Topic 5 - Actuarial Modelling and Data Analysis

Question 1

What are Actuaries employed to do?

Answer 1

Solve financial problems

Question 2

Give two examples of financial problems?

Answer 2

The premium to charge for a new product
How much money needed to fund a pension in
retirement

Question 3

Actuaries use a series of tools that can be broken into:

Answer 3

Data
Assumptions
Models

Question 4

What type of data do Actuaries use on a regular basis?

Answer 4

Raw data

Question 5

Give two examples of raw data

Answer 5

Details of policyholders for an insurance company

Details of members for a pension scheme

Question 6

What are some of the drawbacks with using raw data

Answer 6

Raw data can be difficult to manage & draw conclusions from

Question 7

How do Actuaries ‘tidy up’ raw data?

Answer 7

Carry out types of data analysis to help tidy up data:
Descriptive –summary stats and simpler format
Inferential –using sample as proxy for whole population
Predictive –using past data to make future predictions

Question 8

What steps do Actuaries take when working with data?

Answer 8

Actuaries use a number of steps when working with data:

• Develop objectives to be met by data analysis
• Identify the data items required for analysis
• Collection of the data from relevant sources
• Process and formatting data (access database or spreadsheet)
• Cleaning the data (looking for errors omissions)
• Exploratory data analysis
• Model the data
• Communicating the results (source, limitations)
• Monitoring the process (iterative process)

Question 9

What is a model?

Answer 9

An imitation of a real-world system or process

Question 10

How are models useful to Actuaries in life or pensions sector?

Answer 10

• Actuaries in life or pensions work over long timeframes
• Models allow us to study them in compressed time
• Allows actuaries to investigate or test outcomes without carrying out action or having to wait until they play out

Question 11

Outline the iterative process used by Actuaries when building models

Answer 11

• Define objectives
• Plan modelling process and how model will be validated
• Collect and analyse data
• Define parameters and assumptions
• Build or write code for model
• Test the model and test reasonableness of output
• Review sensitivity of results to changes in assumptions
• Analyse output from model
• Adhere to any professional guidance
• Communicate and document results of the model

Question 12

What type of model(s) will we use during this module FIN1013 Actuarial Maths 1?

Answer 12

Deterministic models

Question 13

What is a deterministic model?

Answer 13

Key variable will take a definite value and is known in advance, producing a single outcome.

Question 14

What is a stochastic model?

Answer 14

Key variable may take a range of values
(random)
An assumption is made about the statistical distribution of the key variable range

Question 15

What are the benefits of using models?

Answer 15

• Models allow us to study complex problems in
  compressed time
• Allow us to study complex systems with stochastic
  elements
• Allow us to carry out multiple runs to see best fit

Question 16

What are the limitations of using models?

Answer 16

• Model development requires time, money and expertise
• Models need to be maintained and updated
• For stochastic models need large number of runs
• Models more useful for comparing inputs than max outputs
• Can be lulled into false sense of security
• Models rely on quality of data
• Users need to understand model and limitations
• Hard to include all future events
• Can be difficult to interpret some of the outputs of model

Question 17

What factors must be considered when considering the suitability of a model

Answer 17

• Objectives of the modelling exercise
  • What are you trying to achieve?
• Validity of the model, data and assumptions
• Impact and extent of correlation in random variables and results
  • Matching of assets and liabilities principle
  • if they move in same direction - Positively correlated
• Relevance of previous models
  • Can you update a previous model
  • can this be used to validate
• Credibility of data input and results output
  • Test reasonableness of outputs
  • Carry out sensitivity tests
• Dangers of spurious accuracy
  • Saying value of pension scheme is £9,876,543.21 say £9.9m
• Ease of how model and results can be communicated
  • Meet client needs and communicate with them in mind
• Regulatory requirements
  • Technical Actuarial Standards (TAS’s)