Insurance is a complex business, predicated on large volumes of data and complex risk analysis. Developing semi or fully automated systems has started to take off in the last few years, thanks to huge advances in artificial intelligence (AI) technologies that are now mature and adaptable enough to have a wide range of data analysis uses on the latest digital insurance platforms.
Mark Colonnese, Director, Aquarium Software
Mark Colonnese, a director at Aquarium Software has advocated how the insurance industry can benefit from digital technology since he joined the company as a start-up almost 14 years ago. Now, Aquarium Software has insurance customers in the UK, Australia, and North America with a strategic focus on the fast-growing pet insurance sector.
In this guest post for The Fintech Times, Mark explains how using AI and machine learning (ML) is an essential component of fully automated insurance and why the use of these technologies offers benefits for customers and insurers alike.
Automation can help substantially reduce the costs incurred in the manual administration of policies from sales, renewals to claims. This means greater operational efficiency for insurers, resulting in lower policy premiums for the customer – a significant competitive edge in a fiercely competitive marketplace.
AI and ML technologies are indispensable tools for automated insurance platforms, where there is the need to replace human data analysis.
Much of the current focus is on claims management, where insurers are tapping into technologies such as AI and ML to replace traditional paper and labour-intensive processes delivering better customer experiences.
In the early days, AI-based platforms required very specialist knowledge and gave mixed results. Now, AI is more reliable and able to more accurately mimic human thought processes. ML is considered a subset of AI, where software automatically learns from data analysis and improves its sophistication over time. These technologies have the capability to make intelligent human-like decisions but far faster than people could realistically achieve.
One notable benefit is the speed and accuracy at which claims can be settled or policy quotes issued. Using AI and machine learning enables insurers to settle all but the most anomalous claims within seconds through an automated process; there is no need for human intervention.
Even for claims that fall outside standard parameters, AI enables insurers to assess these with a few clicks of a button rather than realms of time-consuming paperwork. From the end customer perspective, an insurance claim that is paid automatically within seconds provides an enhanced and hassle-free experience.
Imagine a vet advises someone that their pet needs an immediate operation costing £800. The vet inputs all the details of the treatment required, sends this to the insurer that analyses the age of the pet, the treatment required, the time needed to perform the operation, the average cost of such treatment both from this vet and others in the region and nationally. Drawing on AI and ML to analyse this data, the insurer’s platform recognises this is a legitimate claim, within the parameters set and responds with an approval code for the vet in near real time. The policyholder is asked to pay the excess and receives a text message telling them the claim is paid and how much cover is left on the policy.
The same principles can be used in a broader range of insurance sectors including household, car, medical and travel claims: customers could make a household claim, have this paid within minutes and a repair company booked at the same time; and a medical insurance claim could be analysed and authorised without the need for paperwork or multiple calls into different call centre agents.
AI technologies are not without their challenges; there is a long way to go before they reach their full potential. Insurtech companies still need to invest in getting models trained up to specific business needs and to ensure that AI and ML software is using optimal data sets. There is a way to go on developing self-service claims applications from mobile phones. Foremost here is customer-centric design and tailoring AI to support real-time data management for mobile devices.
2021 is a pivotal year for insurers in all sectors deciding whether to capitalise on AI technologies. There is no doubt that these have matured enough to deploy and use at scale throughout the industry, and we are excited about the possibilities that AI will offer as this develops further. As no one insurer, customer – or in our case pet – are the same, sophisticated data analysis will enable more innovation and customisation that will address pain points for customers and change the face of the traditional insurance experience.
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