How data accelerates insurer performance

Rich, diverse data can accelerate the insurance business in the same way it enhances race car performance.

Unlike up-and-coming challengers, existing insurers have a wealth of historical data that can be mined for insights. (Photography: Envision Virgin Racing)

The high-speed, high-tech world of motor sports and the centuries-old insurance industry may seem to have little in common. But there’s a shared fuel powering them both: Data.

In Formula E — the world’s first fully electric, international single-seater street racing series — collecting data is required to even get in the race. Insurance is an industry built on data, too. Without it, insurers wouldn’t be able to predict losses, price risks, or assess claims.

What differs between motor sports and insurance is the speed at which data is captured, structured, analyzed, and acted upon. Formula E teams have just a 45-minute race to turn data into podium positions — giving insurers a lot to learn about performance acceleration from their peers on the track.

A winning combination

From the sport’s first race in 2014, Formula E has always been data-driven. Teams like Envision Virgin Racing have diligently collected and analyzed information on vehicle and driver performance, energy use and more. Despite all this experience with data, the team recognized that more could be done to turn this asset into a true competitive advantage.

Since 2018, Genpact has partnered with Envision Virgin Racing, using artificial intelligence (AI) to analyze vast amounts of data — some of it previously considered unusable — to assess race performance patterns. This helps Envision Virgin Racing become a more instinctive racing team by accelerating its understanding of data, making quicker, more informed decisions on race strategy, and ultimately winning races and collecting championship points.

The data advantage

Insurers, facing increasing disruption from the InsurTech sector, are looking for competitive advantages in today’s marketplace. They may very well find that competitive edge in their existing data sets.

Unlike up-and-coming challengers, existing insurers have a wealth of historical data that can be mined for insights, as well as the resources needed to drive action based on those finding.

Just as Envision Virgin Racing has turned to AI and analytics to generate fresh insights from new and existing data sources, insurers can use these tools to unlock sharper predictions, more accurate risk profiles, and faster claims cycles.

Better outcomes

In racing, decisions are made at 170 miles per hour. Conditions are unpredictable, and millions of possible scenarios can unfold — all of which affect a car’s energy consumption.

Formula E cars are reliant on battery power, so in a 45 minute plus one lap race, managing energy is a critical component of strategy as the driver doesn’t know the exact number of laps to complete at the start of the race. This is an ideal use case for predictive analytics. So Genpact designed a system for Envision Virgin Racing known as the lap estimate optimizer, which predicts the number of laps in a race to optimize energy deployment around the track.

Similarly, insurers using analytics for predictions, forecasts and risk profiles can drive down their losses and overhead.

Pricing, for example, is more accurate when insurers use multiple data sources such as previous claims, customer information and social media to price policies. Here’s another example: With underwriting-related skills becoming scarcer, AI and predictive analytics combined can help individuals speed up the submission and quote-creation process. This not only helps insurers win business, it also provides a better experience for the consumer. Last but not least, fraud is easier to spot if those data sources are in analytics.

Sharper insights

Organizations that are making the most of their analyses are looking beyond traditional data sources for insights. The increased digitization of data means there’s more information than ever before to consider, both within and outside of company databases.

In auto claims, for instance, machine learning algorithms can be trained on hundreds of thousands of images of vehicle damage to assess claims. This allows customers to start the assessment process remotely, and gives insurers another resource to identify claims trends. By looking at alternative or unstructured data sources, today’s insurers can learn a great deal about their customers’ preferences, how claims trends change in relation to lifestyle choices, and new areas that will need coverage in the future.

With today’s technology capabilities, even data that was previously considered too noisy or difficult can become a vital resource. Envision Virgin Racing found something similar this year with race GPS data. Despite housing valuable insights into drivers’ performances, this unstructured data had previously gone underutilized due to its more disorganized nature.

By using the latest AI and analytics tools to carefully clean and filter this data, the teams found that it provides valuable insights into driver tendencies. Customer invoices, GPS data, claims documents and social media could all be hiding similar insights that would help insurers improve pricing and identify new insurance product trends.

The impact of AI

AI offers insurers the opportunity to shift their analytics up a gear and extract every ounce of value from their data. In addition to identifying new ways to use existing information, insurers can free up capacity, speed up underwriting and claims cycles, and overhaul the customer experience. The more precise profiling of risks means carriers can manage reserves more accurately and release capital to invest in growth and new technologies and better compete with InsurTechs.

By automating routine tasks and augmenting decision-making, AI will change the face of the insurance industry over the next 5 to 10 years. According to Genpact’s latest AI research, 87% of insurance carriers are investing more than $5 million in AI-related technologies each year. Although insurers still face challenges in completing their adoption of AI, there are clear benefits to deploying this technology. By embracing AI, and putting data at the center of their organizations, insurers can strengthen value propositions and deliver operational efficiencies.

Whether it’s racing or insurance, performance improves as fresh insights fuel better decisions. Ultimately, it’s the competitors with the strongest insights that will have the best opportunity to accelerate their strategic planning and land at the top of the podium.

Sasha Sanyal (sashas.sanyal@genpact.com) is Genpact’s global business leader for Insurance, Diversity & CSR. These opinions are her own.

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