Leading insurer modernizes claims management with automated workflows using Insurity ClaimsXPress

An insurance provider deployed Predictive ML for Claims Processing in Property & Casualty. As reported by www.sikich.com: 11 months end-to-end implementation duration.

Maintained by Peter Korpak, Lead EditorHow evidence is checked
11 months end-to-endImplementation Duration
Strong adoption within first month post go-liveUser Adoption

Source-reported figures — cited source: www.sikich.com

What the insurance provider was trying to fix

A leading insurance provider relied on manual, paper-based claims processes that caused slow resolution times, inconsistent handling across lines of business, and limited reporting capabilities. Staff spent significant time on redundant data entry, and compiling reports required days of manual work. These inefficiencies drove up administrative costs and introduced compliance risks.

What the insurance provider deployed

The insurer partnered with Sikich to implement Insurity's ClaimsXPress claims management platform over an 11-month engagement. Sikich designed flexible, automated workflows tailored to multiple business lines, deployed real-time reporting dashboards, and leveraged AI-enabled project delivery methods to accelerate testing and quality assurance.

Results

Claims resolution was streamlined through automated workflows and real-time visibility, replacing multi-day manual reviews. Staff time previously spent on data entry and rework was freed for higher-value tasks, accuracy improved through standardized workflows, and leadership gained real-time visibility into claims data via intuitive dashboards.

Key Takeaways

  • Early stakeholder alignment on process design and user acceptance testing is critical to avoiding costly rework mid-implementation.
  • Structured training and enablement programs are essential for accelerating user adoption after go-live.
  • Balancing flexibility with consistency in platform configuration enables a single system to serve diverse business lines without sacrificing efficiency.

Evidence for the insurance provider's Claims Processing deployment

Reported outcome metrics
2 cited below
Cited source
www.sikich.com
Last updated

Limitation: The cited source does not identify the company.

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Details

AI Technology
Predictive ML
Company Size
MidMarket
Company
Insurance Provider

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