COURSE UNIT TITLE

: INTRODUCTION TO ACTUARIAL MODELS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 4182 INTRODUCTION TO ACTUARIAL MODELS ELECTIVE 3 0 0 5

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

Offered to

Statistics
Statistics(Evening)

Course Objective

The objective of this course is to cover actuarial models of loss contingencies. We will cover statistical concepts of location and dispersion, inferences from insurance data.

Learning Outcomes of the Course Unit

1   Review the theory of probability.
2   Learn IRM and CRM models.
3   Calculate the expected payment per loss and variance of the payment per loss.
4   Generate frequency models
5   Generate aggregate models and estimate ground up loss.
6   Calculate and modeling modifications of loss amount.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to loss models.
2 Moments and probability generating functions. IRM and CRM models. The Double Expectation Theorem.
3 Mixing Distributions and Splicing Distributions.
4 An example with the IRM and CRM models.
5 Truncation and censoring of distribution.
6 Severity Models
7 Families of Continuous models for loss amounts. Coverage modifications of the ground up loss. The expected payment per loss and variance of the payment per loss.
8 Midterm exam
9 Frequency Models. The types of frequency models. Compound frequency models and mixed frequency models.
10 The impact of exposure on frequency and the impact of severity on frequency.
11 Filtering the zero terms from a compound sum.
12 Aggregate models.
13 Compound Poisson Collective Risk Models.
14 Aggregate annual claims of an insurer/ Reinsurance.

Recomended or Required Reading

Textbook(s):
Stuart A. Klugman, Harry H. Panjer, Gordon E. Willmot, Loss Models: From Data to Decisions,2nd Edition, John Wiley and Sons Inc., 1999

Planned Learning Activities and Teaching Methods

The course consists of lecture, class discussion and problem solving.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 VZ Vize
2 FN Final
3 BNS BNS VZ * 0.40 + FN * 0.60
4 BUT Bütünleme Notu
5 BBN Bütünleme Sonu Başarı Notu VZ * 0.40 + BUT * 0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

Student responsibilities:Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

DEU Faculty of Science, Department of Statistic
e-mail: guckan.yapar@deu.edu.tr
Tel: 0232 301 85 59

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 12 2 24
Preparation for midterm exam 1 20 20
Preparation for final exam 1 28 28
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 115

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.154554553
LO.254554553
LO.354554553
LO.454554553
LO.554554553
LO.654554553