Improving underwriting productivity through evidence-driven decision support
About the Customer
Sun Life Philippines is one of the country's leading life insurance providers, offering protection, health, savings, and wealth solutions through a nationwide distribution network. The organization manages large underwriting volumes across a diverse portfolio of life and health insurance products.
Summary
The customer wanted to increase underwriting efficiency without increasing underwriting risk. While rules engines could process straightforward applications, underwriters still spent significant time assembling and reviewing medical evidence before making decisions.
Kamios implemented a recommendation-only underwriting assistant that assembles evidence, summarizes medical information, evaluates manual-rule engagement, and continuously measures performance through a dedicated evaluation framework. Underwriters retain full decision authority while benefiting from better-prepared case files.
The Challenge
The insurer wanted to improve underwriting productivity without compromising underwriting standards. While rules and expertise were already in place, underwriters spent significant time gathering, organizing, and interpreting medical evidence before they could begin evaluating risk. This resulted in:
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01
Time-consuming evidence preparation and review
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02
Medical information spread across multiple sources
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03
Inconsistent case presentation and documentation
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04
Limited ability to measure recommendation quality objectively
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05
The need to maintain full underwriter accountability for decisions
The Kamios Approach
Kamios introduced a recommendation-only underwriting assistant operating under strict human oversight. The platform focuses on evidence preparation and decision support rather than decision automation.
Evidence Assembly
Consolidated medical and underwriting evidence into structured case files.
Rule Evaluation
Identified relevant underwriting rules and supporting evidence.
Risk Profiling
Created structured applicant risk summaries.
Source-Linked Summarization
Generated traceable underwriting summaries.
Evaluation Framework
Tested workflow and model changes against historical cases.
Continuous Improvement
Incorporated underwriter feedback and overrides.
Business Impact
The most important improvement came from better evidence quality rather than greater autonomy.
Underwriters continued making all final decisions, but they did so using more complete, structured, and traceable information. The platform also provided a measurable framework for evaluating changes before deployment. This created confidence in continuous improvement efforts while ensuring underwriting standards remained consistent over time.
Outcomes
- Underwriters gained faster access to relevant evidence.
- Case presentation became more consistent and traceable.
- Time spent preparing cases was reduced.
- Model and workflow changes became easier to evaluate.
- Full underwriting authority remained with human experts.
Who is Kamios?
Kamios is the AI agent orchestration platform purpose-built for Insurance and regulated industries: one governed place for insurers, banks and financial services firms to run AI agents on live cases, from claims and underwriting to onboarding and credit decisions, with every action declared, evidenced and metered. A Neutrinos business, built by founders with decades in insurance and banking technology.