Kalepa partners with AmRisc to scale AI underwriting operations
Kalepa, a specialist in AI-powered underwriting, has partnered with AmRisc, a catastrophe-focused MGA, to expand and streamline AmRisc's underwriting operations. The decision followed a rigorous assessment of multiple AI and automation providers, measured on performance, integration speed, accuracy, and long-term value. AmRisc selected Kalepa for precision in live underwriting, quick implementation, and measurable impact.
Why operations teams should care
The partnership targets the bottlenecks that slow down underwriting. Document intake and submission workflows will be streamlined so underwriters can process information faster and make consistent, data-driven decisions.
Kalepa's platform automates core steps, reduces manual effort, and provides insights that support better portfolio outcomes. It integrates with existing systems, giving AmRisc immediate performance gains without disrupting current processes.
What the evaluation proved
AmRisc's President, Laura Beckmann, noted they needed more than a generic AI vendor-they wanted a partner that understands workflow nuance and precision at scale. That requirement led to a hands-on evaluation across complex submission and document types.
According to Mark Hall, Software Engineering Group Lead for AmRisc, Kalepa delivered a proof of concept with accuracy in the mid-to-high 90s across diverse submission and document formats, exceeding internal benchmarks. That level of performance supported the decision to move forward.
Kalepa's CEO and Co-Founder, Paul Monasterio, highlighted AmRisc's leadership in data-driven property underwriting and emphasized a shared focus on precision and speed at scale. The partnership aims to give underwriters reliable tools that improve throughput and decision quality.
Operational impact you can model
- Submission intake and triage: Automated extraction and classification reduce touch time, shrink backlogs, and improve routing.
- Decision support: Structured summaries, risk signals, and document links help underwriters move from data gathering to judgment faster.
- Cycle time and SLAs: Faster quote turnaround with fewer handoffs helps protect response time targets and strengthens broker relationships.
- Quality and consistency: Standardized workflows and transparent reasoning improve auditability and second-line controls.
- Integration: API-driven connections to policy admin, broker portals, and document stores minimize change management and keep teams in familiar tools.
- Rollout and adoption: Underwriter-in-the-loop workflows, phased deployment, and clear KPIs-time-to-quote, hit/bind ratios, and loss ratio stability-support disciplined scaling.
Implementation considerations for Operations
- Define success metrics early: accuracy thresholds, turnaround time targets, exception rates, and user adoption.
- Pilot with representative complexity: include varied lines, regions, and document types to avoid blind spots.
- Plan integrations in layers: start with read-only ingestion, then move to write-back and workflow triggers.
- Establish governance: data security, PII handling, model monitoring, and clear human oversight rules.
- Enable the frontline: concise playbooks, office hours, and rapid feedback loops to refine prompts and outputs.
- Measure ROI continuously: track efficiency gains, reduction in rework, and portfolio quality indicators.
About the companies
Kalepa builds AI software for commercial underwriting, focused on accuracy, transparency, and reliable integration with existing systems. AmRisc is a US-based MGA focused on catastrophe-exposed property risk, known for its data-driven underwriting discipline.
Key takeaways for operations leaders
- Start with clear workflows and measurable targets; let data validate impact, not slideware.
- Prioritize integrations that remove duplicate effort and keep underwriters in their core systems.
- Keep humans in the loop for high-severity decisions; automate the repetitive data work.
- Build a feedback and monitoring loop so accuracy and compliance improve over time.
If you are building team capability in AI-driven operations and underwriting workflows, explore job-focused learning paths at Complete AI Training for practical upskilling.
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