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What's the future of data analytics in insurance?

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Insurance is a data-hungry industry. Data is crucial for assessing risk and calculating premiums based on asset values and customer behaviours. And today, insurers are faced with more data than ever before.

Advanced technologies, such as smart devices and artificial intelligence, are offering new actionable insights to insurers. Smart devices in the home, for instance, monitor security and physical risk in real time - something that was never before possible.

At the same time, customers are becoming more accustomed to sharing their personal data with brands. Data is now used across many industries - from ecommerce and entertainment to banking. And there's evidence - from an Ernst & Young (EY) study - that customers may be more willing to share that information.

In this article, I explore some of the opportunities that advanced analytics offer for insurance - and some ways insurers can keep customers onside. But first I consider the current state of data analytics in insurance and its limitations.

Higher quality data allows insurers to create more accurate profiles of customers and reduce the risk of fraud. For consumers, it promises an improved experience overall, saving time and reducing the number of forms they need to fill out.

In home insurance, insurance companies make risk assessments by looking at the potential cost of a claim. They work this out using data such as a property's value, security, location, and usage. In car insurance, insurers use data on consumers' driving behaviour, their vehicle models, and demographic information such as the postcode a driver lives in.

But as new technology (such as smart connected cars) becomes the norm, there's a lot of data being left on the table. This is detrimental to both insurers and consumers - advanced data could help provide more accurate risk assessments for insurers and (potentially) lower premiums for consumers.

So what are the downsides to how the insurance industry is currently utilising data?

There are 2 main challenges that insurers currently face in their management of data.

1. Insurers are relying on self-reported, often inaccurate, consumer data

Insurers rely on their customers to provide the information they need. But, consumers don't always have that information, making it difficult for an insurer to accurately determine risk.

For instance, how many home insurance customers know their property's rebuild value, or the precise distance of their property from water? This might be valuable information that insurers can use to assess the value and security of a property, but it's not knowledge that's actually widespread.

To overcome inaccurate self-reported data from customers, insurers turn to third parties to provide that data instead. In many cases, third-party data can offer more information than many consumers are able to themselves. For instance, organisations such as Experian can provide credit information, while mapping services will likely have historical data on environmental risk such as floods.

But third parties can't currently supply all the data insurers would like from consumers. That leaves insurers overly dependent on inaccurate self-reported information.

2. Both consumers and insurers aren't always comfortable sharing data

Data privacy is an ongoing issue. A study by EY shows over half of consumers are more conscious of their data since the pandemic.

Furthermore, research from the ABI shows that about 86% of consumers say they're concerned about organisations selling or sharing information about them without permission. More than half say they're uncomfortable even when they've given permission for their data to be shared.

It's not just consumers who are worried about sharing data either. Insurers may often be reluctant to share valuable customer information with other insurers. While it might seem natural to want to guard your data for a competitive advantage, it could be worse for the insurance sector overall.

If insurance customers were able to share data between insurers with ease, it would make the switching process smoother. This might be bad for the minority of dominant insurers, but it opens up a healthy level of competition in the market.

Whatever new technologies are used in the future, there's a clear opportunity for insurers to use data to improve the industry - for customers and insurers.

Here are 3 main technology trends that I expect to affect insurance analytics.

1. Smart home tech and connected cars mean insurers can collect more accurate consumer data

Technology, such as vehicle telematics, have been around for decades. Telematics collects live data on the way policyholders drive, then uses that information to determine customers' premiums.

In the near future, built-in (or black box) telematics are likely to become extinct, making way for connected cars with internet-enabled onboard computers. These vehicles can collect much more data than traditional telematics. For example, cars can already collect live engine diagnostics and even driver heart rates. All of this data could potentially run through analytics tools, and influence insurance premiums.

An increase in live data collection thanks to improved technology isn't just limited to motor insurance, though. In home insurance, smart devices that track domestic data and share it with insurers might be more common. For instance, some providers are offering home insurance that comes with smart devices, such as motion sensors and leak monitors.

These technologies promise new levels of real-time data to not only make premiums more accurate, but also reduce claims. For instance, by detecting leaks, smart sensors could prevent property damage and therefore dramatically reduce the cost of damages.

In the future, smart tech could even inform insurers as soon as there's a problem. This could make submitting a claim effortless for customers and increase profitability for insurers.

2. Insurers can use AI and machine learning to automate claims processing

Data isn't just useful for assessing risk and calculating premiums. Insurers can also use data to improve the whole customer journey.

One area where data can be useful is in processing claims.

Making a claim usually follows a negative experience for customers, such as a car accident. They may be stressed, uncertain about the process, and concerned that a claim may be rejected. A customer would probably welcome more automation in this process.

Challenger companies in insurance have recognised this and are implementing new technology to speed up the claims process. For instance, the US brand Lemonade has recently broken the record for claims management - by processing a claim in just 2 seconds.

Artificial intelligence is at the heart of this process. Lemonade uses data on the consumer and their policy to quickly process the claim. Then they feed it through fraud detection algorithms to verify its legitimacy.

Handling claims isn't going to be entirely automated any time soon. But data-driven AI could help to identify and speed up the claims process for some claims. This is good for both the industry and consumers.

3. Technology like open banking means more data sharing between insurers, helping improve the user experience for customers

In 2018, the Open Banking Directive made it mandatory for banks to share customer data with any approved banks, apps, or service providers that consumers allowed. Since then, these changes have transformed the finance industry, helping customers enjoy a smoother experience and giving banks direct access to their financial data.

But open banking hasn't quite taken off in the insurance industry. Instead, insurers rely on self-reported financial information alongside data sources such as consumer credit ratings. As such, they're not getting the fullest picture of their customers' financial profile.

Easier data sharing within the industry would allow insurers to quickly access consumers' financial information directly from their bank accounts. By allowing insurers access to more third-party information, identity verification would become much more straightforward for customers, and their premiums would be more accurate too.

But there's so much more that this technology can potentially offer. For instance, it could improve customer experience further by making their interaction with insurers more personalised and more integrated. Imagine an app where you could simply update your personal details and have all your insurance policies updated too. It would save a lot of time for everyone.

Technology could seriously improve how insurance analytics are currently handled. But that can only happen if both insurers and consumers are onboard with data sharing.

Ultimately, better technology won't be useful for the insurance industry if consumers don't consent to sharing more of their personal information with insurers.

So what should insurers do to convince consumers to share their data? I think there are 2 crucial strategies:

1. Be clear about the benefits of data for consumers

In many industries, consumers are becoming more willing to share data with companies.

For example, a 2022 study by Global Data & Marketing Alliance found that 46% of consumers globally feel more comfortable sharing data with businesses. That's up from 40% in 2018.

Another study by GlobalData revealed similar results. This found that two-thirds of consumers would only share data on their home with insurers in exchange for financial rewards. Together, these studies show that most respondents would only be willing to share data if there was "a clear benefit to doing so".

Are insurers currently offering a clear benefit to customers?

In the case of products such as black-box insurance, customers are being offered cheaper insurance policies in return for sharing more data. This is attractive to customers who otherwise face high costs - yet the market share for these policies is still limited.

For consumers to get on-board with greater data sharing, insurers need to clearly demonstrate the benefits of sharing this data. This could be in the form of lower premiums and a smoother experience - which leads to higher customer satisfaction.

2. Provide greater transparency over how data is used

For the majority of consumers, it's not always clear how insurers actually use their personal data. To grow trust among their customers, insurers could be more open about their data management processes.

A study by ABI showed that only 13% of consumers say they trust insurers at all. With customers being suspicious of insurers, why would they consent to share even more data? At present, most consumers don't know what their data is used for, who it's shared with, or who owns it.

According to a survey by KPMG, almost half of consumers believe they should own their own driving data. But only 35% of UK auto executives expect the driver or car owner to have ownership over the data their vehicles collect in the future. Clearly, there's a disconnect here.

Insurers can help improve these feelings of trust by providing greater transparency about how they use customer data. They could do this by educating customers about the way they calculate premiums using that data. For instance, they could explain how a driver could benefit from a reduced premium by reducing their driving mileage.

Insurers can also show concretely - through educational content - how data could be used to increase consumer convenience. For example, if customers have a smart home insurance policy that comes with leak monitoring equipment, they could avoid the risk of disastrous damage to their home.

In the ABI study cited above, fewer than 3 in 10 customers said they were confident about how insurance premiums are calculated. By being more transparent with consumers, we can help build trust in the industry.

As mediators between consumers and insurers, price comparison websites (PCWs) play a crucial role in the collection and sharing of data. At Confused.com, we're trying to improve the way data is used in 3 ways.

Firstly, we're using data to help customers access premiums more quickly. PCWs in general enable consumers to quickly compare deals from different insurers without having to re-enter their data each time. But we're speeding up this process even more.

For example, Confused.com's home insurance quick quote service enables existing customers to see quotes in a matter of seconds. If a customer already has a quote for car insurance, we already have access to their data at Confused.com. We can then use that data to give customers an estimate on their home insurance, without them having to re-enter their details.

This can help customers save time, raise awareness of current prices, and remind them to protect their home and belongings. It benefits insurers too, by putting their deals in front of potential new customers.

Secondly, we collect more data than other PCWs by asking customers more questions. This way, we help insurers build more accurate risk profiles of customers - and help consumers get more accurate premiums.

Finally, our award-winning fraud detection mechanisms offer additional reassurance for insurers. Customer data is at the heart of how they work. For example, if a customer has been using Confused.com for a number of years, we can vouch that they're a legitimate customer. This could help to reduce the risk of fraudulent claims.

As data analysis and collection technologies develop, our offering evolves too. We're continually studying the market for new opportunities to serve both insurers and customers.

New technologies for collecting and analysing insurance data are emerging. These new data sources could offer an improved customer experience, more accurate pricing, and a better understanding of risk across the insurance sector.

But if these technologies are to take off, customers need to be willing to share their data. For insurers, that means being clear on how they'll use consumer data - and communicating what the benefits are for the customer.

To stay in the loop about how the industry is adapting, learn more about what we do at Confused.com.

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