Our primary objective is to reduce your total cost of risk and improve decision quality.

We analyze your historical loss data to uncover trends in:

• Frequency
• Severity
• Development patterns
• Exposure-adjusted loss rates

This allows you to better understand your risk profile and present your organization more accurately to the insurance marketplace.

Our work often results in:

• Lower insurance or reinsurance premiums
• Improved underwriting discussions
• Better retention decisions
• Operational improvements tied directly to empirical loss patterns

In addition to delivering detailed analytical reports, we provide consulting support to interpret findings and, when appropriate, assist in presenting results to brokers and underwriters.

Minimum requirement:

• At least 4 years of data
• Preferably 6–10 years
• At least 10 claims per year per coverage for stronger statistical credibility

We provide rigorous analysis of whatever the data support.

However, projection credibility depends on:

• Data stability
• Correlation strength
• Volatility levels
• Claim mix consistency

Where trends are stable and volatility is low, projections can be highly credible. Where variability is extreme, conclusions will be appropriately qualified.

Yes.

We estimate:

• Claim frequency
• Frequency rate per exposure unit
• Projected future frequency
• Frequency development trends

When data show strong correlation and manageable volatility, projected frequency results can be statistically meaningful and decision-useful.

We model your losses across multiple layers and retention levels.

By analyzing different data slices — including loss development factors (LDFs), frequency trends, and severity components — we help present a more credible and nuanced underwriting profile.

This often allows underwriters to:

• Move beyond industry averages
• Recognize favorable enterprise-specific trends
• Price risk more competitively

Clients have achieved meaningful premium reductions when empirical results supported improved risk positioning.

Requirements vary by analysis type.

Incurred Loss Development (ILD)

• Successive annual loss runs for at least 4 years (preferably 6–10, up to 15)
• Common valuation date
• Incurred losses by occurrence year

Loss Forecasting (LF)

• At least 4 years of total incurred losses and claim counts
• Corresponding annual exposure data
• Current and projected exposure estimates

Exposure Data Examples

• Workers’ Compensation: Payroll or number of employees
• Auto Liability: Number of vehicles or vehicle miles
• General Liability: Sales or revenue
• Healthcare: Covered lives (age-segmented if available)
• Aviation: Takeoffs/landings or seat-miles

Raw Excel data is preferred.

Deliverables include:

Loss Development Analyses

• Executive summaries
• Detailed analytical reports
• Comparative retention analyses
• Incurred and paid development factors
• Frequency development factors
• Graphs and full audit trail

Loss Forecasting Analyses

• Projected total losses
• Projected claim frequency
• Projected frequency rates
• Discounted after-tax cash flow modeling
• Sensitivity comparisons across SIR levels
• Complete analytical transparency

All results include visual graphs and detailed component analysis.

Yes. We frequently coordinate directly with brokers to support renewal strategy, retention analysis, and underwriting discussions.

Yes. We can present findings directly and explain the empirical basis of projections and assumptions.

Yes. We can help your team:

• Improve data collection processes
• Standardize reporting formats
• Implement more efficient internal risk analytics workflows

Yes. Where data support it, we can perform location-level, division-level, or segment-level analyses in addition to enterprise-wide modeling.

Yes. We have experience supporting other risk analytics organizations when additional modeling depth is required.

Depends upon the project and the data. It typically ranges from 3 to 10 weeks after receiving all required loss data. Note: Expedited engagements may be available depending on scope and scheduling.

No. We complement actuarial work and often enhance actuarial discussions by providing deeper segmentation and layered modeling.

No. RiskMap® is proprietary intellectual property developed by RAS and is currently used exclusively by RAS.

Yes. Confidentiality agreements are standard prior to data transfer.

Any business that has loss data that meets our requirements.

Examples include transportation, healthcare, manufacturing, restoration, service organizations, multi-location retail, public entities, non-profits, and other organizations with credible historical loss data.