AI – The Challenge for Insurance Companies

Digitalization and industry 4.0 are inextricably linked with information technology. The introduction of modern IT systems is often equated to successful digitalization, but this is a superficial attitude. Latest developments and technologies, such as machine learning, will transform the challenges and work of IT departments in insurance companies.

Functioning IT is an important prerequisite for an economic livelihood of an insurance company. A core task of an insurance company is to process information, and this was the case even before the computer age. All business processes of an insurance company (e.g. from product development, consulting, issuing policies to claims processing) are supported by IT systems.

In recent years, the challenges facing internal IT service providers in insurance companies have clearly increased. Networking of locations via the Internet, work independent of the location by the sales force or use of strategies such as Bring Your Own Device (BYOD) are just some examples. The advent of additional technologies will entail an even stronger reconsideration of work organization and skill development.

IT transformation for artificial intelligence a management task

The signs are unmistakable: The use of the most modern technologies in all areas is gaining importance for the competitiveness of an insurance company. One of the key technologies in this process is artificial intelligence, i.e. the combination of different methods such as pattern recognition, pattern prediction or machine learning.

The first companies are using AI systems to identify possible fraud or process claims. Bots and voice-operated systems are used to communicate with customers. In addition to fulfilling the wish for more flexibility, they help save on costs.

But not every insurance company by far has recognized the urgency of the technological race to catch up as a management task. This is due, in part, to the fact that the radical transformation in the process models is underestimated and no expertise has been built in the necessary areas.

These three areas of activity need to be addressed

The Internet of Things (IoT) will change people’s living environment and, with it, the insurance industry. The connection of more and more devices in our homes and cars will enable new business and insurance models. These approaches will also lead to an upsurge in data volume.

At first, this does not sound novel. A growth in data volumes has been observed for years under the buzzword Big Data. AI systems that make predictions or recognize patters on the basis of data need these large data volumes. But that is the only commonality between AI and solutions for business intelligence. The introduction of AI systems is a little different from data warehousing. For this reason, IT managers and chief information officers (CIOs) in the insurance industry are well-advised to develop skills and expertise in areas of AI as quickly as possible. One important task of modern IT departments will be to securely store the huge data volumes and update them in real-time through various interfaces.

The second challenge is closely related to the huge data volumes, the raw material for machine learning. National and European lawmakers, as well as consumers themselves, expect this data to be acquired, processed and evaluated in adherence to compliance regulations. In case of doubt, information has to be anonymized; precautions need to be taken to rule out the copying or manipulation of data. Ultimately, this requires comprehensive strategies to secure internal IT systems from access by unauthorized third parties or criminals.

Fintech and insurtech companies worldwide are working on new business models and service offers around the traditional business fields of banking and insurance. In recent years, initially critical mutual scrutiny has increasingly resulted in cooperation. An insurance company that accesses the solution of a start-up can put a new service out in the market quicker. Solutions for machine learning and prediction are being offered in the framework of Software as a Service (SaaS). From the insurance companies’ perspective, this is an option to be able to use the know-how for AI faster.

But, at this point, the internal processes of insurance companies and start-ups need to converge. The use of agile methods in software development and project management will be an important condition for success. The development and integration of interfaces for data acquisition and the integration of external systems and services are just two examples of projects whose success is shaped by short phases. With the help of AI, product management departments of insurance companies will be able to develop hypotheses and new offers to consumers. Using agile techniques and organizational forms, the hypotheses can be quickly subjected to a reality check or initial experience can be gathered. Here, speed and flexibility are not optional extras, but a fundamental condition of success.

For more about the challenges and opportunities of AI, read our study “The Future of Property and Casualty Insurance“.