Dynamic Claims
Development
Forecasting
Peraison helped Doctors Health Fund automate claims development forecasting by translating the actuarial chain ladder methodology into a dynamic, self-serve capability that predicts incremental claims for months +1 to +11 at month end, without manual actuarial effort.
Leaders can track predicted claims alongside benefits and service volumes, then filter and re-calculate results instantly by product, claim type, clinical category, hospital type, state, and service type to understand what is changing and why.
This replaced a slow whole-of-fund, static monthly process with timely, segment-level insight that improves planning, reserving, and IBNR decision-making.
Month-end claims predictions available immediately, by segment
Delivered dynamic forecasts for months +1 to +11, filterable across key dimensions, so executives can act on emerging trends without waiting for manual outputs.
Reduced actuarial effort & faster turnaround
Removed the recurring manual production of claims lag and development outputs, freeing actuarial capacity for higher-value analysis and advice.
Stronger reserving & financial planning confidence
Provided a governed, consistent methodology aligned to existing actuarial practice, improving confidence in reserving, IBNR estimates, and understanding of claims drivers
across the fund.
Modern Solutions for a changing Insurance landscape
Helping Insurance institutions
accelerate with data & AI
Modernise data foundations across policy, claims, billing, and digital channels to enable cloud adoption and AI readiness. Establish governed data products, reusable pipelines, and scalable platforms so underwriting, claims, and service teams can make faster decisions with trusted, current information.
Unify policyholder, broker, and channel data to improve acquisition, renewal, and retention. Build segmentation, propensity, churn, and next best action models that help teams target the right customers, support intermediary performance, and improve portfolio mix across products and customer segments.
Strengthen risk and compliance outcomes with embedded controls, auditable data, and clear lineage across key processes. Implement model governance, monitoring, and regulatory-aligned workflows to reduce operational risk, improve transparency, and support consistent compliance across jurisdictions and lines of business.
Reduce claims cycle time and improve customer outcomes by redesigning workflows and automating high-volume tasks. Apply intelligent triage, document processing, and exception-led handling to lower cost to serve, improve consistency, and free specialists to focus on complex claims and member support.
Improve underwriting discipline and pricing performance with better risk selection and portfolio visibility. Deploy analytics that monitor loss ratio drivers, exposure shifts, and performance by line, segment, and channel, enabling earlier intervention, stronger pricing adequacy, and more confident growth decisions.
Deliver trusted reporting that supports IFRS 17, solvency, reserving, and management performance needs. Reduce manual reconciliation through controlled data models, automated validation, and consistent definitions so finance and actuarial teams can close faster, explain movement, and report with confidence.
Deliver robust outcomes across policy, claims, and data platforms with modern architecture and stack-agnostic engineering. Use proven accelerators and delivery patterns to integrate core systems, uplift reliability and performance, and enable scalable capability that teams can own and extend.
Our Insurance stories & insights
Explore the real‑world impact of our work across financial services, with stories and insights that reveal how data, AI, and technology deliver measurable outcomes.
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