Category: Loss Development and Trend

The Analytically Based - Data Driven Broker: Reserve and Cash Flow Analyses

Blog 1: Intro to SIGMA & Scope and Data Requirements Blog 2: Loss Development Factors Blog 3: Reserve and Cash Flow Analyses Blog 4: Trending, Pure Loss Rates, and Loss Projections Blog 5: Confidence Interval and Retention Level Analyses Blog 6: Loss Cost Analysis Now that we understand the data necessary for an actuarial analysis […]

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The Analytically Based – Data Driven Broker: Loss Development Factors

Blog 1: Intro to SIGMA & Scope and Data Requirements Blog 2: Loss Development Factors Blog 3: Reserve and Cash Flow Analyses Blog 4: Trending, Pure Loss Rates, and Loss Projections Blog 5: Confidence Interval and Retention Level Analyses Blog 6: Loss Cost Analysis In our previous blog post, we covered one of the first steps in creating […]

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Understanding Confidence Intervals

Seeing the Big Picture While a loss pick or point estimate produced from accurate analysis by an experienced actuary is valuable information, its usefulness is tempered by the likelihood of how accurate the estimate is. That is, from a statistical standpoint, the loss pick has a certain probability of being correct. That probability, measured in a confidence interval, is […]

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Analytics for Non-traditional Captive Risks

After attending the Fall 2015 Hawaii Captive Insurance Council meeting and the Spring 2016 CICA captive meeting, I became increasingly aware of the continued trend of placing non-traditional1 risks in captives. At SIGMA, we are seeing a growing number of captives formed with a sole focus on non-traditional risks. We are also noticing a large […]

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Forecasting Losses

Trending to the Future In a prior blog article, we discussed loss development factors and IBNR analysis. The IBNR analysis includes the estimation of ultimate incurred losses for past years, but what about future years? If we also have an estimate of exposures, then we can compute pure loss rates (trended losses per some unit […]

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Cyber Risk emerges in the Property & Casualty Market - Reflections on a Year of Education and Research

Cyber risk is likely the most significant property casualty risk to emerge in recent times. Premiums for cyber risk are growing significantly, and daily headlines bring attention to yet another major data breach affecting an entity. Most of us with credit cards have probably had new cards issued because of a breach in the last […]

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Gross vs. Net Retained Reserves: Considerations for Year End 2015 Actuarial Reports

Many companies have a liability associated with retained losses through self-insured retentions or large deductible programs for a wide array of risks. These can include workers compensation, automobile liability, general liability, medical professional liability, and property. Most companies use an actuarial report to determine the net retained liabilities for these risks. However, many auditors and […]

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Conversation on Loss Development Factors

I have found that interviews can often produce interesting results and insights. So, this month, I decided to sit down with Tony King, one of our actuarial analysts, and discuss the popular topic of loss development factors. The conversation has been edited for clarity, but I think you will find it a good review with […]

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Risk Management: Analytically Based, Data Driven

A few months ago, we conducted a survey concerning the utilization of analytics in the retention decision process.  As I continue through the PhD program at Oklahoma State University my prospective dissertation topic continues to move toward the study of analytical capabilities within an organization and its correlation with organizational performance. While the risk management […]

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Simulation and Confidence Level Analysis

Loss simulations and confidence level analyses are important tools when budgeting for projected losses in the upcoming year. The projected loss pick determined by an actuary provides the expected or average value of losses, but it is also important to understand the volatility around the projected losses or to compare the effects of various per-occurrence […]

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