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| '''Dynamic financial analysis''' (DFA) is a [[simulation]] approach that looks at an [[insurance]] enterprise's risks holistically as opposed to traditional [[actuarial]] [[analysis]], which analyzes [[risks]] individually. Specifically, DFA reveals the dependencies of [[hazard]]s and their impacts on the [[insurance]] company's financial well being such as [[business]] mix, [[reinsurance]], [[asset allocation]], [[profit (accounting)|profitability]], [[solvency]], and [[Regulatory compliance|compliance]].
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| In addition to projecting [[stochastic]] future [[economic]] scenarios through using scenario generators such as '''interest rate''', '''underwriting cycle''' and '''jurisdictional risk''' models, DFA also links the scenarios with the '''financial models of the targeted insurance company''' that is being analyzed. Such models not only reveal the operation and the [[business structure]] of the company, but also uncover the dependencies among its business practices. Because DFA tries to account for every aspect of the company, it produces a vast amount of [[data]]. As a result, analyzing and presenting the [[outputs]] effectively is of great importance.
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| ==Objectives==
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| DFA is used primarily by [[financial]] practitioners to manage profitability and financial stability (the risk control function of DFA)<ref name="Intro DFA">Kaufmann, Roger. Andeas Gadmer. Ralf Klett. (2004, May) [http://www.casact.org/library/astin/vol31no1/213.pdf ''Introduction to Dynamic Financial Analysis'']. Retrieved October 23, 2009, from Casualty Actuarial Society website: http://www.casact.org/library/astin/vol31no1</ref> Not only do DFA users seek to maximize [[shareholder]] values, but they also try to maintain [[customer]] values. Furthermore, outputs from DFA could help managers identify strengths and weaknesses of the following areas.<ref name="Converium">Blum, Peter. Michel Dacorogna. (2004) [http://www.wiley.co.uk/eoas/pdfs/TAD036-.pdf ''Dynamic Financial Analysis''], Retrieved October 23, 2009, from Converium Ltd website: http://www.scor.fr/www//index.php?id=350&L=2</ref>
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| * '''Business mix''': estimates relative and absolute value of each line of [[business]] (e.g. [[premium]]{{disambiguation needed|date=August 2012}} and [[Commission (remuneration)|commission]] level) compared to the company's [[financial]].
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| * '''[[Reinsurance]]''': uncovers the structure of the company's line of businesses such as [[contract]] types, interrelation among contracts, and cost of [[reinsurance]].
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| * '''[[Asset allocation]]''': determines whether a company is taking on too much [[financial risk|investment risk]], which could be minimized through [[Diversification (finance)|diversification]] of investments.
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| * '''[[Profit (accounting)|Profitability]]''': measures the profitability of the company's each line of business.
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| * '''[[Solvency]]''': reveals [[liquidity]] problems, which are mismatches of [[cash flows]] that a company might experience if it did not have enough [[cash]] to immediately meet [[financial]] [[obligations]].
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| * '''[[Regulatory compliance|Compliance]]''': assesses the likelihood of [[insurance]] [[regulatory agency|regulators]] intervening the company's business due to change in [[regulations]] or deteriorating [[business operations]].
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| * '''[[Sensitivity]]''': explores the company's reaction to a change in [[strategies]] and [[economic]] conditions in the future.
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| * '''Dependency''': uncovers dependencies of all kinds of [[risks]] that are hard to understand without a holistic modeling and [[analysis]] tool.
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| ==Elements==
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| DFA consists of the following 3 parts:<ref name="Converium" />
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| * '''Scenarios''', generating expected and extreme economic [[scenarios]] to assess the company's reaction to [[social change|changes]]
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| * '''Business Models''', quantifying the company's [[business models]] and uncovering the dependencies among them
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| * '''Analysis Presentation''', presenting the [[analysis]] to the [[executive (management)|executives]] who make [[strategy|strategic]] [[Decision making|decisions]]
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| Careful [[calibration]] is required to ensure the [[accuracy]] of the scenarios and the [[correlations]] among [[business models]].
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| ===Scenario===
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| The scenario generator must meet the following criteria:<ref name="Converium"/>
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| * Generate individual [[risks]] while keeping track of their dependencies with one another and with time (e.g., an increase in the [[price]] of gasoline might lead to less driving mileages of [[automobile]] policy holders, thus leading to fewer [[car]] [[accidents]]).
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| * Produce both normal and [[abnormal]] behavior of the risk factors (e.g., a 1% change in [[S&P]] index is normal; a 40% change is extreme).
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| * Simulate [[stochastic]] [[scenarios]], meaning that [[scenarios]] are not the same every time you run the [[analysis]].
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| * Assign [[mathematical models]] that best imitate the [[behaviors]] of the risk factors. Such models could be found in, though not exclusively, [[actuarial science]], [[finance]] and [[economic]] disciplines.
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| * Track the incurred losses and the development of the losses, specifically the [[cash flows]] of the company's operation. This may help [[managers]] recognize the need to implement better [[asset liability management]] strategies.
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| ====Interest rate generator====
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| The interest rate generator is the core fundamental of DFA. Many sophisticated interest rate models were created in the effort to best imitate the real world interest rate [[behavior]]. Although none of the existing models are perfect, they have their own advantages and disadvantages. The following is a simple interest rate model used in a publicly access DFA model.<ref name="D'arcy">D'arcy, Stephen P. Richard W. Gorvett. Thomas E. Hettinger. Robert J. Walling III. (1998, Summer) [http://www.casact.org/pubs/forum/98sforum/98sf053.pdf ''Using the Public Access DFA Model''], Retrieved October 23, 2009, from Casualty Actuarial Society website: http://www.casact.org/pubs/forum/98sforum/</ref>
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| =====Cox, Ingersoll, and Ross (CIR) interest rate generator=====
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| The [[Cox–Ingersoll–Ross model|CIR interest rate model]] characterizes the short term interest rate as a mean-reverting [[stochastic]] [[Forecasting|projection]]. Although CIR was first used to project continuous changes in the interest rates, it is also acceptable to use it to project discrete changes from one time period to another. Below is the formula.
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| <math>dr_t = a(b-r_t)\, dt + \sigma\sqrt{r_t}\, dW_t</math>
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| where <ref name="D'arcy"/>
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| * '''b''' = the long-run mean to which the interest rate reverts; the expected interest rate in the long run
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| * '''a''' = the [[speed]] of reversion of the interest rate to its long-run mean (e.g., a = 2 means the interest is expected to return to its long term mean within half a year, and a = 1/5 means it would take 5 years).
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| * '''<math> r_t</math>''' = the current short-term interest rate
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| * <math> \sigma\, </math> = the [[volatility (finance)|volatility]] of the interest rate process expressed as the [[standard deviation]] of historical or projected interest rate changes.
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| The CIR model has two components: a [[deterministic]] <math> a(b-r_t)</math> and a stochastic part<math>\sigma\sqrt{r_t}\, </math>. The [[deterministic]] part will go in the reverse [[Direction (geometry)|direction]] of what the [[Present|current]] short term rate is heading. In other words, the further the current interest rate is from the long term [[expected value|expected]] rate, the harder the [[deterministic]] part tries to reverse it back to the long term [[mean]].
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| The stochastic part is purely [[random]]; it can either help the current interest rate deviate from its long term [[mean]] or the reverse. Because this part is multiplied by the [[square root]] of the current interest rate, when the current interest rate is low, its impact is [[minimum]], thus leading to the unlikelihood of the interest rate going below zero, and the interest rate cannot be [[negative number|negative]]. However, the reverse is true if the current rate is high.
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| =====Jurisdictional Risk Generator=====
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| In the [[United States]], each state has its own [[regulatory]], [[jurisdictional]] and [[legislative]] bodies, and there are advantages and disadvantages for an [[insurance]] company conducting businesses in different [[U.S. state|states]]. For example, some states have [[regulation|restrictions]] on how much rate increase that an insurance company can charge for the [[risks]] on which it takes. Such risk can severely hamper the insurance entity's profitability and operation.
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| In DFA, jurisdiction risk is reflected in two ways.<ref name="D'arcy"/>
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| # "'''Acceptable" rate changes''': each state has its own limit for how much rate increase in [[percentage]] proportional to the existing rate an insurance company can charge without attracting regulators' scrutiny. Under the scenarios, if DFA indicates that the insurance company needs to charge more than the state's maximum limit for the risks, that should raise a red flag to the [[executive (management)|executives]] overseeing the insurance business in that [[region]].
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| # '''Lag in implementing indicated rate changes''': insurance companies often do not immediately implement the approved rate changes, and in fact there is often a [[lag]] of 3 to 6 months. The lag, shown in the model in terms of years, is longer in states with harsh rate regulation.
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| =====Underwriting Cycles Generator===== | |
| The number of [[insurance policy|policies]] an insurance company can sell depends on the [[macroeconomic]] [[Environment (systems)|environment]] of the [[insurance]] industry. The DFA scenario accounts for this [[risk factor]] to best simulate the nature of insurance business.
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| Below are four underwriting [[Cycle (baseball)|cycles]] that an [[insurance]] company may experience.
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| * '''Mature Hard''': Rates can be increased and may still sell more policies
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| * '''Mature Soft''': Rates need to be decrease in order to sell more policies
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| * '''Immature Hard''': Transition state from mature soft to mature hard
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| * '''Immature Soft''': Transition state from mature hard to mature soft
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| ===Company and Strategy modeling===
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| To estimate the impacts that the [[scenarios]] have on an [[insurance]] company, the company's [[business practices]] needed to be quantified and linked to the [[scenario]] factors such as interest rate and [[underwriting]] [[Business cycle|cycles]].
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| '''Types of Models'''
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| * ''Cash Flow Oriented Model'': Such model tries to imitate the [[cash flows]] of the insurance company's [[assets]] and [[Liability (accounting)|liabilities]]. Also it assess the impacts on the company's [[financial statement]].
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| ** Advantages: It might not be difficult to project [[cash flows]] linked to [[economic]] factors for the company's [[assets]].
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| ** Disadvantages: [[Liabilities]] are often unknown for an insurance company, and thus it is hard to generate outgoing [[cash flows]] for [[claim (legal)|claims]].
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| * ''Simple Model'': Such model only account for part of the [[Economic indicator|economic factors]] of the [[scenarios]]
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| ** Advantages: The model is mathematically tractable, and [[accuracy]] can be achieved.
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| ** Disadvantages: It defeats the purpose of implementing a DFA, which is to analyze potential impacts that changes in [[Economic indicator|economic factors]] can have on the [[insurance]] company's [[financial]] [[performance]].
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| * ''Complex Model'': Such model not only tries to account for all the [[Economic indicator|economic factors]] that the [[scenarios]] generate, but also the dependencies among the company's lines of [[business]]. It involves sophisticated [[mathematical models]] and [[parameter]] to achieve its goal.
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| ** Advantages: This approach helps [[executive (management)|executives]] truly understand the dependencies among its [[business models]] and the [[external]] impacts on the company's profitability.
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| ** Disadvantages: Such model is very unlikely to be mathematically tractable. In other words, the model can be totally wrong because no one may know the exact dependencies among the [[business]] models and the impacts that [[economic]] [[risks]] can pose to the company.
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| ===Analysis and presentation===
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| Without effective [[analysis]] and [[presentation]], [[managers]] can hardly make any sense out of the vast amount of [[data]] that DFA produces. The goal of DFA is to help the [[managers]] to find out whether the company's current [[strategies]] are in line with its [[financial]] goals. Below are some tricks of conducting and presenting DFA [[analysis]].<ref name="Corporate Strategy">Wiesner, Elizabeth R. Charles C. Emma. (2000, Summer) [http://www.casact.org/pubs/forum/00sforum/00sf079.pdf ''A Dynamic Financial Analysis Application Lined to Corporate Strategy''], Retrieved October 23, 2009, from Casualty Actuarial Society website: http://www.casact.org/pubs/forum/00sforum/.</ref>
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| # Keep communication concise and focused.
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| # Eliminate, if needed, part of the DFA's [[outputs]] that are irrelevant to the company's [[financial]] objectives.
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| # Include no more than four most important [[results]] in a brief [[executive summary]], and support your [[sentence (linguistics)|statements]] with [[graphics|graphs]] and [[exhibits]] in the [[Addendum|appendix]].
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| # Focus on [[business development]] trend, as opposed to over emphasis on specific [[number]]s or the details of the model. Keep in mind that DFA is only an [[Forecasting|estimate]] of what might happen.
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| # Support the DFA [[analysis]] with other available [[information]] within the company.
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| ==References==
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| {{Reflist}}
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| [[Category:Finance]]
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