Changing the insurance business model while keeping actuaries at its heart

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Insurance companies are working hard to renew their business models. A huge part of that is a modernised approach to actuarial practice, but why and how? I asked my colleague, actuary Diego Rivas.

The insurance business looks like a smooth, calm river from the outside. Is that image misleading?

DR: Most definitely. The insurance market is saturated, and there is tough, even cut-throat, competition. Consumer attitudes have also changed significantly. Customers today no longer see an insurance policy as a good thing, but simply a product like any other, and they often decide on price. Companies can no longer rely on a loyal customer base, especially not when it comes to classic composite insurance. Many consumers today buy insurance through price comparison websites. Increasingly few are choosing the traditional ways of going direct to the insurer or using a broker. Personal relationships no longer matter.

Wasn’t price always the most important issue?

DR: Of course price was always a factor. Today, though, there is huge transparency through the web and especially through comparison sites. And customers are much more open to new supply models. Premiums linked to behaviour, which we are now seeing for health and motor insurance, are becoming much more acceptable, and even attractive, to customers. Newcomers to the insurance business, including car manufacturers or e-commerce providers, have driven a lot of this, and this has increased the pressure on established insurers by using algorithms to develop new models and pricing structures.

Would you say this had given newcomers a competitive advantage in the medium term?

DR: More than that, I think it’s a matter of survival. If insurers continue to calculate their tariffs in the old-fashioned way, their market share will fall and, in the end, many established players may disappear. It isn’t even a matter of jumping on the analytics bandwagon, because the pressure from the market is not the only issue for insurers. They are also under regulatory pressure from IFRS and Solvency II. At the same time, they are suffering from low returns on their own investments. That puts pressure on their profitability. The established infrastructure and processes for pricing cannot always keep up with the dynamics demanded by the market.

What does that mean in practice?

DR: Pricing in insurance is a complex, lengthy process. It starts with “technical” pricing, or the theory behind it, and then flows into market-based pricing. After that come rating and, of course, monitoring. The whole process involves actuarial staff, marketing, sales and IT, so it takes time. And that applies not only to new products but also to changes in tariff optimisation. It usually takes a recoding to map a tariff into the IT systems. That alone can take about four months.

Then actuaries can’t just model a tariff and put it on the market?

DR: No, definitely not. But there are plenty of people who think that should be possible – and much faster than before. The new competitors in the market behave very differently. They are providing products like car insurance based on driving style and travel insurance “to go." If the traditional insurers want to go there, their tariff development will need to be modern, agile and dynamic. In practice, of course, this means that actuaries are suddenly back in the hot seat.

Are you saying that actuaries should be driving the insurance business?

DR: Yes! Actuaries have always been the heart of insurance companies, but now they need to innovate even more. They need powerful tools to bring rating and pricing processes closer to real time. Actuaries rely on agile methods to develop tariffs much faster and bring them into actual production. Techniques like machine learning, for example, have made this much easier. But analytics alone is not going to make insurers customer-centric. The key is for companies to be willing to develop their pricing process.

How will that look on the ground?

DR: Insurers urgently and constantly need new products for existing markets and market niches. With standard methods, this is a bit like searching for a needle in a haystack. With analytics and machine learning, though, an individual actuary can do it. Analytics can help in a wide variety of ways. It makes it possible to include external sources such as telematics data in their models, improving risk assessments. Variable selection for models can also be significantly faster and more accurate. Tariff models also make simulation and benchmarking much easier. Analytical platforms would allow actuaries to work very differently.

Insurers urgently and constantly need new products for existing markets and market niches. With analytics and machine learning, an individual actuary can do it. Click To Tweet

Are insurance companies really ready and able to change their data landscape so radically?

DR: I don’t think they need to. The existing actuarial infrastructure can and should, at least in principle, be fine. You can link an analytical platform to these structures to supplement them, and that would support a range of processes, from data preparation and modelling to real-time pricing. The goal is to make the entire process more efficient and to complement functionalities that are not possible without analytics, such as effective model governance. Insurance companies that are already using analytics platforms provide compelling evidence that this supplementation process works. One company, for example, has been able to make up to 12 possible tariff adjustments per year instead of the previous three, and its IT costs are 20 percent lower. Analytics platforms are very definitely helping to transform insurance while putting actuaries firmly front and centre.

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About Author

Michael Rabin

Michael Rabin assists insurance companys on their way towards digitalization, big data analytics and IoT. Prior to this, he worked as a technical account manager in this segment. He began his career with a German insurer (including businesscontrolling of property / casualty insurance and strategic bankassurance) and is therefore familiar in the field of classic insurance. Michael Rabin unterstützt Sie als SAS Account Advisor für Versicherungsunternehmen auf ihrem Weg in Richtung Digitalisierung, Big Data Analytics und künstlicher Intelligenz. Zuvor war er als Technical Account Manager in diesem Segment tätig. Seine Laufbahn begann er bei einem deutschen Versicherer (u.a. in der Geschäftssteuerung Schaden-/Unfallversicherung und im strategischen Bankenvertrieb) und ist daher auch im Bereich der klassischen Versicherungsthemen zuhause.

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