Introduction
In our last lesson, we assembled the "ingredients" for our pricing recipe: the pricing basis. We defined the key assumptionsβdemographic, financial, and expenseβthat actuaries must make to project future cash flows. We also explored the crucial relationship between the best-estimate assumptions used for pricing and the more prudent assumptions often required for reserving.
This lesson moves from the ingredients to the "recipe" itself. We will examine the main methodologies actuaries use to combine those assumptions into a final premium. You will learn how these methods translate a set of beliefs about the future into a tangible price for an insurance contract. Your foundation in statistics will be particularly useful here, as these methodologies are essentially different forms of applied statistical modeling.
By the end of this lesson, you will be able to describe the two primary pricing methodologiesβformula-based and cashflow modelingβand understand the contexts in which each is most appropriately used.
The Methodological Framework: Two Main Approaches
At a high level, actuarial pricing methodologies fall into two broad categories. The choice of method depends on the complexity of the product, the data available, regulatory requirements, and the purpose of the calculation.
Actuarial Pricing Models and Methods: The Complete Guide - MatBlas
This article from MatBlas provides an excellent overview of the different types of models used in the industry. It clearly positions traditional models alongside more modern techniques.
Please read the section Types of Actuarial Pricing Models. Pay attention to the distinction between Generalised Linear Models (GLMs), which are a sophisticated form of formula-based pricing, and Scenario-Based models, which rely on cashflow projections.
As you've just read, the spectrum of models is wide, but they can be distilled into two fundamental approaches:
- Formula-Based (or Equation-Based) Methods: These methods use a single, often complex, equation to calculate the premium directly. They are static and calculate the premium at a single point in time based on a set of aggregate inputs.
- Cashflow Modeling Methods: These methods involve projecting all the expected cash inflows and outflows associated with a policy over its entire lifetime. The premium is then determined iteratively by finding the value that ensures the project meets a predefined profit target.
Let's explore each of these in detail.
1. Formula-Based Methodologies
Formula-based approaches are most common for simpler products, particularly in general insurance, but are also used for certain life insurance products. The core principle is to construct an equation that directly equates premiums with the sum of expected costs and profit.
The general structure of such a formula is:
Premium = Expected Claims Cost + Expenses + Profit Loading
The sophistication lies in how each of these components is calculated. For instance, in general insurance, the "Expected Claims Cost" is often derived by analyzing historical loss data and adjusting it for future trends.
Mastering General Insurance Pricing: An Actuary's Guide
This video on General Insurance (P&C) pricing explains the fundamental concept of using past data to set future prices, which is the heart of many formula-based approaches.
Please watch the segment from 06:51 to 10:19. The speaker describes this as the "bread and butter" of pricing: taking historical loss data and applying "on-level" and "trend" factors to make it representative of the future policy period. This is a classic formula-based technique.
A more structured example comes from the world of life microinsurance. The following resource details a clear, step-by-step formula for calculating a gross premium.
[PDF] An introduction to actuarial pricing of a life microinsurance product
This Milliman user guide provides a perfect illustration of a formula-based pricing calculation. It shows how different components are calculated separately and then combined.
Please review the following two sections: Section 3.1 to 3.4, which shows the calculation of the risk premiumβthe part of the premium that covers the expected claims. Section 3.5 and 3.6, which explains how expense and profit loadings are added to the risk premium to arrive at the final gross premium.
The approach you just reviewed can be summarized by the following equation, which is a common formula-based structure for pricing:
Here, the Risk Premium is the present value of expected benefit payments, calculated using probabilities of claim. The denominator "grosses up" the direct costs to allow for expenses and profit that are expressed as a percentage of the final premium. This is a powerful and efficient method for products where the cash flows are relatively simple and predictable.
2. Cashflow Modeling
For more complex productsβespecially in life insurance with investment components, options, or guaranteesβa static formula is insufficient. Cashflow modeling provides a dynamic, year-by-year (or even month-by-month) simulation of the policy's financial life.
The process involves building a projection of all cash flows:
- Cash Inflows: Premiums received, investment income earned on assets.
- Cash Outflows: Claims paid, expenses (commissions, administration), taxes, and critically, the change in reserves held.
The net of these cash flows in each future year is known as the profit signature. The premium is then treated as an unknown variable. The actuary uses a numerical method, like Excel's Goal Seek function, to find the premium that makes the Net Present Value (NPV) of the profit signature equal a desired profit objective.
The pricing model for the cancer insurance product we've seen before is a perfect example of this methodology in practice.

Pricing Models for Life and Health insurance products with a Fellow Actuary
This is the core of the pricing model video, where the actuary explains how all the cashflow components come together to produce a profit stream.
Please watch the segment from 35:04 to 44:09. As you watch, identify the key cash inflows and outflows he discusses. The crucial part is his explanation of how a macro (automating Goal Seek) iterates to find the premium that results in the target 12% profit margin.
The key distinction of cashflow modeling is its ability to handle complexity and time-dependent factors. For instance, lapse rates or expense levels might be assumed to change at different policy durations. A formula-based approach struggles with this, while a cashflow model accommodates it naturally.
Pricing Models for Life and Health insurance products with a Fellow Actuary
This short clip makes the distinction between the two methodologies very clear.
Watch this brief but important explanation from 34:42 to 34:55, where the speaker highlights that varying assumptions by term is a key reason to use a cashflow model instead of a formula-based one.
When to Use Which Method?
The two methodologies are not mutually exclusive and are often used in conjunction. A formula might be used for an initial quick quote, while a full cashflow model is used for financial reporting and business planning.
- Use Formula-Based Methods for:
- Simple, short-term products: Most general insurance (motor, property), simple group life insurance.
- Quick Quotations: When an indicative price is needed quickly.
- High-volume business: Where individual policy cashflow modeling would be computationally prohibitive.
- Use Cashflow Modeling for:
- Complex, long-term products: With-profits, unit-linked savings plans, annuities.
- Products with options and guarantees: Where the value of these features depends on future conditions.
- Regulatory requirements: Many modern regulatory regimes (like Solvency II) require cashflow modeling for valuation and capital assessment.
- Detailed Profit Analysis: Assessing profitability by source (e.g., profit from lapses, mortality, expenses).
- Asset-Liability Management (ALM): Understanding the interaction between policy liabilities and the assets backing them.

Conclusion
We have now explored the primary "recipes" actuaries use to cook up a premium from the pricing basis. You've seen that these pricing methodologies range from elegant, static equations to complex, dynamic simulations.
Formula-based methods calculate the premium directly using an equation that balances expected costs and profits. They are efficient and effective for simpler products.
Cashflow modeling projects all policy-related income and expenditure over time, solving for the premium that achieves a specific profit goal. This dynamic approach is essential for complex products and for deeper business analysis.
The choice of methodology is a classic case of actuarial judgment, balancing the need for accuracy and sophistication against the principles of simplicity and proportionality.
In our next lesson, we will complete the strategic picture by examining the critical three-way interaction between pricing, reserving, and capital. We will see how a pricing decision not only impacts profitability but also has immediate consequences for the amount of regulatory capital an insurer must hold.
Key Takeaways & Cheatsheet
| Feature | Formula-Based Methodology | Cashflow Modeling Methodology |
|---|---|---|
| Core Principle | A static equation that directly solves for the premium at a single point in time. | A dynamic projection of cash flows over the lifetime of the policy. |
| Handling of Time | Time is handled implicitly through present value factors within the formula. | Time is handled explicitly, with cash flows projected for each future period (year, month). |
| Calculation | Premium = f(Claims, Expenses, Profit) |
Solve for P such that NPV(Profit Signature(P)) = Target |
| Best Suited For | Simple products, general insurance, quick quotes, high-volume business. | Complex products (life/pensions), products with options/guarantees, regulatory reporting, ALM. |
| Outputs | A single premium value. | A full profit signature, premium, and various other metrics (e.g., payback period, profit by source). |
| Strengths | Simple, fast, transparent, easy to implement. | Handles complexity, dynamic assumptions, provides deep insights, required by many regulators. |
| Weaknesses | Struggles with complex features, provides limited insight beyond the premium itself. | Complex to build and maintain, requires more data and computing power, can be a "black box" if not documented well. |