-business Master, he began his career in the insurance sector in Ras in 1995, managing an inter-project team in the field of 'Business Process Reengineering'. He joined AXA in 1997 as organization Analyst for AXA Assicurazioni, as Head of Innovation, E-Business and CRM (2000-2001), Innovation and CRM Development Manager (2001-2003), Business Support Manager 2003-2005), Six Sigma Project Organization Manager (2005-2007), Customers Programs-Quality of Service-Complaints Office and AXA Way-Six Sigma Project (2007-2008). In February 2008 he became Chief Marketing Officer in AXA MPS. In February 2012 he became Executive Head of P&C in AXA MPS. In January 2015 he became General Manager of Quadra Assicurazioni (AXA Italia company dedicated to the development of protection through non-proprietary distribution channels).
He is also Head of Partnership and Innovation Leader of AXA Italia.