Risk Flow Digest

Risk Flow Digest

Welcome to the first edition of Cytora’s Risk Flow Digest, where we share best practice on how insurers can digitize and optimise their risk processing workflows.


Markel partners with Cytora and achieves +100% productivity uplift?

Markel International , a leading speciality insurer, has partnered with Cytora to evolve their underwriting processes into AI-powered risk flows to automate pre-underwriting activities and perform the upfront risk evaluation so that underwriters receive decision-ready risks.?

We are proud to announce the results of the partnership:

  • 113% Surge in Productivity measured as GWP/FTE?
  • Strategic Quote Turnaround Time Slashed from 24 hours to a swift 2 hours
  • Internal Recognition at Markel's Annual Shareholder event

Read the full case study here: https://lnkd.in/eXpj-srE


The Future of Underwriting has arrived: Cytora and InsTech Joint Event

Did you miss the most attended? InsTech session to date with over 300 participants? You can now listen to The Future of Underwriting panel discussion between Chris Varley (CDO at Allianz UK), Jamie Wilson (Head of Pricing and Innovation, hyperexponential ), Salman Siddiqui (Insurance Practice Lead, Moody's Analytics ) and our very own Juan De Castro (COO at Cytora )? in the latest episode of “Making Risk Flow.” Chaired by Matthew Grant (CEO, InsTech ), this discussion delves into how technology is simplifying the lives of underwriters by streamlining lower-value tasks, providing crucial decision support, and fostering a customer-centric approach.?

Listen to the panel discussion here: https://lnkd.in/d_qgxKtA


Making Risk Flow Podcast season 4

Launched in 2022, Making Risk Flow the podcast aims to bring clarity, know-how and inspiration in driving digital transformation for commercial insurers, paying particular attention to the digitization of risk processing. It is led by our very own Juan de Castro and features very exciting guest appearances of insurance change makers.

Discover the latest episodes of Season 4 here featuring Jeffrey Hayman of R&Q Insurance Holdings Ltd , Jamie Wilson of hyperexponential , Chris Varley of Allianz , Salman Siddiqui of Moody’s Analytics , Bryan Falchuk of Property & Liability Resource Bureau , David Gritz of InsurTechNY and Craig Knightley of Inigo Insurance .?


Meet the Cytora team at ITC Vegas - October 31 to November 2

If you’re attending ITC Vegas this fall, come meet our team to discuss how Cytora empowers insurers to streamline and optimize their underwriting workflows.

Be sure not to miss our CEO, Richard Hartley , who will be part of an engaging panel discussion titled "The Future of Commercial Insurance: Forecasting Disruptive Technologies and Business Models" on November 1st at 10:30 AM.?


Cape Analytics joined the Cytora data ecosystem

We are delighted to announce our recent partnership with CAPE Analytics , a provider of innovative, AI-powered property insights. CAPE Analytics' commercial property data APIs will be accessible on the Cytora platform, enhancing insurers' capabilities to assess and manage risks associated with commercial properties. Read the full press release here. ?


Large Language Models (LLM) operationalised and in production in Cytora platform?

Following a successful release of LLM powered digitization, insurers are now able to take advantage of different LLM-powered digitization actions including extraction, inference, resolution, enrichment and others in their multi-step risk flows.???

The deep context that LLMs brings to understanding risk data is transformative. Inference is a good example. The multi-lingual and LLM powered functionality can be used any time an external party describes something in their own words (e.g. a broker describes property occupancy in free text), but the insurer needs it to be matched to a predefined set of allowed choices, typically driven by things such as the property occupancy code rate tables in the insurer’s internal rating model.?

LLMs bring significant new benefits including the ability for customers to configure and tune digitization workflows with limited training data. Zero shot inference enables customers to go live with inference powered fields in low data environments, reducing upfront implementation costs of deploying new inference models. Continuous model optimization is enabled through generating model training examples from human validation and exception management interactions. Risk professionals can review, approve and reject training examples to provide control and accelerate model performance. Find out more here .

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