Industrial Insurance Underwriting
VALUE PROPOSITION
- Facilitating near real-time responsiveness to emerging risks by providing up-to-the-minute dashboards and reports of underwriting risks
- Enabling a major Digital Transformation leap, by utilising ELEMENT’s revolutionary Knowledge Graph technology to create a detailed network of client risk characteristics
- Reducing labour-intensive efforts by providing a process-centric, AI-embedded application
Modernisation of the underwriting and risk engineering infrastructure of a leading international insurer specialising in industrial insurance, by automating processes to reduce risk exposure and lower operating expenses
BACKGROUND
The insurer’s manual, ad-hoc approach to risk monitoring impaired its ability to manage emerging risks proactively
The client engagement process required parties to complete paper surveys with onerous questions, delaying issuance and review of policies
Underwriters manually collected information, but were unable to monitor a growing number of data sources (e.g., Internet of Things, data streams, aerial analysis)
TARGETS
- Construct a unified knowledge base about clients, seamlessly correlating all risk-related information to improve risk analysis
- Automate acquisition of sector-specific data to reduce laborious tasks performed by risk engineers
- Set automated alerts for risk-related events (e.g. natural disasters) to proactively reduce insurance incidents via client interaction and advice
ADDRESSING THE NEED
- Assembled a Knowledge Graph that integrates the insurer’s core infrastructure — including the client questionnaire repository, hundreds of public data sources, and billions of media articles, to automatically enrich profiles of insured clients
- Deployed predictive AI models to automatically generate risk-related insights on clients and markets based on a set of attributes and events (e.g. nearby geographic events, such as extreme weather, and competitor-related events, such as M&A)
- Configured Machine Learning algorithms to generate timely alerts for trigger events, such as risk-related news and media mentions — monitored using Natural Language Processing, to proactively reduce insurance incidents
Other Use Cases
