ArticleData Algorithmic Underwriting Machine Learning

Big data: the key to underwriting in the modern world


2020 has been a difficult year for many, and insurers are no different. Luckily, the insurance industry is perfectly poised to flex to the demands of Covid-19.

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2020 has been a difficult year for many, and insurers are no different. While the insurance sector hasn't borne the economic brunt of the pandemic like the leisure and hospitality sectors have, the industry will feel the effects of Covid-19 for some time to come.

Luckily, the insurance industry is perfectly poised to flex to the demands of Covid-19, with new technologies offering innovative ways to introduce efficient, agile working practices which can help insurers to meet the demands of the post-pandemic world while keeping their employees happy and healthy.

What is big data?

Even before the pandemic struck, big data was already making waves in insurance underwriting. We've written before about big data in insurance, which refers to the use of large volumes of data to track patterns and emerging trends.

Cloud computing platforms have for a long time been powerful enough to store huge amounts of data, but data in such large quantities is practically useless without any way to analyse it. Only in recent years has AI caught up, offering insurers a cost-effective way to analyse big data and use it to track patterns and predict trends.

To collect big data, insurers have to think outside the box. Data can be gathered from social media pages, as well as Internet of Things (IoT) devices such as fitness trackers and black box telematics, which can be used in life insurance and car insurance respectively to help underwriters to more accurately predict risk and price fairer premiums.

How is big data used in insurance underwriting?

It's here, in underwriting, that big data's most important applications are realised.

Underwriting has long been seen as one of the most complicated tasks insurers take on, requiring a great deal of judgement and analysis that traditionally could only be achieved by humans.

With the help of artificial intelligence and big data, some aspects of the underwriting process can now be automated. AI software can analyse big data - gathered from a variety of sources - to assess an applicant's suitability for cover and make recommendations for what kind of cover they should be eligible for.

Crucially, this technology isn't about to put any underwriters out of a job: AI isn't capable of making all of the complex decisions that are needed on a daily basis in underwriting. Instead, it can simply complete some of the more low-value tasks that underwriters have traditionally had to complete manually, allowing professionals to spend more time on other tasks.

One such use of big data in insurance underwriting is automated submission triaging.

Using AI, powered by big data, all new submissions and applications can automatically be triaged, with the riskiest applications rejected and the safest applications accepted, leaving human underwriters the difficult task of making decisions on the rest.

This partial automation of the submissions process may sound like a small step, but it means that the time-consuming work of triaging is done automatically and underwriters can spend more time and energy working on higher-value tasks.

Why big data will be key in post-pandemic underwriting

While we're all still hoping for a vaccine to mark an end to the pandemic, certain changes to the way we live and work look set to become at least semi-permanent.

Remote working is becoming the norm, allowing employers to make savings on office lease costs and employees to improve their work-life balance by reducing the need for the daily commute. But this also means that the way insurers operate must change, too.

Big data will drive automation; the more data insurers can gather and use to assess risk and determine premiums, the more successful AI software can be in automating parts of the underwriting and claims processes. Machine learning can even help such software to adjust and improve its algorithms as time passes, spotting new patterns in data and recognising emerging trends.

Insurers are currently working under incredible strain while the pandemic continues, bringing with it periods of increased claims, as well as logistical difficulties in assessing damage and risk safely. Automation can help to ease this strain and bring balance back to the industry.

Consumers are ready for a digital revolution

If there's one faint silver lining to this tragic pandemic, it's that the necessary changes society has had to make have pushed the world to embrace new technologies with more gusto than ever before.

This is already evident in daily life: consumers are paying by contactless more often, with one in five using contactless for the first time during the pandemic.

Online spend has also risen by up to 10% during the pandemic despite overall spend having fallen since March, and 46% of US adults reported shifting to using online banking more than before the pandemic hit.

It's clear that consumers are more open and accepting of new technology in part due to restrictions enforced during the pandemic. If insurers have been looking for the right time to introduce new ways of working, now might be the time to do it.

Millennials are quickly catching up to baby boomers as one of the biggest population groups in the UK, and in other parts of the world they've already taken the top spot. Millennials are keen to see insurers making use of technologies which can add value and offer personalised products to individuals - which is exactly where big data excels.

With brokers across the globe already having to navigate new working practices and more consumers taking the leap into digital services, there's never been a better time to introduce digital change for the better.

For more information on how Artificial can help your business, get in touch.

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