The Insurance Industry: Reacting to a Disrupted Market
16-Apr-24
The Insurance Industry: Reacting to a Disrupted Market As the insurance sector surveys the landscape for 2024 and beyond, there are a number of changes in sight. New technology, extreme events and changing cultures are all shifting the way Property and Casualty insurance needs to operate. Some of these new factors create opportunities, while others create risks; many offer both. Responding to market disruption is nothing new for P&C insurance. While the specific factors may be unprecedented, the insurance sector has always been at the forefront of predicting and responding to new risks. In this article we will look at some of the key elements that are changing (or are set to change) the industry within the next few years. Artificial Intelligence It is impossible to discuss disruptive markets without talking about AI. Artificial Intelligence has been on the scene for a few years now, but as it continues to develop, it brings about innovation and opportunity, while also creating risk, uncertainty, and potential problems. Almost all industries need to adapt to a world where AI is commonplace. AI offers massive opportunity to the insurance industry. It can reduce risk, increase speed and refine processes across the board. AI can interact with clients in a more supportive way than ever, meeting their requirements and even anticipating their needs in a way that has not been possible before. At the same time, lots of clients struggle with the impersonal nature of AI – although this is improving all the time, as it becomes more adept at mimicking human emotional responses. Of course, there are dangers that come with computer learned behaviours. One recognised risk is that AI is vulnerable to using data to inadvertently create an illegal or unethical bias – for example, a bias against a protected group. This could result in fines and legal sanctioning, as well as a significant loss of trust in the methods being used by the industry. As this is already a recognised risk, ...
The MGA Model: Reliable or Redundant?
27-Feb-24
The MGA Model: Reliable or Redundant? Placing over 10% of the UK’s insurance premiums, Managing General Agents have become a fixture of insurance in this country. While MGAs enjoyed a number of years of expansion through recent decades, over the past three years, they have seen a small amount of decline. Some companies may be questioning whether use of MGAs is still a business model that works as we move forwards into 2024. Are there more opportunities for the future of MGAs, or is it time to move on and look at different models? What are MGA’s? MGAs are insurance agents, authorised by insurers to carry out a variety of roles such as underwriting and negotiating contracts on behalf of that insurer. They may also be involved in settling claims or appointing brokers. They work within parameters agreed with the insurer.[i] The partnership between insurers and MGAs can be a very beneficial one. MGAs tend to have specific strengths in their field of expertise, and they can offer insights into particular markets that large insurers may not be able to access as efficiently. Meanwhile, the large insurers can offer capital, flexibility and resources that maximise the insurance offerings for clients and the profitability of the programme. [ii] Is the model declining? Although it is acknowledged that there are lots of benefits to the MGA model, the past three years has seen their growth declining. Insurance DataLab revealed the preliminary findings of its 2022 MGA performance report exclusively in Insurance Times, rating the performance of MGAs based on their financial performance. It showed that while 2020 saw an average growth score of 53.8%, this decreased to 51.6% and 49.4% in 2021 and 2022 respectively. [iii] While this will be of concern to those investing in and managing the MGAs, at the same time it’s important to recognise that the past three years is not a neutral sample to analyse. The insurance industry has had a very challenging few years across the ...
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