新たな被保険者（英語版のみ）

自動引受査定および新たなデータソースは、従来は値段が高すぎて利用できなかった、あるいは全く利用する術がなかった多くの人々に保険の利用を可能にしています。

生命保険は、全ての人々が利用できる状態からは程遠い状態です。多くの潜在顧客、特に、既往症がある場合や遺伝子検査で発症する可能性があることがわかっている場合は、保険を探すことが困難です。しかしながら、テクノロジーの進化により、従来は保険が見つからなかった人にふさわしい契約を探す手助けをする個別のリスクを保険会社が正確に評価することが容易になってきています。

「データソース、アルゴリズムおよびよく考えられたコンピュータ・テクノロジーへのアクセスが増すことで、保険業界のプライシングにおける知見が向上します。」と、英国アクチュアリー会損害保険執行委員会（General Insurance Board of the UK’s Institute and Faculty of Actuaries）委員長のMichael Trippは語っています。「自動引受査定は、新たなニッチを特定し、従来は保険にアクセスできなかった人々に保険というオプションを提供することが可能です。」

Technology steps in

Like other sectors, the insurance industry has more technology at its fingertips than ever before. Underwriters can use computer systems to carry out automated underwriting, and these systems are able to analyse huge data sets that can provide a better understanding of the risks the insurer is taking on with each client, as well as offering decisions quickly and often more economically.

The data used in automated underwriting might include figures on life expectancy for different health conditions, or the geographic spread of certain types of claim. It may even include data from social media or Google Earth, all of which can be analysed to reach a more accurate conclusion.

How insurers use data

Whether they are pricing a life insurance policy for a healthy person who has previously had cancer, or considering offering a home policy to a customer whose house has previously flooded, insurers are doing the same thing they have always done: using the information they have available to work out how likely it is that the customer will make a claim, and pricing the policy accordingly.

“Insurance is about making sure the needs of the few fall lightly on the shoulders of the many,” explains Laurie Edmans, one of the UK’s Financial Inclusion Commissioners. He uses the analogy of ships crossing the sea laden with valuable cargo: “an insurer must decide how many of the ships will sink, and therefore what to charge the owner of each one.”

With little information about the state of each ship, insurers would charge them all the same. However if the insurer can work out which of the ships is most likely to sink, it would charge those owners a higher premium. Big Data is what is now giving the industry this valuable extra insight, and could also result in quicker claims processing, shorter policy application requirements and lower premiums.

“Life insurers will be able to gain a more complete picture of a customer’s situation, increasing the accuracy of risk assessments and pricing decisions,” says David Hackett, chief executive of MLC, an Australian life insurance group. “There is enough evidence from other industries, such as healthcare and technology, to show customers are getting better service and products when more information is available. The same benefits could be realised for the life insurance industry.”¹

How data makes a difference

There is evidence that using technology and the insights gained from mining Big Data can make insurance more affordable for some customers who traditionally had very high premiums. In Singapore, for example, insurance companies are looking to use big data to identify underwriting opportunities for those who suffer chronic illnesses such as dementia and obesity, say lawyers at Baker, McKenzie, Wong and Leow.²

In the UK, as described alongside this piece, Big Data is improving insurance outcomes for those with HIV. Analytics show that most people with the disease are likely to live a healthy and long life, and premiums are falling as a result.

As well as bringing down premiums for those who could not previously get insurance, increased automation in the industry has the potential to reduce prices for many others. The industry is already seeing digital-only entrants, particularly in Asia, which offer automated underwriting only, and can compete on cost.

Richard Holloway, managing director South East Asia & India, Life, at Milliman, says that insurance companies in Asia are spending significantly in this area. “There is certainly a lot of visibility around digitalization, and innovation across the industry in the region,” he explains.

“The Singapore government has been supportive of the establishment of ‘digital garages’, ‘incubation centres’ and ‘innovation labs’ in Singapore. I think of it as ‘R&D’ spend, and perhaps in this context the insurance industry is catching up on the lack of R&D spend historically.”

Analysis from McKinsey shows that automated underwriting can significantly improve productivity , which should also bring down costs for consumers.

Ethical considerations

However, there are some concerns about data-driven machines deciding who can have insurance, and at what cost. The UK’s Financial Conduct Authority recently looked into concerns that customers with higher risks would be unable to obtain affordable insurance if Big Data alone is used to decide their premiums.

Christopher Woolard, director of strategy and competition at the FCA, said that these concerns were “not yet materialising”. “However, the FCA will remain alert to the potential exclusion of higher risk customers and will engage with government if concerns begin to develop because of how firms are using Big Data,” he added.

Tripp, at the Institute of Actuaries, agreed. “Given the nature of automation, care must be taken to ensure the system does not exclude groups of people for the wrong reasons,” he said.

This content was produced by FT², the advertising department of the Financial Times, in collaboration with Milliman.