Why Lloyd’s Underwriters Need Better Data
Kacper Bałdyga

Background

In this fast-paced industry that currently faces digital transformation, Lloyd’s underwriters are increasingly finding themselves in need of higher-quality data to make more informed underwriting decisions. It becomes a need rather than an option. While Lloyd’s has long been known for its ability to provide specialized insurance coverage, the market is not immune to the changing landscape of the insurance industry. In this blog piece, we’ll explore one of the most significant needs of Lloyd’s underwriters, and how emerging technologies can help them stay ahead of the curve in the finally changing world of insurance.

Over the centuries, the market has evolved to become a hub for specialized insurance coverage for high-risk and complex risks that traditional insurers may not be willing to cover. Today, the insurance industry is in the midst of a technological revolution, with emerging technologies such as artificial intelligence and big data analytics transforming how insurers underwrite risk.

Lloyd's Underwriters gathered in the Lloyd's of London building

Lloyd’s underwriters need better data

The Future at Lloyd’s strategy envisions a data-focused, automated, and cost-efficient insurance marketplace – Lloyd’s of London Annual Report 2021

This decade embarks on a period of change in the industry. Lloyd’s of London, one of the world’s most-known insurance markets has a rich history that dates back to the 17th century. Lloyd’s Syndicate history started when a group of merchants met at Edward Lloyd’s coffee house in London to discuss shipping news and insurance. The first formal meeting of underwriters at Lloyd’s was held in 1688, and Lloyd’s market has grown and evolved over the centuries into what it is today. One of the most pressing challenges Lloyd’s underwriter face right now is the need for better data. In the past, underwriters have relied on historical data and expert judgment to assess risks and set premiums. However, emerging technologies have made it possible to collect and analyze vast amounts of data to gain insights into previously impossible risks, which is especially important for Lloyds underwriters as The London Market focuses on large, complex, and bespoke risks.

In today’s London Market, insurers are striving to adopt the latest technological advancements that would allow them to fit into the age of real-time data, a way faster and smoother decision-making process, and the road to the “questionless quote”. 

Losses and solutions

“Back in 2017 hailstorms caused significant attritional losses for many syndicates that provided insurance for either small commercial or residential properties in the midwestern states. However, the underwriting process did not always account for pre-existing roof damage, leading to syndicates covering repairs that may not have been caused by the hailstorms. AI prefill data* is an easy solution. Over-outdated tax data to obtain comprehensive rebuild values, evaluate the likelihood of perils, and consider other relevant risk factors. This approach enables a more accurate assessment of the vulnerabilities in the portfolio and allows for property details to be verified during the quoting process” – said Daniel Buda, Account Executive at Tensorflight.

“Weather-related disasters continued to dominate in 2021, with circa $120bn of industry-insured natural peril losses reported. The US was most significantly impacted, with Hurricane Ida and Winter Storm Uri being key drivers of results in this line of business at Lloyd’s. Other regions also experienced extreme events, most notably Bernd in central Europe, where flash flooding and extreme rainfall resulted in insured losses in Germany being greater than any other natural disaster on record.” Lloyd’s of London Annual Report 2021

Modern solutions may provide underwriters with high-quality, reliable data on commercial and residential properties’ construction type, address, replacement cost, year built, occupancy type, and square footage. With the data, underwriters can make more informed decisions about risk, as well as identify and segment property portfolios based on this characteristic. In addition, they can proactively identify underperforming portfolios and take steps to reduce risk and maximize profits. All of this data can be provided almost instantly, through API, reducing costs and amounts of many processes, at the same time accelerating these significantly.

“Tensorflight’s technology offers critical building attributes that will actively help us to transform the way we look at property exposure. The solutions will be the first step in a journey towards redefining the way underwriters interact with locations and exposure” – said Farah Bukhari, Data Analyst at MS Amlin (Lloyd’s of London, Tensorflight’s customer).

Summary

Lloyd’s underwriters require better data due to the changing landscape of the insurance industry. Emerging technologies, such as AI and big data analytics, provide them with vast amounts of data, enabling more informed decisions about risk, portfolio segmentation, and verification of property details. Tensorflight’s AI prefill data is an example of a modern solution that offers critical building attributes for transforming the way underwriters look at property exposure. Without better data, Lloyd’s underwriters may not keep up with the competition and provide specialized insurance coverage for high-risk and complex risks.

About Tensorflight’s AI pre-fill data:

When the user enters a property address, we prefill known attributes, like square footage or construction type. We embed our front end in the process to verify property location and imagery. We are also helping insurers monitor their portfolio to detect risks and prevent losses before they happen (e.g., a roof condition degrading before it transforms into a real issue). 

Sources: Lloyd’s of London Annual Report 2021

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