Back office ops · Production

Markel records 113% productivity increase in underwriting team following Cytora partnership

The problem

Markel's underwriting process required senior underwriters to manually triage every incoming submission and re-key risk data across systems, with underwriters spending 30%+ of their time on low-skill tasks — limiting GWP growth without adding headcount.

Workflow diagram · grounded in source
1
Broker submission intake
trigger
“Cytora's Platform that collects broker submissions”
2
Risk data enrichment
integration
“Risks are digitised upfront and augmented with additional data sources, bringing together all data required for risk evaluation”
3
AI risk prioritization
ai_action
“prioritises the risk in the context of Markel's underwriting and distribution strategies”
4
Triage and routing
routing
“Risks are triaged and routed to the right specialist underwriter”
5
Decision-ready risk delivery
output
“Expert underwriters receive decision-ready risks within minutes”
6
Downstream system population
integration
“streamlines the flow of data into downstream systems”
Reported outcome

Markel achieved a 113% uplift in underwriting productivity (GWP/FTE) and reduced SLA quote turnaround time for strategic partners from 24 hours to 2 hours, with underwriters now focused on decision-ready, high-propensity risks.

Reported metrics
underwriting productivity (GWP/FTE)113%
SLA quote turnaround time for strategic partners24hrs to 2hrs
Underwriter time on low-skill/low-value tasks (baseline)30%+
Reported stack
CytoraCytora's PlatformCRMPAS
Source
https://www.cytora.com/risk-flow-center/blog/case-study-markel-records-113-productivity-increase-in-its-underwriting-team-following-cytora-partnership
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Markel achieved a 113% uplift in underwriting productivity (GWP/FTE) and reduced SLA quote turnaround time for strategic partners from 24 hours to 2 hours, with underwriters now focused on decision-ready, high-propens…

What tools did this team use?

Cytora, Cytora's Platform, CRM, PAS.

What results were reported?

underwriting productivity (GWP/FTE): 113%; SLA quote turnaround time for strategic partners: 24hrs to 2hrs; Underwriter time on low-skill/low-value tasks (baseline): 30%+ (source-reported, not independently verified).

How is this back office ops AI workflow structured?

Broker submission intake → Risk data enrichment → AI risk prioritization → Triage and routing → Decision-ready risk delivery → Downstream system population.

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