How Insurers Can Use Hazard and Behavioural Data

Hazard Data 

Hazard data is the information collected during and after a hazardous event. This includes information on the intensity of an earthquake, soil condition, distance from wildfire, flood depth, and so on. This data can be obtained through a company’s telematics devices or from other third-party agencies, like RMS, Impact Forecasting, JBA, HazardHub, and KatRisk.  

Property and casualty insurers are the biggest consumers of hazard data. Insurers in these industries need this data to assess property risk and price their policies based on an individual’s risk score. Examples of companies using data include AllState and Security First Insurance. 

To start using hazard data, companies should refine internal data instruments or purchase it from third parties (a fairly costly process). Most companies operate a large number of simultaneous data streams, which can quickly overburden a small team. Luckily, software programs and APIs can help alleviate the workload.  

Bottom line 

Hazard data can help property and casualty insurers forecast a property’s susceptibility to disasters. This enables them to price their policies competitively and cut down on losses. Investing in automation and other APIs that process data faster is vital. 

Behavioral Data 

Behavioral data is the information gathered from customers’ actions. Human beings are predictable, and, by watching their behavior patterns, an insurance company can learn how and when they make decisions. This strategic move can help companies target consumers with the right offer or information.  

The main sources of behavioral data are first-party and third-party agents. The former involves lead gathering, cookie tracking, agent interactions, and other in-house data harvesting methods. 

But to get a holistic view of a customer buying journey, insurers need to tap into third-party sources. This data can provide information on how a customer is interacting with other websites, what else they are buying, and how long their journey has been.  

Behavioral data is essential to a variety of insurance industries. For companies just starting off with behavioral data, it is essential to segment data, perform risk modeling, and individually target customers. APIs and predictive analytics can help you manage and analyze this data. Examples of insurance companies using behavioral data in their approaches include Neos, London-based ZEGO, and Lemonade. 

Bottom line 

Highly successful insurance companies like Lemonade are also heavily customer-centric. They rely on behavioral data to tailor their services and meet each client’s expectations. 

 Originally posted here.