One Model. One Truth.
One Source for the Whole Company!
Long-tail liability insurers rely on many sources of data and analysis to manage and
assess risks.
ICRFS™ introduces a new standard in long-tail risk management
— delivering a unified,
enterprise-wide perspective.
A Unified, Data-Driven Risk Model
Our Multiple Probabilistic Trend Family (MPTF) modelling framework identifies
a
single, optimal composite model across multiple lines of business
and segments.
The model is driven by the data, with future forecast assumptions made explicit and
auditable.
ICRFS™ explicitly measures and connects:
- Social inflation
- Impact of law reform
- Process volatility
- Trend relationships between Case Reserve Estimates and Paid Losses
- Emerging risks as they develop
- Common drivers across lines
- Volatility correlations between businesses and segments
The above, with the accompanying forecast distribution metrics, enables a genuinely enterprise-wide understanding of risk behaviour.
A Single Point of Reference for the Enterprise
ICRFS™ establishes a single, consistent point of reference for risk metrics across all lines of business, segments, and business units.
Rather than managing disconnected spreadsheets and competing views, decision-makers assess social inflation, volatility, correlations, and assumptions within one coherent framework — ensuring alignment across actuarial, risk, and executive functions.
Built for Decision-Makers and the Actuaries
Who Support Them
ICRFS™ empowers senior management to:
- Interactively explore and interrogate risk characteristics
- Run what-if scenarios and sensitivity analyses in real time
- Understand the implications of emerging trends before they materialise
For actuaries: trends, volatility and volatility correlations are measured from the data – and future assumptions can be directly connected to historical experience.
For executives: risk capital decisions are supported by a transparent, company-wide model that reflects the true risk profile of each portfolio.
Modelling wizard for individual lines
A modelling wizard, optimisation algorithms, and comprehensive statistical diagnostics are used to rapidly identify the optimal, parsimonious model.
The model on a log scale is summarized by four charts:
- Development period trends;
- Accident period trends
- Calendar period trends
- Process volatility
- The impact of emerging risks in real time
