How can auto insurers become successful by leveraging data and AI?

Simon Axon, EMEA financial services industry consulting director at Teradata.

Historically, insurers have struggled to draw a profit from auto insurance policies, but the current economic conditions has only made this harder. From supply chain issues, inflation, and the rising number of claims, they have all put an enormous strain on operating costs. Whilst motorists are faced with premium increases of 16 percent or more this year, insurers cannot raise rates significantly due to the current cost-of-living crisis.

Looking inwards, the insurance industry’s own structure is changing. Recent forecasts from McKinsey found that technological advancements are likely to have a significant impact on the auto insurance risk pool in the U.S. by 2030. This is expected to leave traditional insurers with a shrinking share of value. On the other hand, new technologies, including AI-driven opportunities, are enticing new customers with innovative products.

In this, there are big technology players who can use their strong expertise in data. They want to offer seamless, integrated, and high-value services to customers. Also, some auto manufacturers and brands already use sensor data in order to tailor their relationship with drivers. In addition, there are neo-banks and other emerging fintech companies, like Revolut in Ireland, who offer discounted policies to safer drivers based on the data which have been collected from the telematic devices installed in cars.

The drive to innovate

There is currently a race to provide more personalised, flexible, and cost-effective policies to customers but traditional insurers are slow to make the necessary moves. However, traditional insurers have recognised that there is a need to offer tailored, differentiated and value added services to retain profitable customers. In the same vein, IDC found that 72 percent of firms surveyed are prioritising digitalisation, and over half are investing in products that engage drivers more often, such as speed alerts, in order to offer more tailored services.

However, only a few insurers have prioritised the real-time experiences that those in the automotive and retail sectors have already deployed. There are only a small number of leaders creating consistent, automated engagements across customer-facing channels to boost loyalty that are cost-effective to deliver.

The aforementioned IDC report found that only one third of respondents cited that they are developing products for the wider sharing economy, which is one of the most important drivers of growth in digital markets. As well as this, only one in five have plans to share data across internal functions, and one in ten of the respondents are prioritising the segment of one in their marketing.

It is clear that insurers must adapt quickly, or they could find themselves distanced from customer relationships. This has a long term impact in cutting them off from the main sources of incremental revenue increases, which make auto insurance monetarily viable.

What about the opportunities?

Modern vehicles have a number of sensors that provide continuous performance data and also offer insights into individual driver behaviour. The “black boxes” which are used by a number of insurers are becoming outdated in terms of the amount and type and amount of data.

A move beyond this is vehicles being able to self-report accidents directly to insurers. As such, there is an opportunity, and a growing necessity, for insurers to use this data for tailored quotes and usage-based policies. This could lead to creating a wide range of additional personalised services aimed at specific customer segments.

Putting this into practice, McKinsey outlined a hypothetical journey for a U.S. auto insurance customer, which goes through real-time risk calculations and liability shifting among different insured parties focused on autonomous and semi-autonomous driving, with real-time policy pricing. Whilst these services are not yet available, the technology to bring them to life already exists. Therefore, similar data and techniques could be applied to reshape auto insurance norms and create innovative products.

Putting data in the driving seat

If traditional auto insurers are looking to compete with the innovative companies entering the market, they must quickly accelerate their use of data for automation, AI and machine learning. Through collecting and analysing customer, mobility and telemetry data, and using analytics insights from the ecosystem of partners, insurers are able to gain a better grasp of customer behaviour to improve engagement and create more value.

For insurers to truly be successful and thrive in the AI-driven road ahead, they must move from the traditional annual customer renewal process to a more fluid and customer contact cycle to “always-on” and real-time relationships. This includes continuously offering new products and services that create lasting relationships with individuals at their point of need. In order for insurers to achieve this, they must create a strong data culture. They should also invest in an enterprise-wide cloud analytics and data platform leveraging AI that offers the necessary speed and scalability to be able to accurately and rapidly analyse billions of data points in real time.

Image: Canva.

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