Aon said it has started offering coverage designed to protect income streams for companies with lots of intangible assets, such as firms in the gig economy. LexisNexis is releasing a new data score intended to help insurers more accurately rate and underwrite local fire responses using predictive analytics.

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Aon plc is now offering non-damage business interruption (NDBI) coverage intended to protect income streams for companies in the gig economy, as well as other firms with high levels of intangible assets.

NDBI policies protect companies’ revenues against business interruption costs that result from an event where there is no physical damage. For an increasing number of firms, physical damage is a lesser-risk priority than risks related to income streams and cash flows, such as a terrorist threat, a cyber attack or unseasonal weather.

Structured by Aon’s Innovation & Solutions team, the NDBI product is centered around advanced data and analytics and actuarial analysis. This allows for the development of customized policies for each individual client that can use parametric indices and/or traditional insurance and reinsurance, according to Aon.

An Aon representative said the policy is available for gig economy companies across the globe.

Insurance protection for the new NDBI product is provided by insurers and reinsurers including Lloyd’s of London and Swiss Re, Aon said.

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LexisNexis said its Risk Solutions division is releasing a new data score designed to help insurers more accurately rate and underwrite local fire responses using predictive analytics.

Dubbed the LexisNexis Fire and Disaster Response Score, the product is pitched as something that can help property insurers improve profitability, streamline processes and reduce expenses by leveraging more robust geographic and fire-specific data sources.

The LexisNexis data-driven approach to fire response scoring incorporates cutting-edge geospatial technology, historic fire department responses and loss data, true drive times from responding fire stations, and other data sources to help precisely model the peril of fire. It also provides the level of risk at the location area, LexisNexis said.

By converting this quantifiable data into actionable intelligence, this product estimates an average future loss severity based on fire station response capabilities by segmenting risk into 10 different segments. Nationally, the homes at highest risk for a fire are more than two times riskier than those considered low risk, based on fire response, according to LexisNexis.

Sources: Aon, LexisNexis