Every month, we help you keep up with the Belgian and Luxembourg insurance markets.

Mergers & acquisitions

• AG and BNP Paribas Fortis are Touring’s new shareholders
• Merger between NN Non-Life Insurance S.A. and Nationale-Nederlanden Schadeverzekeringen Maatschappij N.V.

Partnerships

• Axa and Doctena join forces to strengthen access to health care
• Zurich Insurance Group capabilities joins forces with Belgian insurtech Qover, to expand its embedded insurance capabilities

Market

• Corona Direct becomes Belfius Direct Assurances
• FSMA issues vade mecum on product oversight and governance
• Quarterly overview of Belgian public UCIs
• EIOPA: quarterly risk dashboard of the EU insurance industry

NatCat

• EIOPA published a Staff Paper about the limited uptake of NatCat insurance in Europe
• NatCat law: the limit under which insurers can intervene will be multiplied by 4 to reach €1.6 billion
• Public-private partnership between insurance companies and the European Union to spread the coverage of climate risks
• The AAE issues a new report on Sustainable Products on Insurance

Legislation

• Claims: insurers sanctioned for late reply
• The Economic Committee of the House has passed the law concerning bundled sales

AG and BNP Paribas Fortis are Touring’s new shareholders

This acquisition concerns Touring’s operating activities. AG holds 75% of the shares and BNP 25%.

All operating activities keep the same brand name.

Merger between NN Non-Life Insurance S.A. and Nationale-Nederlanden Schadeverzekeringen Maatschappij N.V.

Subsequent to the merger, these insurances will be carried on without modification in Belgium by NN Non-life, the Belgian branch of Nationale-Nederlanden Schadeverzekering Maatschappij N.V.

NN Group’s strategic vision is to combine all the Dutch non-life insurers in its group into a single strong insurance company. The group also wants to preserve its strong local presence through its branch in Belgium, NN Non-Life.

Axa and Doctena join forces to strengthen access to health care

Axa will add the online calendar of Doctena to its online platform MyAXA Healthcare. Thanks to this partnership, AXA extends its range of health services and provides its policyholders with access to more than 4 600 specialists.

Zurich Insurance Group joins forces with Belgian insurtech Qover, to expand its embedded insurance capabilities

Zurich Insurance entered this partnership through Zurich Global Ventures. According to Qover, this partnership will “push boundaries, providing businesses and individuals even more convenient and timely protection they need in a changing world”.

Corona Direct becomes Belfius Direct Assurances

Corona Direct gets a new name: Belfius Direct Assurances. Corona SA was fully integrated to Belfius Insurance SA and all its insurance portfolio was transferred to Belfius Insurance SA.

FSMA issues vade mecum on product oversight and governance

With this document, the FSMA sets out its recommendations and expectations regarding the supervision and governance of non-life and life insurance products on the topics of value for money and exclusions.
For more information, click here FR/NL.

Quarterly overview of Belgian public UCIs

FSMA has released its quarterly overview of Belgian public UCIs. The authority reports that the total net assets of these UCIs rose by 4.9% compared with the end of 2022, amounting to €193.5 billion. In addition, net subscriptions reached €2.2 billion.

For more information, you can access the report here.

EIOPA: quarterly risk dashboard of the EU insurance industry

EIOPA has recently published its quarterly risk assessment of the EU insurance industry. The Risk Dashboard, based on Solvency II data, summarises the main risks and vulnerabilities in the European Union’s insurance sector through a set of risk indicators.

The data is based on financial stability and prudential reporting collected from insurance groups and solo insurance undertakings.

You can read the full dashboard here.

EIOPA published a Staff Paper about the limited uptake of NatCat insurance in Europe

In this Staff Paper, EIOPA explores ‘demand-side’ barriers that can prevent consumers from buying NatCat insurance and proposes possible consumer-tested solutions to overcome these barriers.

For more information, you can read the Staff Paper here.

NatCat law: the limit under which insurers can intervene will be multiplied by 4 to reach €1.6 billion

A recent change to the NatCat law is that, from January 2024, the limit under which insurers can intervene will be multiplied by 4 to reach €1.6 billion, driven by politicians. However, this does not solve the problem of intervention when the total bill exceeds this limit, as was the case for the floods of 2021. Finally, this change in cap will lead to an increase in fire insurance premiums for policyholders.

Future public-private partnership between insurance companies and the European Union to spread the coverage of climate risks

Amélie Breitburd, CEO of Lloyd’s Europe, recently called for a public-private partnership between insurance companies and the European Union to spread the coverage of climate risks. With the increase in climate disasters, this would help to counter the lack of protection and promote solidarity between European countries, which can sometimes be affected by this risk unexpectedly.

The AAE issues a new report on Sustainable Products on Insurance

With the release of its report on Sustainable Products on Insurance, the European organization wants to make constructive proposals and contribute to the ongoing debate of sustainibility of the insurance sector. The report states constructive proposals and contribute to the ongoing debate of sustainibility of the insurance sector. The report discusses the following topics:

• How the EU’s Sustainable Finance Disclosure Regulation (SFDR) aims to improve transparency about the ESG features of investment-based insurance products.
• What sustainability means for other insurance products, with a focus on insurance risks in Life, Health and Property & Casualty lines.
• How sustainable solutions can be benchmarked against the UN Sustainable Development Goals (SDGs).
• What are the key initiatives to increase transparency, through the use of a sustainable taxonomy and other non-financial reporting standards.

You can read the full report here.

Claims: insurers sanctioned for late reply

The Minister for the Economy has proposed a bill that would require insurers to respond more quickly to policyholders following a claim. If no response is received within three months, a fine of €300 will be imposed. If the policyholder has sent a reminder and has not received a response within 14 days, a fine of €300 per day of delay will appply.

The Economic Committee of the House has passed the law concerning bundled sales

In short, the conditional interest reduction is only authorised for fire insurance, debt balance insurance and surety insurance in bundled sales.

Bundled insurance policies may only be linked to the insurance company and no longer to the insurance broker.

Consumers may cancel grouped insurance policies, without losing the interest reduction, after one-third of the total term of the mortgage, and before one-third of the total term of the mortgage in the event of a rate increase (no ABEX indexation) and claim.

Sources:

• Communiqué de presse, AXA et Doctena s’unissent pour faciliter l’accès aux soins de santé
• Assuropolis, AG et BNP Paribas Fortis officiellement nouveaux actionnaires de Touring
• Press release, EIOPA research sheds light on why households and businesses are reluctant to take out NatCat insurance
• Belfius Direct Assurance, Corona Direct devient Belfius Direct Assurances
• Reinsurance News, Zurich announces partnership with insurtech Qover
• Assuropolis, Dermagne veut sanctionner les assureurs qui tardent à répondre
• Press release, Nationale-Nederlanden Schadeverekeringen Maatschappij NV and NN Non-Life Insurance NV join forces
• Communiqué de presse, La FSMA publie son vade-mecum sur le Product Oversight and Governance (POG) en assurances
• Press release, Evolution of Belgian investment funds in the first quarter of 2023
• L’Echo, Le plafond d’intervention des assureurs multiplié par 4.
• L’Echo, Amélie Breitburd (Lloyd’s Europe) : « Une couverture européenne du risque climatique aurait du sens »
• Assuralia, Ventes groupées : le projet de loi a été débattu et voté par la commission de l’économie de la Chambre
• EIOPA, Risk dashboard 
• Press release, Actuarial Association of Europe publishes AAE Discussion Paper “Sustainable Products in Insurance” 

According to the International Data Corporation, the spending on artificial intelligence will surpass $300 billion in 2026. According to McKinsey, the use of AI will boost productivity and reduce operating costs by 40% by 2030.

Whilst the use of artificial intelligence technologies offers many advantages for insurance companies, the risks associated with them are equally significant, and managing them is essential to ensure that AI is used to best effect and becomes a major breakthrough.

Benefits of artificial intelligence

Pricing and reserving

Thanks to its ability to gather and process a large amount of data, artificial intelligence and its developments are helping to improve pricing methods.

With the implementation of Machine Learning in the insurance industry, the accuracy of data processing used to determine insurance policies has been enhanced, by collecting a vast amount of data, both internal and external, and automating its processing. This tool is already widely used for pricing non-life insurance products and is nothing new to the sector.

The development of AI does, however, give insurers access to data from multiple sources. As a result, the pricing and development of new tailor-made insurance products, or even micro-coverages adapted to specific needs, are positive aspects of the advance of AI in the sector. By using a wide range of data, individual risk can be better predicted and policies can be more accurately priced by increasing the number of parameters taken into account in the models. These insurances, particularly in the car sector, will adapt to the behaviour and activities of policyholders thanks to more detailed data analysis, for example through behavioural dynamic modelling.

Artificial intelligence will connect the insurer and the policyholder in real-time, resulting in the development of a new business model: insurance policies priced, purchased and linked in real-time.

In addition, the development of artificial intelligence techniques also helps to better study the development of portfolio claims, thereby identifying and modelling claims that develop over a longer period and have an impact on the reserving strategy. These techniques can also be used to determine which claims will cost the most quickly. These advances mean that the models used are increasingly accurate, since they take into account the characteristics of claims, resulting in better modelling of the severity component of pricing because the projection of future amounts to be paid is more precise.

Prediction and claims management

In addition to underwriting, the AI breakthrough can significantly contribute to claims prediction and management.

The Machine Learning models developed for claims volume forecasting are already implemented in the current methodology. However, the use of AI could allow almost complete automation of the management process. Indeed, claims analysis could be accelerated, particularly in car insurance, using Deep Learning and damage processing based on images from a smartphone or visual recognition, in addition to the insurer’s historical data.

The algorithms powered by this data can be used to predict and prevent claims, since they will be optimised to detect which policyholders are likely to make a claim and forecast events which could cause claims to be made.

Moreover, AI would facilitate rapid and instant processing of claims handling, compensation and reporting. This would reduce the financial burden on insurance companies and boost customer satisfaction and retention. A concrete example is the case of the American insurtech Lemonade, which is believed to have made the fastest claim settlement in history: in 3 seconds.

Combining artificial intelligence with the volume of data available to insurers could also improve the assessment of other damages at different levels. More specifically, the amount of compensation and the degree of disability for certain types of injury or, on the contrary, the analysis of the reasons for rejecting a claim under health or disability insurance could be simplified.

“AI would facilitate rapid and instant processing of claims handling, compensation and reporting.”

Fraud dectection

The use of AI to detect insurance fraud is an increasingly common practice in the industry. Indeed, one very specific case involves the analysis of claims using sophisticated algorithms to identify potential fraud.

These algorithms can investigate trends and abnormal patterns to detect fraudulent behaviour. These tools include text analysis, which identifies contradictory or inconsistent information in claims. Image analysis identifies changes made to pictures sent to the insurance company to show the damage when a claim is opened. Finally, behavioural pattern analysis can identify unusual or suspicious customer behaviour and can even detect abnormal behaviour from distribution networks.

However, the use of AI to detect insurance fraud raises major issues, such as biased or incomplete data, which can lead to errors in detection, and the issue of confidentiality and protection of customer data. These problems are still being studied in the academic world and improvements are being made.

Its limits for the sector and the actuarial profession

In spite of the non-exhaustive list of benefits described above, the use of artificial intelligence in the sector raises fears and entails risks that we need to be aware of and prepared for.

Compliance and ethical issues

In particular, the use of generative technologies raises compliance and ethical issues, as some of them are based on probabilistic models that are not designed to comply with strict policies. In addition, these technologies collect data to continually refine themselves, which makes it difficult to remove data and information from their knowledge base.

“It is therefore necessary to take the time to understand these systems, which are very often described as “black boxes”. Openng these “black boxes” is possible, but this requires the appropriate specific skills.”

Furthermore, because these technologies predict relevant responses based on observation and replication of what they have been trained on, they can be biased, which can be difficult and costly to correct for the user who is not prepared to deal with this bias. Indeed, in order to detect these biases, it would be necessary to carry out tests to identify these defects in the data set.

However, the use of AI and its consequences are subject to the programmer or user behind the technology, who may also be biased. It is therefore necessary to take the time to understand these systems, which are very often described as “black boxes”. Opening these “black boxes” is possible, but this requires the appropriate specific skills.

The actuarial intuition

When it comes to actuarial intuition, artificial intelligence will not be able to act as a substitute for all the risks impacting the market.  In particular, there are special risks (earthquakes, political risks, etc.) for which little historical data exists and which will always require the expertise of the actuary. In these cases, assessing the risk depends not only on the estimate of the final loss, but also on other factors, such as the buy-back of reinsurance or the company’s solvency requirements, which AI cannot take into account at this stage.

However, AI can in some cases provide new insights to help actuaries make the right decisions. The combination of AI and intuition is therefore key and can be a major help for the actuarial profession.

The interpretation of results 

Beyond these special risks, interpreting the results generated by Deep Learning and Machine Learning models involves a different kind of thinking that implies a knowledge of the business approach that only an actuary familiar with the business can have. Actuaries have the power to contextualize results and explain what they mean by establishing a link with the company’s business and how these results feed into other results.

The sector’s adaptation to the use of artificial intelligence

Artificial intelligence and its many developments are not unknown to the market. Indeed, insurtechs have been pioneers in the use of artificial intelligence since their emergence in the mid-2010s. Over the last few years, insurtechs have become increasingly prominent in the sector because they are prepared to change traditional methods by adopting AI. In particular, Capgemini identifies three types of insurtech in the market: full carriers, which develop new innovative insurance products and distribute them (Alan, Luko, Qover), distributors, and enablers such as Akur8, which provide technological solutions to traditional insurance companies. Insurers will evolve with this changing environment by working more closely with these insurtechs as part of a wider ecosystem and fulfilling new roles within it as directors and providers of “active” insurance products.

In terms of European regulations, the European Union is currently considering a draft regulation known as the AI Act, which would come into force by 2025. Indeed, the law contains an initial requirement for the documentation and assessment of artificial intelligence applications, particularly in the case of life and health insurance, which are defined by the EU as high-risk cases. However, the introduction of the AI Act will have an impact on actuaries and their work. In the future, when selecting statistical models for calculating underwriting risks, classification according to the AI Act will also have to be taken into account and documented.

Broadly speaking, the development of AI is leading to a transformation of the actuarial profession and a move towards hybrid processes. Showing interest in new technologies and new languages (R, Python) are skills that are increasingly sought after in the profession, and this is not surprising as actuaries will always have a key role in analysing data and interpreting it, all in an environment subject to strict regulatory constraints. Actuaries will also have a key role in persuading management of the relevance of the models used and the results produced. This development will also require greater collaboration between traditional actuarial profiles and data science-oriented profiles.

“The development of AI is leading to a transformation of the actuarial profession and a move towards hybrid processes.”

Therefore, the fear of a decrease in demand for actuarial profiles is not yet likely. Actuaries will continue to be crucial to the development of AI within insurance companies. They will be essential in assessing risk, using statistical models to inform the development of AI, validating model, assessing the fairness and accuracy of AI algorithms, and ensuring that AI systems comply with regulations and that they are used ethically. As AI develops, actuaries will be able to develop by adopting the fundamentals of data science, a skill increasingly sought after by insurance companies.

Conclusion

As discussed above, the development of artificial intelligence and its specific features can bring considerable benefits in an increasingly competitive market. All in all, it allows insurers to reduce costs in a number of areas and to be more competitive in the market by offering products that are aligned with policyholders’ needs.

Artificial intelligence is currently transforming the actuarial profession. Consequently, adapting to these technologies and understanding their impact on improving the profession is a challenge that actuaries are facing and will continue to face in the coming months.

Finally, an advantage that we might not think of when we talk about AI is that it will enable us to focus more on the human aspect. Thanks to the automation of calculation and administrative tasks, actuaries will have more time to devote to higher added-value activities, to which artificial intelligence will provide new information that will help the actuary to make decisions.

Sources:

• Insurance Europe, AI in the insurance sector
• McKinsey, Insurance 2030 – The impact of AI on the future of insurance
• Dataconomy, The insurance of insurers
• Mostly AI, AI and machine learning use cases for insurance 2023
• KPMG, Powering insurance with AI
• LinkedIn, How Can ChatGPT Be Used in Insurance?
• Institut des Actuaires, Intelligence Artificielle: vers une mutation des métiers
• Forbes, L’intelligence artificielle et le métier d’actuaire 4.0
• Millenaire 3, Actuariat et intelligence artificielle : l’exemple d’addactis
• The European Actuary
• ProActuary, Will Artificial Intelligence Replace Actuaries?
• Numalis, L’IA dans la finance, les banques et assurances, en vaut-elle l’investissement malgré les défis ?
• L’Echo, L’intelligence artificielle s’immisce dans vos tarifs d’assurance
• ProActuary, AI for Actuaries : What do you need to know?
• ACPR, La transformation numérique dans le secteur français de l’assurance
• Aaa-risk finance, AI : Actuarial Intelligence