Of course, many MGAs and carrier/MGA relationships find ways to marry incentives with greater or lesser success. These include profit sharing mechanisms, transparent management information shared and interpreted consistently, binder contracts that respond to certain Key Performance Indicators, and simply a shared mindset and culture of what “good” looks like. These mechanisms can remove the sharp edges of crude rate strength by via product richness, sophisticated rate relativities, and strength of customer and broker relationships.
Be that as it may, the experience and reputation of the MGA model is not pristine. Many respectable insurers simply “don’t do” delegated authority business. Many others are wary as they dip their toe.
Delegated authority, however, has a very powerful case in its favour. By focusing on a narrow product range or customer segment (or means of distribution, for many insurtechs), the MGA brings a focus not possible in large insurers. This focus is a necessary condition for success wherever the insurance proposition doesn’t fit the operational or strategic model of an insurer. Non-core business, operational disruption, management distraction, absence of scale economies: these reasons mean many insurers can’t do what many MGAs do. But it’s still insurance, where successful pricing and underwriting married to successful operations and distribution can make money and deliver growth.
And this is why carriers should love the MGA model: bring what you do well (manage and aggregate risk for profit) to an insurance proposition that you find difficult to accommodate operationally.
Which brings us back to the gap, which can manifest itself in many ways. Sometimes it’s just simply not valuing the same data and MI. Or different success drivers. Or each side having very little awareness of how hard it is to execute the other’s responsibilities: a carrier may think it’s easy to distribute a niche product; an MGA may consider that the pricing is easy compared to customer service. If this gap between the MGA and the carrier can be bridged, the delegated authority model has brilliant opportunities for success for both of them. Calibrant’s objectives are to do this with a combination of relationship and contractual management, and actuarial and analytical insight. We have built our track record working for carriers and have learned some positive and negative lessons along the way. We will share more of our experience and thoughts in future entries in this section.
There has been a lot of speculation recently around the use of AI in insurance and how this signals the death knell for Underwriters. Having mopped up the coffee that I spat out and checked my life insurance provisions, this got me to thinking. Surely not all underwriters? But if not, then who?
The ineffable question of the “effs”. What should a business aim for – and more specifically, for us, the underwriting function in an insurance business – efficient operations or effective decision making?
We have all heard of the boiling frog syndrome which says: if a frog is put in boiling water, it will jump out to protect itself. However, if you place a frog in cold water and slowly turn up the heat, it won’t notice the subtle increase in temperature and be boiled alive.
Game theory aims to shed light on outcomes where multiple actors operate. Dry academe often assumes “ceteris paribus” even in social sciences, but in the real world when we are trying to anticipate the outcomes of decisions one actor makes it is essential to consider the possible and likely responses of other actors…
In various parts of our lives, we are examined and tested to grade our ability and knowledge, be that driving tests, ‘A’ levels, or piano exams.
And so it is with the insurance industry. Boards and regulators are increasingly pushing for demonstrable oversight. This is especially true in the field of Delegated Authority (DA)…
Managing General Agents (MGAs) provide insurers a broad opportunity for profitable growth. Operating in niche sectors with lean efficient models and providing customers with products that they often find hard to come by in the mainstream. All of this is wrapped up with the relevant expertise and providing insurers with access to markets that…
As 2022 was drawing to a close, insurers across the UK were starting to look at their results, keeping their fingers, toes and everything else that they could, crossed in the hope that December would fizzle out in a whimper.
But alas it was not to be as temperatures plummeted and the industry suffered…
What use statisticians and actuaries when the world is being transformed by modern data-analysis techniques? What hope for clunking humans in the era of Big Data (Facebook sells data which influences US presidential elections), of Artificial Intelligence (China can identify disliked racial groups through automatic facial recognition technology)…
Catastrophes – natural events where one “system” (wind, earthquake etc) causes multiple insurance claims in one go – are difficult. Much else in insurance pricing is subject to conceptually simple averaging-over-time, but cats are different. You can’t take a 5 or 10 year history of natural-peril losses and assume you have an accurate view of exposure to catastrophes…
In part 1 of this triptych on insurance pricing we looked at Technical Price (TP): what must be covered over the long run to make reasonable profits. I finished that note by considering TP in the context of the market. Here, I take this theme further and explore more how to think strategically about pricing.
This note covers the fundamentals: the three building blocks of a technical price and a note on the role technical price plays. It is followed with a deeper look at pricing strategies. Finally we consider a knotty topic, cat(astrophe) pricing, in particular the use of cat models to inform the price.
On 26th September 1983, at the height of the Cold War, Soviet missile monitoring picked up apparent signs of five nuclear missiles launched from the US. Retaliation was the default planned reaction.
Charles Dickens opened A Tale of Two Cities with these lines, contrasting calm enlightenment London with turbulent revolutionary Paris: “It was the best of times, it was the worst of times…