Given that real estate directly and indirectly accounts for roughly one third of the global insurance risk book, the importance of high-quality, accurate and trustworthy real estate-related data in a format that can be readily used by insurers, is evident.
Insurers are among the most sophisticated users of data on the planet, notably in the deep probabilistic models they deploy. At the same time, like other sectors, many insurers face the challenge of sharing and evaluating business information, including importantly real-estate related information, at a speed, scale and level of connectivity that ensures they remain competitive.
There are opportunities at all levels of the risk book for insurers to harness the benefits of AI and other market leading technologies to price and manage direct and indirect real estate risk in a way which is quicker, more accurate and more cost-effective than manual or legacy technology approaches.
Securing Reliable Fundamental Underwriting and Advisory Data Inputs at Scale
Taking the example of underwriting and advisory in areas such as pricing and disaster modelling, real estate data fundamentals include:
- Address validation and precision location;
- Square footage, number of storeys, construction type and materials used, applicable buildings, age and occupancy type;
- Design features including e.g. basements used to store expensive equipment, but susceptible to flood risk; and
- Rebuild cost.
Arriving at reliable data on these types of decision-forming fundamentals requires the extraction, review, validation and conversion of multiple complex data sources in different formats and languages. These sources include:
- Floor plans;
- Building codes;
- Postal information;
- Relevant legal information;
- Satellite imagery;
- Environmental data; and
The challenge here is not so much individual building assessment, but rather being able to deliver these kind of fundamentals at scale, reliably and on a continuously updated basis across broad, potentially international, portfolios.
This level of data ingestion and insight surfacing is beyond human capabilities and beyond conventional computing. But it’s a good example of a task that powerful data and technology platforms like RE5Q deploying A.I. across large, disparate data-sets can get done.
More broadly, many of today’s conversations across sectors are ESG-centric or ESG related. Insurance is no exception, with 41% of the $1.4 trillion losses due to climate perils over the last 30 years, occurring in the last 5 years and ESG insurance-related regulatory requirements and commitments increasingly on the rise.
Some of these conversations are embryonic, others more developed, but Big Data and AI use cases and applications being discussed include:
- Surfacing the full ESG risk suite – in an insurance context not just e.g. flood risk in isolation, but seeing and understanding the full suite of risks together;
- ESG scoring across asset portfolios (including benchmarking versus indices and peers); and
- IoT sensor deployment and connecting point solutions wirelessly (CCTV, HVAC etc) to create deeper unified data pools which enable enhanced energy efficiency and lower carbon footprints and smarter KPIs and measurement – potentially very relevant going forward to premium pricing.
How Can RE5Q Help?
RE5Q enables clients to gain deeper insights into real estate assets and risks, facilitating more informed decisions.
We use next generation AI and adjacent technologies to capture, surface and enrich valuable insights relating to commercial and residential buildings and land more generally. We derive these insights from vast amounts of data, drawn from hundreds of thousands of structured and unstructured data sources in over 240 languages, worldwide, including new bespoke data-sets our smart AIs can create.
Our multi-disciplinary team combines data engineers from the likes of Google and Facebook and experienced industry practitioners, including our CEO, Martin Samworth, the former Chairman of CBRE’s advisory business in APAC and EMEA.
RE5Q’s strong property heritage and industry knowledge informs the depth and breadth of the real estate-related insights it is able to generate. This expertise is versatile and has been just as relevant to, for example, RE5Q’s work with insurers looking at rebuild cost and banks validating their loan books, as it has been to its work with professional real estate owners and managers looking at site location, valuation, risk and ESG compliance, across their portfolios. Proptechs, fintechs or insurtechs can equally use RE5Q’s “data engine” to enhance current offerings, build out new products or enter new territories.
Importantly we can deploy our infrastructure and technologies in a versatile and seamless way that works with and around insurers’ existing systems and, critically, does not cut across existing in-house system workflows or models. We can work on prem, hybrid or in the cloud, in all cases with military-grade levels of security.
With around 70-90% of the world’s data still locked away in legacy paper and digital format such as PDFs, documents and old databases, we are still very much in the foothills of the opportunity here. Insurers that leverage the power of Big Data and AI through professional-grade real estate-related data and technology platforms like RE5Q, will gain competitive edge, including crucially in the pivotal areas of underwriting and advisory and increasingly ESG.