IRB Brasil Re selects Insurdata platform

London, 19 August 2020 – Insurdata, the award-winning insurtech firm which specialises in the augmentation of peril-specific exposure and risk data via its exposure platform, has today announced that IRB Brasil Re (IRB) has licensed its Insurdata Portal.

IRB, the largest reinsurance company in Latin America and with an expanding presence in the international market, will use the platform to generate precise property geocode information across its global exposures. The company’s catastrophe modelling team will integrate the Portal into its daily risk assessment workflow, boosting the resolution of existing data in real time using Insurdata’s wide range of proprietary technologies.

Capitalising on the enhanced exposure information across both their Latin American and international portfolios, IRB aims to use the technology to increase operational efficiency significantly and benefit from more precise exposure data to drive increased accuracy of catastrophe modelling outputs and exposure accumulation information. The increased data precision will also serve to reduce overall model volatility.

Commenting on the announcement, Luis Brito, Catastrophe Modelling Manager at IRB, said: “We are very excited to be working with Insurdata as we look to enhance the resolution of the global exposure data which supports our underwriting, pricing and portfolio management decisions. That data quality will enable us to maximise the analytical potential of our catastrophe modelling, reduce the associated volatility of modelled outputs and boost our overall underwriting efficiency.”

Jason Futers, CEO, Insurdata, added: “The decision by a company of the scale and sophistication of IRB to adopt our platform is a fantastic endorsement of our technology and exposure methodologies. By enhancing exposure data, our aim is to give underwriters greater confidence in their modelled loss estimates leading to improved risk selection and portfolio management, and ultimately more accurately priced products and stronger balance sheets. We’re delighted to work closely with IRB to integrate our Portal into their data processes, ensuring they fully capitalise on the potential it creates.”

Insurdata and Canopius carry out exposure data resolution study

• Data modelled through Fathom’s flood model on the ModEx cat modelling platform
• Study reveals range of geocoding displacement
• Augmented data sets have marked impact on loss estimates

London, 26 February 2019 – Insurdata has today released the findings of a flood data study conducted with global speciality re/insurer Canopius, flood modelling firm Fathom and ModEx, a catastrophe modelling platform delivered by Simplitium.

The study focused on how augmented property exposure data altered the risk profile of an asset when modelled, and how the revised data sets would impact annual average loss forecasts and maximum event losses for a series of return periods.

“The main aim of the study,” explained Jason Futers, CEO, Insurdata, “was to establish the potential impact on loss estimates at both the individual property level and portfolio level when exposure data is modelled at a much higher resolution than currently available to many re/insurers.”

The sample data provided by Canopius represented a typical raw data set as available in the re/insurance market. The unaugmented address data was originally geocoded to a variety of resolutions from building to zip-code level.

The portfolio included data for approximately 1,000 properties in the Houston, Texas region, with a total insured value of $9.9bn spanning residential, commercial and industrial locations. Some locations had been impacted by the 2017 inland flooding resulting from Hurricane Harvey.

The initial phase of the study involved the creation of four specific data sets, the initial raw location data and three augmented sets which included updated geocode information, building perimeter points, and building attribute data, including first-floor elevation (FFE). These data sets were then modelled through Fathom’s high-resolution flood data model with average annual loss (AAL) and exceedance probability analysis conducted for all locations.

The geocode corrections saw a displacement of five metres or less for 384 exposures. 20 percent of the properties witnessed a geocode displacement of 50 metres or more, while 75 locations were displaced by one kilometre or more resulting in an overall location displacement of 276km for the portfolio. It should however be noted that not all original geocode data supplied was at street level.

Analysis of the augmented property data sets had a significant impact on the annual modelled loss figures:

• The revised geocodes (Set 2) resulted in an 84% increase in the loss estimate
• The addition of the building perimeter data (Set 3) reduced the increase to 76% compared to Set 1, or a 4% decline compared to Set 2
• The addition of the building attribute data, including FFE, (Set 4) saw a 2% decrease in the loss figure compared to Set 1, or a 44% decline compared to Set 3

In terms of the impact on the modelled estimates for the return period loss, for a 1-in-200-year event, the analysis revealed:

• Set 2 analysis resulted in a 42% increase in the estimated loss compared to Set 1
• Set 3 analysis saw an 11% decline compared to Set 2
• Set 4 analysis continued the downward trajectory with a further decline of 37% compared to Set 3

Commenting on the findings, Jason Futers, CEO, Insurdata, said: “As the analysis demonstrates, augmenting property location information with building perimeter data and first-floor elevation measurements, rather than relying upon a single geocode and a default FFE assumption, has a material impact on the modelled loss estimates.”

His comments were echoed by Dr Andrew Smith, Chief Operating Officer, Fathom, who said: “Flooding is one of the most spatially complex phenomena that insurers have to tackle, which makes the ability to map exposures accurately critical to their ability to robustly model such losses.” He continued: “There is no reason why re/insurers should not be using accurate geocode data in their risk analysis.”

Paul Wilkinson, Head of Catastrophe Management, Canopius, concluded: “Current market conditions and narrow profit margins are driving greater focus on risk differentiation and portfolio optimisation. The augmented data metrics generated in this study can help insurers improve risk selection and enhance portfolio makeup, support decision-making around risk quantification and policy conditions, and facilitate the development of new products and more flood-specific coverage. Canopius is fully committed to taking a leading position in efforts to enhance the resolution of the data which underpins our industry.”

A report on the findings entitled “Breaking down the flood data” is available here 

“Our Exposure Engine provides insurers and reinsurers with the resolution and type of data quality essential to maximising the value of today’s high-resolution catastrophe models”
Jeremy Sterns — CTO, Insurdata