Advanced knowledge of the fundamental theory, continuous-time financial mathematics skills and the ability to put that expertise into practice, coupled with an understanding of key concepts in actuarial and financial mathematics is more important than ever to an understanding of the increasingly complex financial market. Competition for the best jobs in the finance and insurance sector is also set to intensify, and acquiring that expertise significantly improves your chances of moving into this field or furthering your career in finance or insurance. You can develop the skills you need on the Financial Engineering distance-learning programme at TU Kaiserslautern.
The programme is aimed at graduates of mathematics programmes who are already working, are seeking a career in applied financial mathematics or research, and whose first degree did not provide sufficient expertise in this area. The programme is also and in particular aimed at graduates of other Master‘s programmes whose Master‘s or initial Bachelor‘s degree had a significant mathematics component, who are already working in a relevant industry and who want a more in-depth understanding of financial mathematics and to learn about the background, concepts, and methods.
In-depth knowledge of methodology, modern financial mathematics and actuarial theory and their
statistical and numerical use in practice are increasingly important in the finance and insurance industry. Regulators now also set strict risk assessment requirements for business portfolios, and these require an understanding of the latest statistical methods and actuarial models.
A combination of methods is key in practice, but this demands comprehensive mathematics qualifications in all areas. The programme is tailored to the demands of everyday working practice: interdisciplinary, and designed to teach the advanced financial mathematics and financial economics theory and skills required for an in-depth understanding of the increasingly complex financial market. It also explores links to actuarial science and teaches relevant statistical and numerical methods.
Schedule and organization
The standard length of the Financial Engineering distance-learning programme, including assessment periods, is six semesters. The programme is worth 90 credit points and begins in October each year.
1. ADMISSION WITH A UNIVERSITY DEGREE
Applicants must demonstrate that they have completed a higher education degree lasting at least six semesters at a German or foreign state or state-recognised higher education institution, at least one year‘s relevant work experience in the finance and insurance sector or in a mathematics-related profession following their degree, and that they have the necessary prior knowledge from their previous degree. Prior knowledge from applicants‘ previous degrees is demonstrated using a scoring system and by the successful completion of module assessments in analysis and stochastics. Students may be able to catch up with some aspects required during the first year of the programme (conditions of admission).
2. ADMISSION WITH A PROFESSIONAL QUALIFICATION
Prospective students without an undergraduate degree but with at least four years‘ relevant professional experience in finance and insurance can take an aptitude test for admission to the programme. They may have to complete credits in analysis and stochastics in the first year of the programme (conditions of admission)
Application & Enrollment
A period of several weeks, generally from mid-May to mid-July, is set for applications. New intake is in the winter semester only. Please contact the DISC or the Student Affairs Office at the Technische Universität Kaiserslautern for details of the current admission dates and application deadlines. They will also provide the necessary forms and documents for applications. Successful applicants will be sent detailed information on registration. Separate conditions apply for candidates with professional experience but no university degree.
You can discontinue or interrupt your distance learning programme at the end of each semester. The associated certificates of de-registration or leave of absence will also be issued at the end of the semester. The registration fee and the tuition fee cannot be reimbursed in the case of withdrawal after successful admission to the programme. Many students experience periods in which they need to focus more strongly on their careers or families while enrolled in an academic programme. Experience has shown that it is nonetheless possible to successfully graduate from the programme despite other commitments. Contact the programme officers in time so that they can potentially help you to find an individual solution in order to avoid interrupting or even discontinuing your academic programme.
Students take various classes towards two modules in each of the first five semesters. Students work through one to two sets of learning material for each module. The sixth semester is for the Master‘s thesis. Around 16-18 hours per week will be required for working through the learning material and completing the corresponding exercises. Students should schedule this time, especially in the first semester, as it generally takes a while for them to establish their own individual working and studying style and to get used to the written course material. Realistically, the initial workload is likely to be higher, not least for those from non-mathematical disciplines: they will need to familiarise themselves with a new and perhaps strange terminology and style, and new types of question.
Your actual workload will depend on a range of very different factors such as prior knowledge, your individual studying habits and your professional and personal situation. One weekend (Friday to Sunday) per semester is required on top of the specified workload for attendance at the on-campus phase. Whatever your actual workload, you will find that you will not be able to pursue all your previous activities and hobbies as usual. We, therefore, recommend realistically considering your capacity, your interests and the time available to you to avoid unnecessary frustration.
The state offers individual tax incentives in Germany for advanced training measures. Depending on your personal income and job situation, you may be able to offset the costs of your distance learning programme as advertising expenses or special expenses and receive a partial or full refund. For more information, please contact an independent expert or your local tax authority. Unfortunately, financial support cannot be granted in accordance with the Sozialgesetzbuch – Drittes Buch (SGB III) (Social Security Code – Book Three) or the Bundesausbildungsförderungsgesetz (BaföG) (Federal Training Assistance Act).
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Last updated July 11, 2018