Dynamic Financial Analysis

Dynamic Financial Analysis (DFA) is a systematic approach for the integrated financial modeling of non-life insurance and reinsurance companies, aimed at evaluating the risks and profits associated with strategic decisions made by the company.

This is a form of simulation that is dynamic as it continues to evolve. This model can be used as a guide for various firms, but it must be used with a healthy dose of skepticism.

DFA takes the integrated and holistic point of view instead of the traditional actuarial analysis in which the different aspects of a company while calculating the risks were considered in isolation.

DFA simulates the company's reactions to many interconnected risk factors, including underwriting risks - typically from multiple lines of business - and asset risks.

In addition, to account for the long time horizons common in insurance and reinsurance, it allows dynamic projections for several periods into the future, where the period is typically a year but can also be a quarter long.

These typically reflect the entire financial structure of the modeled company, including the impact of accounting and tax structures. As a result, it enables projections for the company's balance sheet and profit-and-loss account ('P&L').

In addition to projecting Stochastic (property of well-being described by a random probability function) future economic scenarios through various generators like interest rate, jurisdictional risk models, and underwriting cycles, it also links the scenarios with the financial models of the insurance company that is being analyzed.

These models reveal the business structure, profits, losses, risks incurred, and operations of the company and discover the interdependence of its business practices. It generates a large amount of data as it attempts to account for every aspect of the business.

As a result, analyzing and presenting the outputs is crucial. As a result, DFA has become an important tool for decision-making and an essential part of erm, particularly within non-life insurance.

Objectives

The main objective of DFA is to manage a company's profitability and financial stability. The financial professionals of that company usually do this. The users of this model strive not only to maximize shareholder value but also to maintain customer value.

Furthermore, the outputs from this analysis could assist managers in identifying the following areas' strengths and weaknesses. 

• Business Estimates: The business estimates help to assess the relative and absolute value of each line of business (for example, premium and commission level) concerning the company's financials.

• Reinsurance: It reveals the structure of the company's line of business, such as contract types, contract interrelationships, and reinsurance costs.

• Asset Allocation: Asset allocation helps to determine whether a company is taking on too much investment risk, which could be reduced through investment diversification, or whether the company is taking low investment risk, which can be increased through increased investments. 

• Profitability: Profitability helps to measure the net profit or net income of the company's various business lines. We can calculate profitability by checking the net profit margin, calculating the gross profit margin, analyzing the operating expense, checking the profit per client, and listing upcoming prospects. 

• Solvency: By determining the solvency using this analysis, it reveals liquidity problems, which are mismatches of a cash flow that a company might experience if they do not have enough liquidated cash to meet its financial obligations immediately.

• Compliance: Compliance assesses the likelihood of the insurance regulators intervening in the company's business due to changes in the regulations or stagnant and declining business operations. 

• Sensitivity: By analyzing the sensitivity, we can explore the company's reactions to changes in the strategies, external sources, and economic conditions in the future. 

• Dependency: It reveals and discovers dependencies of all kinds of risks that are difficult to understand without a holistic modeling and analyzing tool. 

Elements of DFA

Three major elements of DFA must be carefully calibrated to ensure accuracy between the various elements.

A) Scenarios: The scenario generator is supposed to generate extreme and expected economic scenarios to assess the company's reaction to changes. Therefore, the scenario generator must meet the following criteria: 

• Generate individual risks while keeping track of their dependencies at one time (for example, an increase in the price of petrol might lead to less driving mileage of the automobile holders, thus leading to fewer car accidents.) 
• It produces both the various risk factors' normal and abnormal behavior.
• Simulating scenarios that are not the same each time you run them. 
• They assign mathematical models that imitate the actual behavior of the risk factors. These models could be found in actuarial sciences, economic and finance disciplines. 
• They are tracking the incurred losses and the development of the losses, specifically the liquid cash flow of the company's operations. This helps managers to recognize better asset liability management strategies. 

There are three ways to measure this generator: 

1. Interest Rate Generator:  The interest rate generator is fundamental to this financial analysis. Many sophisticated interest rate models have been developed to mimic real-world interest rate behavior.

Although none of the existing models are perfect, they each have benefits and drawbacks. A simple method to calculate the interest rate model is using the Cox-Ingersoll-Ross Model (CIR) interest rate generator.

2. Jurisdictional Risk Generator: Each state in the United States has its own regulatory, jurisdictional, and legislative bodies, and there are benefits and drawbacks for an insurance company doing business in multiple states.

Some states, for example, limit the rate increase that an insurance company can charge for the risks it accepts. However, such a risk can seriously impair the insurance company's profitability and operations.

3. Underwriting Cycles Generator: The number of policies an insurance company can sell is determined by the macroeconomic environment of the insurance industry. To best simulate the nature of the insurance business, the DFA scenario accounts for this risk factor.

The four underwriting cycles that an insurance company may go through are listed below.

• Mature Hard: Rates can be raised while still selling more policies.
• Mature Soft: Rates must be reduced to sell more policies.
• Immature Hard: The transition state between mature soft and mature hard. 
• Immature Soft: The transition state between mature hard and mature soft.

B) Business Models: It helps to quantify the company's business model and check the dependencies among them. The company's strategy modeling helps estimate the impact of the various scenarios on the insurance company. The different types of models are: 

Cash Flow Model: This model attempts to mimic the cash flows of the insurance company's assets and liabilities. It also evaluates the effects on the company's financial statements. The advantage of this model is that it may not be difficult to forecast cash flows for the company's assets based on economic factors.

Still, due to an insurance company's liabilities being frequently unknown, generating outgoing cash flows for claims is difficult.

Simple Model: This model only accounts for a portion of the economic factors in the scenarios. It is mathematically tractable, and it is possible to achieve accuracy.

Its disadvantage is that it defeats the purpose of implementing a DFA, which is to analyze the potential impacts that changes in economic factors may have on the insurance company's financial performance.

Complex Model: This model attempts to account for not only all of the economic factors generated by the scenarios but also the dependencies between the company's lines of business.

To achieve its goal, it employs sophisticated mathematical models and parameters. This approach enables executives to truly understand the interdependence of the company's business models and the external impacts on its profitability.

C) Analysis presentation: This stage refers to presenting the analysis to the executives of the company, who make the final strategic decisions of the company. Managers will struggle to make sense of the vast amount of data produced by DFA unless effective analysis and presentation are used.

DFA's goal is to assist managers in determining whether the company's current strategies align with its financial goals.

 The following are some tips for performing and presenting this analysis. 

• Maintain concise and focused communication.
• If necessary, remove portions of the DFA's outputs unrelated to the company's financial goals.
• Include no more than four key findings in a brief executive summary, and back up your claims with graphs and exhibits in the appendix.
• Focus on the overall trend of business development rather than specific numbers or model details.
• Support the analysis with other available internal and external information of the company.

Uses and Users

This section of the article discusses the uses attributable to the DFA techniques. We can use this model to improve the company's understanding of costs, advantages, and risks associated with changes in the claims management philosophy for the insureds.

This analysis has a list of potential uses when it states that DFA provides management with useful information for making decisions in the following areas:

• Evaluation of the business plan: These models can be used by the companies to study in depth the financial plans and strategies of the company. Such plans help to study why the company cannot meet its financial objectives. 

• Marketing strategy: This mainly consists of product and market development. This analysis can help provide a base for policy ratings and explore the possible financial effects that the new competition, market, and products will have on the financial result of the company's product and market reach. 

• Claims management: Claims management helps the company to understand costs, advantages, and risks associated with changes in the claims management philosophy for the insureds. 

• Determining the capital necessary for the company: Capital sufficiency normally refers to the company's capabilities to pay all its potential obligations. In the past, many companies have fixed their capital by using simple formulas based on premium or reserve ratios and do not take into account the risks faced by the companies.

  • This analysis helps to quantify the level of capital necessary to support the risks of the business. 

• Allocation of capital over lines of the business: This model permits an evaluation of the risks and profitability of the various divisions of a company and allocates the capital according to the value assigned to the risk borne by the company. 

• Liquidity analysis: This model can help a company to determine the level of short-term funds that may depend on the volatility of the company's present and future cash flow. 

• Reinsurance structure or strategy: Reinsurance analysis depends on the relationship between profitability and risk associated with the various reinsurance structures. The key question becomes the buyer's risk tolerance or risk aversion, as the lesser the reinsurance, the greater the profitability and risk.

  • This model can also help to answer various doubts like what type of reinsurance is to be bought, the levels of retention or limits, etc.

• Analysis of the investment strategy: This can help analyze different asset strategies and observe their influence on the company's long-term financial operations and results, which helps the company determine the proper risk profile strategy.

• Credit rating improvement: The rating agencies recognize the importance of risk management techniques such as DFA that provide the necessary tools to understand and quantify the company's risk exposure.

  • Any company that uses this model to analyze its economic decisions may obtain a more favorable credit rating. 

• Analysis of merger and acquisition opportunities: By using this analysis, it is feasible to quantify the acquisition price of a potential corporate operation as a function of value created by the new company.

Conclusion

The dynamic DFA models include conditional decision rules, which provide artificial intelligence. The theory behind this inclusion is that management can react to its environment by reviewing strategies as needed and not implementing its business plan passively during the model's projection period.

Formally, the decision rules are implemented through algorithms that perform calculations for some model variables based on values obtained in previous periods or predicted values in the future.

In this manner, it attempts to simulate the company's future reaction, recommending incorporating certain strategic decisions into the models. Still, they do not recommend incorporating all decision-making processes into the model so that the impact of various scenarios can be analyzed.

The need to measure the risk to which an insurance company is exposed has recently been fueled by the competitive environment in which the activity is carried out, technological and financial innovations, the current volatile nature of the markets, and the impending implementation of the new capital regulation known as Solvency II.

The main advantage of DFA is that it uses an integrated analysis of assets and liabilities that can be used for various purposes, including establishing risk-adjusted capital levels and evaluating strategies in light of environmental changes.

In this manner, and at all times, the company is aware of the risk it assumes and the capital required to respond to it.

As a result, the company can take action to position the business within the desired risk level and predict the effects of the strategies implemented. This analysis is known as a dynamic risk model, solvency analysis, and financial risk measurement. 

Researched and Authored by Tanika Punjabi | LinkedIn

Edited and Reviewed by Aditya Murarka | LinkedIn

Free Resources

To continue learning and advancing your career, check out these additional helpful WSO resources:

• Excel Current Date and Time
• Excel Dashboards
• Excel Drop Down List
• Excel for Beginners
• Excel for Finance