As an insurance executive, you know that natural disasters are on the rise, and the increasing frequency and severity of extreme weather events and natural disasters are driving economic losses. Insurers are investing significantly in catastrophe models and systems to help them better understand and manage their exposures and tailor their prices more closely to such risks. But what if you could access real-time information, machine learning, and expert analysis to provide intelligence that enables data-driven decision making following catastrophic events?

That’s where McKenzie Intelligence Services (MIS) comes in. MIS is a London-based InsurTech that provides insurers with geospatial data and analysis to accelerate industry response to catastrophic events, driving disaster relief and economic recovery. Recently, MIS completed a six-figure investment from Maven Capital Partners to grow its UK market share and increase penetration into the US and European markets.

MIS’s core product offering, the Global Events Observer (GEO), is a proprietary platform that uses real-time information, machine learning, and expert analysis to provide clients with intelligence to enable data-driven decision making following catastrophic events such as wildfires and hurricanes. This allows underwriters to access detailed post-event assessments within 24 hours following an incident.

Forbes McKenzie, founder and CEO at MIS, said: “As catastrophic events across the globe are becoming increasingly common and more severe, insurers are pressured to act more rapidly and effectively than ever before. This investment is an opportunity to reaffirm our mission of delivering accelerated and reliable intelligence for insurers to confidently make decisions in these critical times.”

Here’s how you can use geospatial data to accelerate industry response to catastrophic events:

Step 1: Access Real-Time Information

MIS’s GEO platform provides real-time information on catastrophic events such as wildfires and hurricanes. This allows insurers to access detailed post-event assessments within 24 hours following an incident. By accessing real-time information, insurers can make data-driven decisions quickly and efficiently.

Step 2: Use Machine Learning

MIS’s GEO platform uses machine learning to provide clients with intelligence to enable data-driven decision making following catastrophic events. Machine learning algorithms can analyze large amounts of data quickly and efficiently, providing insurers with insights that would be impossible to obtain manually.

Step 3: Leverage Expert Analysis

MIS’s GEO platform also provides expert analysis to help insurers make data-driven decisions following catastrophic events. Expert analysis can provide insurers with insights that would be impossible to obtain through machine learning alone.

Step 4: Make Data-Driven Decisions

By accessing real-time information, using machine learning, and leveraging expert analysis, insurers can make data-driven decisions quickly and efficiently following catastrophic events. This can help insurers respond more rapidly and effectively than ever before, driving disaster relief and economic recovery.

Step 5: Get in Touch with Riskwolf

If you’re interested in using geospatial data to accelerate industry response to catastrophic events, get in touch with Riskwolf. With Riskwolf, you can turn real-time data into insurance. Using unique real-time data and dynamic risk modeling, we enable insurers to build and operate parametric insurance at scale. Simple. Reliable. Fast.

In conclusion, by using geospatial data to accelerate industry response to catastrophic events, insurers can make data-driven decisions quickly and efficiently, driving disaster relief and economic recovery. If you’re interested in learning more about how geospatial data can help your insurance business, get in touch with Riskwolf today.

Source: Maven invests in London InsurTech to grow its market share