University of Tampere and IBM to collaborate in the field of insurance and risk management
The best artificial intelligence (AI) systems are able to reach astounding achievements. For example, the AI system AlphaGo of Google’s DeepMind company has beaten champions in the board game Go and IBM’s AI Watson has won offline quizzes against people. In limited areas, artificial intelligence is able to diagnose illnesses or conduct economic and juridical analyses better than human experts.
This technological change also makes us think about the contents of education. The specialism in insurance and risk management offered by the Faculty of Management and the Master’s Degree Programme in Human-Technology Interaction at the University of Tampere have reacted by starting collaboration with IBM.
The insurance field meets
artificial intelligence among the first
In recent years, the most visible change in the operations of insurance companies has been digitalisation that enables novel ways of managing customer relations, automatising the processes of insurance activities and utilising the extensive information supporting the business. A similar change will most likely happen in all sectors of society from commerce to health services. There are several reasons why the insurance field is among the first to meet AI and digital times.
To begin with, the insurance business is knowledge-intensive information work. Secondly, the customers of insurance companies make up nearly the entire society. Any kind of change in the behaviour of the clientele might lead to the assessment of the suitability of insurance products and the changes in risks. For example, assigning work tasks with greater risks to robots as well as the automatisation of traffic may shift the emphasis of risks from personal injuries to material damages. At the same time, the need for liability insurances may increase. On the other hand, the internet of things enables risk analysis based on the real-time monitoring of the activities of humans and devices.
Thirdly, in addition to the traditional consortiums between the insurance and banking industries, there have recently been mergers and extensions in other industries, too. Good examples of collaboration between different industries in Finland include the S-Bank and retail trade, the OP Financial Group and car sharing services, the airline Norwegian’s own bank and the insurance company LähiTapiola and health services. This type of integration enables the better use of more versatile consumer data in developing the operations from the customer’s point of view more precisely. Consumer data is quickly becoming the most valuable possession of companies and its use will define the entire playing field in the future.
Startups and large
There has recently been collaboration that combines the economic resources of large finance companies and the novel know-how of startups. In a win-win situation, the more traditional companies are able to be at the cutting edge of development and the startups in the financial sector will benefit from the support they receive for expansion and networking. These types of companies exist in the Tampere region as well.
The significance of this collaboration was also evident in San Jose at the FINOVATE 2017 conference for the technology companies in banking and finance in which the writers of this article participated. During two days, dozens of startups presented their applications and made collaboration agreements with traditional companies.
The conference offered a wide overview of the current and future opportunities of financial technology that focuses on the interaction between humans and technology. Traditional companies were able to quickly introduce several applications developed by startups. For example, applications for voice and face recognition can be used in video negotiations to confirm the identity of the client. Ageism was not present; instead, the ages of the presenters varied from people in their twenties to people in their eighties.
Silicon Valley connected
to the University of Tampere
Understanding technological development often requires broad and multidisciplinary expertise. General understanding of technology will help to conceive possible development trends, whereas substance knowledge from the field will help to find field-specific application possibilities. In the insurance and risk management specialism, we have started to systematically develop practices from this perspective.
As a part of this process, we visited the IBM Research Center in Silicon Valley’s capital, San Jose. The research center cannot be found with GPS – it must be due to security reasons – but a connection to the University of Tampere exists: Jorma Rissanen, a pioneer in information theory who has worked in this research center for the majority of his career, is also an honorary doctor at the University of Tampere.
The presentations of IBM representatives about the company’s research and development operations demonstrated that significant efforts are focused especially on developing artificial intelligence and its applications. In addition to this, Jim Spohrer, Director of IBM Global University Programs Worldwide, emphasised the importance of universities during the technological paradigm change in research, development and education in the insurance field.
A course on AI and insurance
at the University of Tampere
As operational approaches change, companies need highly educated professionals who understand the ongoing changes. On the one hand, research plays a crucial role when such changes are analysed. The new university in Tampere will be able to meet these needs thanks to the variety of fields represented at the university.
In order to meet this need, we will organise a course on the possibilities of AI in insurance for the first time this autumn. The course will focus on practical exercises during which teams of students will develop a new AI application for the field of insurance by using IBM’s Bluemix tool and AI Watson. The course will be organised in cooperation with the Master’s Degree Programme in Human-Technology Interaction, which means that there will be participants with two kinds of backgrounds: both insurance and technology experts.
The course offers students an excellent chance to experience the development process of an application including AI and to deepen their understanding of the possibilities of AI in the insurance business and elsewhere. We believe the course will also spark interest in insurance companies due to the pronounced role of AI.
Faculty of Management/UTA
Professor of Insurance Sciences
Faculty of Management/UTA
Scenario Talonen – The attitudes of consumers matter
Applications of artificial intelligence evolve and learn by analysing large amounts of data, for which human capacity is simply not enough. Thus, the AI applications introduced in business are often based on utilising the information collected from consumers.
However, people’s willingness to give out data should not be taken for granted, which was evident in the statements issued on the proposal for the Transport Code, the new act on transport market regulations in the winter of 2017. The basic idea seems to be that people shy away from Big Brother watching. On the other hand, nowadays the majority of us give out customer and user data for example to social media services without a second thought.
It seems that the practices and ways through which people are willing to give out their own consumer data for companies and AI applications will become the most crucial question. The company that will be able to create the most effective incentives for consumers to give out data, will be strong in the competition in the future. These incentives can include for example using data only to benefit the client when services are developed, emphasising information security or practices related to the ownership of data and control, i.e. the so-called “MyData” thinking.
Scenario Koskinen – A sceptic changed his mind
There is a lot of hype around artificial intelligence. Experience has shown that the effects of new technology are often overestimated and the schedule for their implementation is underestimated. This will probably happen with AI as well. Nevertheless, I believe in the great transformational power of AI in the coming years.
I am a turncoat, or more positively, I have changed my mind in the light of new information. I usually regard visions of the future as entertainment. This has also applied to the suggested claims about AI as a powerful force in changing society. My view has changed thanks to concrete, advanced AI applications. For me, they indicate the great development and application potential of AI. Usually this type of potential will be utilised.
In my own scenario, I define AI as any system capable of some intelligent function. I would estimate that these types of systems will be doing more and more professional level work already in the coming years. In principle, no occupations – not even the creative ones or those requiring social skills – are sheltered from this development.
However, change takes a lot of time, which enables adaptation. For example, self-driving cars will become more common worldwide in the coming years. However, this change will be slow in Finland due to people not changing their cars very often and the low population density (Ilkka Nummelin analysed this in his Master’s thesis). Respectively, the changes caused by AI in the job market will happen slowly and irregularly. I came to this conclusion with the help of postdoctoral researcher Satu Ojala from the Faculty of Social Sciences at the University of Tampere.
In fifty years, at the end of my scenario, AI will have transformed professions, the job market and the rest of society in a fundamental way.