SOA Exams & Modules
[mathjax] LEARNING OBJECTIVES Able to construct decision trees for both regression and classification. Understand the basic motivation behind decision trees. Construct regression and classification trees. Use bagging and random forests to improve accuracy. Use boosting to improve accuracy. Select appropriate hyperparameters for decision trees and related techniques. EXAM NOTE As pointed out in Subsection 3.1.1, there are only two …
[mathjax] Case Study 3: GLMs for Count and Aggregate Loss Variables Learning Objectives Select appropriate distributions and link functions for count and severity variables. Identify appropriate offsets and weights for count and severity variables. Implement GLMs for count and severity variables in R. Assess the quality of a Poisson GLM using the Pearson goodness-of-fit statistic. Combine the GLMs for count …
[mathjax] Case Study 2: GLMs for Binary Target Variables Learning Objectives Compared to GLMs for numeric target variables, GLM-based classifiers enjoy some subtly unique features, which will be revealed in the course of this case study. At the completion of this section, you should be able to: Combine factor levels to reduce the dimension of the data. Select appropriate link …
[mathjax] Case Study 1: GLMs for Continuous Target Variables Learning Objectives Select appropriate distributions and link functions for a positive, continuous target variable with a right skew. Fit a GLM using the glm() function in R and specify the options of this function appropriately. Make predictions for GLMs using the predict() function and compare the predictive performance of different GLMs. …
[mathjax] EXAM PA LEARNING OBJECTIVES Learning Objectives The Candidate will be able to describe and select a Generalized Linear Model (GLM) for a given data set and regression or classification problem. Learning Outcomes The Candidate will be able to: Understand the specifications of the GLM and the model assumptions. Create new features appropriate for GLMs. Interpret model coefficients, interaction terms, …
[mathjax] Regularization What is regularization? Reduce model complexity: Reduces the magnitude of the coefficient estimates via the use of a penalty term and serves to prevent overfitting. An alternative to using stepwise selection for identifying useful features. How does regularization work? Variables with limited predictive power will receive a coefficient estimate that is small, if not exactly zero, and therefore …
Accounting Principles
OPBT Rollforward Analysis Summary Fee Based Income Insurance Operating Income Beginning – Last Year One-off – Claims Experience Actual claim profits – Expected claim profits, from basic and UDR products Actual claim profits – Expected claim profits, from PPR products Expense Experience Actual expense profits – Expected expense profits Lapse and Persistency Experience Anything else that are difficult to …
Issued: Dec 1987 Superseded by: ASC Summary Scope: For universal life-type contracts that were not addressed by FASB Statement No. 60, Accounting and Reporting by Insurance Enterprises. For limited-payment long-duration insurance contracts and investment contracts and amends Statement 60 to change the reporting of realized gains and losses on investments. Applicability: {US-FAS97-6} Investment contracts, Long-duration contracts that do not …
Classification of Insurance Contracts
Insurance contracts are classified as short-duration or long-duration contracts.
Long-duration contracts: insurance contracts that are expected to remain in force for an extended period include contracts, such as:
whole-life,
guaranteed renewable term life,
endowment, annuity, and
title insurance contracts.
Otherwise, short-duration contracts.
most property and liability insurance contracts.
Defined Terms cedant The policyholder under a reinsurance contract. deposit component A contractual component that is not accounted for as a derivative under IAS 39 and would be within the scope of IAS 39 if it were a separate instrument. direct insurance contract An insurance contract that is not a reinsurance contract. discretionary participation feature A contractual right to receive, …
Product Classification Definition of Insurance Contract An insurance contract is a contract under which the insurer accepts significant insurance risk from the policyholder by agreeing to compensate the policyholder if a specified uncertain future event (the insured event) adversely affects the policyholder. Definition of Insurance Risk Insurance risk is risk, other than financial risk, transferred from the policyholder to the …
Please note that the information contained in this post is based on my own research and understanding of the topic. While I have made every effort to ensure its accuracy, I cannot guarantee that it is completely error-free. If you notice any errors or omissions, please let me know so that I can correct them. Applicability FAS 60 …
Coding & Programming
Dates CODE_SEGMENT Dates ; Valuation Date IF LEN(STRVAL(MONTH(EXTRACT_DATE))) = 1 THEN VAL_DATE = STRVAL(YEAR(EXTRACT_DATE)) + “0” + STRVAL(MONTH(EXTRACT_DATE)) ELSE VAL_DATE = STRVAL(YEAR(EXTRACT_DATE)) + STRVAL(MONTH(EXTRACT_DATE)) ENDIF ; Last-Year End LYE_DATE = STRVAL(YEAR(EXTRACT_DATE) – 1) + “12” ; Beginning of Current Year BOY_DATE = STRVAL(YEAR(EXTRACT_DATE)) + “01” ; Last-Month LM_M = STRVAL(NUMVAL(SUBSTR(VAL_DATE, 5, 2)) – 1) IF LEN(LM_M) = 1 THEN LM_M …
FUNCTION INSTR(BYVAL TEXT_DATA AS TEXT, BYVAL TEXT_FIND AS TEXT)AS INTEGER ; Match Sub-String and Return its Position I INTEGER J INTEGER FOR I FROM 1 TO LEN(TEXT_DATA) – LEN(TEXT_FIND) + 1 FOR J FROM 1 TO LEN(TEXT_FIND) IF SUBSTR(TEXT_FIND,J,1) <> SUBSTR(TEXT_DATA,I + J – …
Function Categories The Prophet programming language provides a wide range of functions which are grouped into the following categories: Array functions Conversion functions Dynamic functions Error / Warning functions Financial functions Logical functions Mathematical functions Product functions Read functions Run Position functions Run Progress functions Run Setting functions Statistical functions Text functions Trigonometric functions Array Functions Function Description ARRAY_INITIALISE Resizes …
Extended formulas enable more complex calculations to be carried out than standard Prophet formulas. They are also able to retain the values that they have calculated from one model point to the next and from one loop to the next in a dynamic or stochastic run. Examples of situations where extended formulas can be useful include: The calculation of commutation …
Overview The Prophet programming language is the programming language used to create and maintain formula definitions for variables in each product and library. A formula in Prophet can be specified using either: The standard Prophet language features or, The Prophet Extended Formula features. A formula created using the standard Prophet language generates values for one variable only. An extended formula …
Purpose Extended formulas enhance and extend the capabilities of the Prophet programming language. They enable more complex calculations to be carried out than standard Prophet formulas. They are also able to retain the values that they have calculated from one model point to the next and from one loop to the next in a dynamic or stochastic run. Examples of …