Current Situation
Hurricanes, earthquakes, storms, tornados, fire, but also civil unrest, political conflicts, and pandemic scenarios are only a few of the worldwide fears that seem to be shaking the concrete foundations of any organization’s survival. Getting commercial protection coverage, which may be deemed as the simplest option organizations have in the short run, at least looking at the financial repercussions of commercial real estate perils, does, unfortunately, fail to deliver an efficient answer owing to the intrinsic complexity of commercial underwriting practice: exposures are heterogeneous, intermediated, and often based on qualitative assessments. In addition, risk outcomes are not binary, policy wording and exclusions may seem straightforward until they are challenged by litigation and subject to interpretation. Because of these dynamics, the commercial property segment exhibits a remarkable protection gap that is pushing Insurance leaders to scout for current technological opportunities that might provide support against such a troublesome book of business.
Goals and Objectives
The most impactful application of digital twins in the commercial property line of business has to do with the capacity to improve the accuracy of portfolio data, allowing insurers to carry out risk-weighted underwriting and ratemaking practices, reduce losses, and create for the first time the chance to offer risk prediction and prevention services by continuously monitoring risk exposure and external dynamics. Digital twins can also deliver real value in the underwriting of parametric insurance products. Applying AI and satellite image analysis across a commercial property portfolio, insurers can identify potential sudden events that might represent losses and automatically verify whether that loss is covered by the insurance policy contract and potentially execute the Claim Settlement with Straight-Through-Processing methods. Digital twins, and specifically the underlying digital thread, may help in tracking as a pull for process mining, namely, exploring process’ real workflows and performances; identifying loops, redundancies, duplications, and generically speaking bottlenecks; and potentially optimizing those processes accordingly. Once a claim has been reported, drawing on the continuous inward streaming of IoT data, digital twins offer insurers the opportunity to genuinely replicate the environment in which the damage occurred and assess whether the claim is fraudulent. Digital twin technology also gives the possibility to better adapt insurance coverage plan in accordance with the real monitored usage. Ultimately, this proposition is about the possibility to create specific coverage bundles that are personalized in accordance with the real need of the insured, clearly affecting customer satisfaction and experience.
Technology Deployed
Geo-spatial intelligence
Big Data
IoT analytics
AR/VR interactive technologies
Cognitive technologies
Next-gen security
Cloud
API architecture
Mobile technologies
5G
Use Case Summary
Leaders must acknowledge the existential threat of climate change on their people and business operations: for instance, a warming planet creates a wide range of risks for businesses, from disrupted supply chains (e.g., scarcity/cost of resources) to operational impact (e.g., facilities damage and workforce disruption) along with the realization that environmental sustainability efforts are becoming the core tenets of any company’s culture and brand identity. With the introduction of low-cost cloud computing, faster data processing and advances in artificial intelligence for data extraction and image analysis, it is now possible to accurately develop digital models of risk at commercial properties without even having to visit them.