Successfully deploying AI in commercial lines insurance

This discusson will look at overcoming the operational challenges to drive efficiencies, improve the customer experience and enable profitable growth

Online Teams Meeting

Free to attend  -  Online Teams Meeting

Once you have registered we will send you a calendar invite with the online joining details.


The rapid development of machine learning and AI models to ingest and enrich third party data has provided an opportunity for insurers to streamline customer/broker journeys, remove frictional costs and improve underwriting decisions.

However, the challenge facing commercial lines insurers is how do you overcome the operational challenges to realise the potential of this data, integrate it with existing data and leverage automation and AI to improve performance?

Attend this virtual round table to hear a successful use case for AI in commercial insurance, take part in the subsequent Q&A and discuss how to overcome the operational challenges to enable this transformative technology in your organisation.

Topics to be covered include:

  • Effectively ingesting inbound third-party data enrichment sources to enhance underwriting performance and radically improve the customer or broker journey
  • Leveraging data analytics, machine learning and AI models to intelligently onboard new risks
  • Overcoming the people, processes and technology challenges to become more data driven.
  • Building data and analytics capabilities and using workbenches to better understand risks, the propensity to buy and probable frequency of claims


Emanuele Colonnella
Innovation Lead

11:00 Welcome from chair
11:10 Case study

Case study: Successfully applying GenAI to insurance operations

  • Our world view on AI from a global perspective – opportunities and threats
  • Overview of the use cases and where they have been successful
  • Building the business case and POC
  • Lessons learned and where next for GenAI?




Emanuele Colonnella
Innovation Lead

11:30 Discussion & benchmarking session

12:00pm Close

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