Description course 5 Capita Selecta for EMAS 08
Students who are exempted for course 1 or passed the exam for course 1 with a grade of 7 or higher, can choose between Risk Perception and Data Science. All other students take the module on Risk Perception. The modules on Ethics and IFRS for Insurers are mandatory for every EMAS student.
Module description “Data Science and statistical learning in the actuarial profession”
In 1956 IBM launched the first hard disk drive (152 cm long, 172 cm high, and 74 cm wide), which was able to contain 3.75 MB of data. Nowadays one can buy, on the consumer market, 3.5 inch 6 TB hard disk drives, which is an increase by a factor more than 106. Computing power, measured in flops, has followed a similar trend; an Apple iPhone 4, for example, is as powerful as the 1985 super-computer Cray-2.
The availability of cheap data storage, and in some cases also regulatory and legal requirements, have led to the collection of large amounts of data by financial and actuarial institutions. The increased computing power makes it possible to analyze these data streams. Up to today the common impression is that companies have only started to recognize and to exploit the (business) opportunities such data offers. Examples in the actuarial industry include pricing based on driving behavior from car sensors, anomaly detection in insurance claims to prevent fraud, and the use of micro-level claim data to determine loss reserves.
Although there is no agreed upon definition of data science, a common description of the role of a data scientist is to “make sense of (huge amounts of) data” and to “create value from data”. This requires knowledge on handling databases (traditional relational databases as well as “big data platforms” as Hadoop), a solid background in mathematics, statistical & machine learning. Moreover, working with large datasets often yields practical problems: datasets often do not fit into the memory of a computer. Therefore, a modern data scientist also has knowledge on distributed/cloud computing (for example, Spark).
This short course provides an introduction to data science with an emphasis on machine & statistical learning. We cover the situations in which the learning target is known (supervised learning), both continuous (regression) and discrete (classification), as well as the case of an unspecified target (unsupervised learning). The focus is on techniques and examples that are useful for the actuarial profession.
dr. R. (Ramon) van den Akker
dr. K.B. Gubbels AAG
Module description Risk Perception:
The module is on preferences, judgment and decision making under risk. The course is interdisciplinary, combining insights from finance, behavioural economics, social psychology, and linguistics. Implications will be drawn for the financial industry and its promise of customer centricity and integrity. Topics discussed in class include:
- How do people consistently deviate from the rational model?
- What do psychological biases imply for product development, choice architecture, and communication with financial consumers?
- Why are professionals less ethical than they think?
- What does the behavioural evidence imply for current attempts to improve integrity in the financial industry? good account
- Should the financial industry introduce gender marketing and should the pension industry introduce gender based investment policies?
- What exactly is pension risk to the financial consumer, and are financial regulation and supervision focusing on the right risk(s)?
- How should we judge current financial supervision by finanvial market authorities against the backdrop of the behavioural evidence?
- Why don't people annuitize more?
- Should reverse mortgages become a standard tool of personal financial planning?
- The fallacy of financial education
Prof.dr. H.M. Prast
Module description Ethics
In a globalizing, transparant and rapidly changing world, there is a growing awareness to address crucial questions related to ethics and sustainable development. What kind of ethical issues are related to the work of an actuary? How to deal with moral dilemmas? How are organizational conditions stimulating (ir)responsible behavior? And what strategies can be applied to make organisations more ethical? In this course on business ethics these kinds of questions are addressed.
Business ethics is the study of ethical dilemmas in business. Studying business ethics helps actuaries to make ethical decisions that are legitimate and hence support the ‘license to operate’ of firms. A professional actuary is capable of dealing with complex situations in interaction with many other parties.
The purpose of the course is to communicate theoretical and practical insights and developments in the fields of business ethics and sustainable development. The students learn the characteristics of ethical issues in business, and more specifically in pension funds and the insurance sector. They become acquainted with general theories of business ethics and sustainable development. Students also acquire competence in handling ethical dilemmas in a systematic way. The course is interactive, with class sessions, small group assignments and a guest lecture.
Prof.dr. A. Nijhof
Module description IFRS for Insurers
The first part of this module focuses on the importance of accounting for understanding the business world. We will first discuss whether and how accounting can be useful to set up economic interactions. Next, after a general introduction into financial reporting rules, we discuss: (i) the difference between cash accounting and accrual accounting, and, (ii) how accounting standards can influence decision-making in insurance firms.
The second part of this module deals with the latest developments in the accounting standards relevant to actuaries. First, an overview of the accounting principles applicable for insurers will be discussed. Next we will dive into how these principles are applied in practice and focus on the relevance of assumptions and model choices for the representation of the financial position and the financial performance of an insurer. We will conclude with discussing how accounting for insurance contracts is expected to affect decision making of management.
Written exam and Assignment
S.N.M. Vandenbogaerde MSc
F. Kratz AAG MSc