John Beal, Senior Vice President, Analytics, Insurance, LexisNexis Risk Solutions talks about the role of AI, ML, and data analytics in the advancement of insurtech
1. Tell us about your role at LexisNexis Risk Solutions
I am responsible for leading the company’s insurance data science teams which develop and services our analytics and modelling products. With more than 25 years of experience in data and analytics across the insurance and financial services industries and market-leading innovations, my team develops incremental predictive uses of existing data and processes. We have a strong focus on developing personal and commercial lines credit-based loss models as well as new non-credit industry solutions.
2. What attracted you to working with insurance providers and car manufacturers on their data strategies?
LexisNexis Risk Solutions products and services are designed to reduce fraud, help consumers find competitive insurance cover with minimal friction, mitigate risk, make society safer and — most importantly — safeguard private data. Those fundamental objectives really appeal to me on a personal and professional level. As more data is becoming available, it is vital it is maximised to ensure people are priced fairly and appropriately for the risk they represent. I can play a valuable role in making that happen.
3. Can you elaborate on your career in the tech industry?
Prior to LexisNexis, I held key leadership roles at First Union National Bank in Charlotte, where I was Vice President, Credit and Market Analytics within the Quantitative Analysis Group, and at Citicorp Bankcard, where I served as Assistant Vice President, Credit Policy Department.
4. How is LexisNexis Risk Solutions using AI and machine learning?
As a data, analytics and technology provider, LexisNexis Risk Solutions works with over 90% of the insurance market in the UK and Ireland to support decisions at all stages of the customer journey – from application through to claim – based on the clearest understanding of risk.
Globally, LexisNexis Risk Solutions has 40 years’ experience providing innovative solutions for significant risk data analytics challenges and today works with 7 of the World’s Top 10 Banks, more than 78% of the Fortune 500 companies, 95 of 100 top US personal lines insurers and over 90% of the UK insurance market.
The Insurance industry has been dealing with vast volumes of data for years and our customers are starting to evaluate new data driven solutions to better segment their customers than their competitors can.
Today data, analytics, Artificial Intelligence (AI) and Machine Learning (ML) techniques are helping the market make faster decisions based on more predictive data.
5. What has been the effect of AI and data analytics in insurance claims?
AI AND ML TECHNIQUES ARE HELPING CONSUMERS TAKE ADVANTAGE OF THEIR INDIVIDUAL DATA POINTS WHICH IN TURN PROVIDE THE MOST ACCURATE AND UPDATED VIEW TO THE INSURANCE PROVIDERS THEY CHOOSE TO INTERACT WITH ON THEIR OWN SCHEDULE.
A good example is the way driving behaviour data from aftermarket devices, or from newer vehicles that are able to provide driving behaviour directly from their own computer systems, gives a clearer picture of someone’s driving risk on the road. Drivers then benefit from being judged based on their individual behaviours, rather than paying premiums based on average driving habits.
This requires transparency. Each time a consumer applies for insurance they consent to their data being used to provide the insurer with the best information possible, so they can set an appropriate premium based on the risk. Within insurance, we are focusing more than ever on educating consumers about how their data can be used and evaluated in a way they control and understand. AI and ML automate and process the data consumers are happy to share – supporting greater choice, improved fairness and reduced friction with more personalised insurance protection.
6. What are the biggest barriers to successful modelling/data analytics and how can they be solved?
A big misconception in the industry is that big data and analytics driven products will replace human capital. Data-driven products allow insurance companies to streamline their existing processes and are meant to complement their existing workflow. Human judgment and expertise will always be required to accurately price risk in line with a company’s business strategy. However, data-driven insights can assist with the decision process.
The time it takes to implement or operationalise an analytics solution. There’s always needs to be a balance between availability and accuracy to ensure the product produces the expected outcomes. A natural consequence of technology’s ability to deliver solutions quicker each year creates a challenge to continue to find ways to expedite our processes.
7. What has been the most exciting development for your team in the past year?
One of the most exciting innovations in motor insurance is how connected car and vehicle build data is set to become part of the quote process. The work to bring Advanced Driver Assistance Systems (ADAS) data into the insurance ecosystem is well advanced, and soon motor insurance providers will be able to factor for each vehicle’s unique combination of safety features. This also presents a fantastic opportunity for the sector to play a part in improving consumer awareness of the presence and function of their car’s ADAS by confirming back to the customer the exact fitments to their vehicle.
From our perspective, 2020 has not stalled innovation it has only accelerated it and that is certainly true in how the market can now build a single customer view based on every previous touch point that individual has had with a provider, through linking and matching technology. Having that single view of the customer benefits the market on so many different levels – from marketing through to claims – but most importantly it unlocks the massive potential of the data insurance providers already hold.
8. How far and how soon do you think the IoT will impact the insurance market?
We see very positive trends in the application for some IoT devices. We have partnered with several home IoT manufacturers and to validate reductions in home insurance claims – both the frequency and severity due to the presence of the device. Also, with more people at home during the pandemic, we’ve seen the severity of home insurance claims reduce. For example, if an IoT escape of water alarm goes off, being there in person to shut off the water can stop an insurance claim becoming very expensive.
However, gathering enough performance or claims data to validate the value of any individual IoT device is an ongoing challenge. It takes time for a device to become widely distributed and the data centrally collected. Once that happens, we do expect to see a need
to standardise and normalise the data collected by the many different devices that are in the marketplace today. The good news is we have been in this business with telematics devices for many years and we have extensive experience creating device generated attributes and scores.
9. What digital innovation do you think will make its mark in the insurance sector in 2021?
Geospatial analytics is an area we think will provide a number of new predictors into our modeling applications. Image recognition is another area we will be looking at and of course, vehicle build attributes and scores hold a lot of promise globally in both pricing and claims areas. Trends and benchmark reporting has been under a spotlight with the impact of COVID-19, but we see this area expanding across the globe.
10. How do you keep pace with the rapidly developing AI tech space?
Aside from the adjustment to homeworking which has entailed lots of video calls with customers and colleagues, the past year has certainly fuelled the appetite for more and more data, attributes, and scores. Insurance providers are hungrier now than they have ever been to evaluate new data driven solutions to better understand and segment their customers.
A significant challenge for insurance providers is any sudden change in consumer behaviour. We all do things we do not even think about as part of our daily routines. Shopping for insurance, driving to work and going to the supermarket are just a few activities that just happened until the pandemic took hold. With very little notice, insurance providers needed to augment and expedite their ability to service their prospects and customers virtually.
This includes prefill solutions, data driven underwriting, pricing applications, and contactless claims processing. Fortunately, we have been developing these solutions for years, so we have been in a good place to help insurance providers interact effectively with their customers and understand how risks have changed as a direct consequence of the pandemic.
11. Tell us about your team and how it supports you
Today, there are over 130 people across various geographies including Europe, Brazil, and China. We continue to invest and expand our footprint into more markets and we expect to continue to grow as the demand for analytically derived products increases globally. We continue to research new areas of opportunities in more mature markets, which would lead to organic growth with new product offerings and data analytics initiatives across the organisation.
However, the size of the team is not as important as the breadth of capabilities we bring to our markets. It is not enough to be able to build new predictive solutions, you need to be able to put new concepts into production quickly and efficiently. In addition, insurance providers need to understand relevant benchmarks to understand how they are performing and where they need to invest. The team offers the range of skills needed to meet these demands.
12. What movie inspires you the most?
Having watched Lion King with my children, I have a greater appreciation for embracing the great circle of life. “Everything you see exists together in a delicate balance As king, you need to understand that balance and respect all the creatures, from the crawling ant to the leaping antelope.” -Mufasa.
Senior Vice President, Analytics, Insurance for LexisNexis Risk Solutions
John Beal is Senior Vice President, Analytics, Insurance, for LexisNexis Risk Solutions. He is responsible for leading the company’s insurance analytics and modeling products and services. With more than 20 years of experience in data and analytics across the insurance and financial services industries and market-leading innovations, Beal and his team develop incremental predictive uses of existing data and processes with a strong focus on developing personal and commercial lines credit-based loss models as well as new non-credit industry solutions.