• Target level of study

    Master's degree

  • ECTS

    120 credits

  • Duration

    2 years

  • Training structure

    Faculty of Economics

  • Language(s) of instruction

    French

Presentation

The Master's in Money, Banking, Finance, and Insurance comprises five tracks:

  • Market Risk Analysis Course
  • Course Banking Risk Analysis
  • Actuarial Science Program
  • Financial Engineering Program
  • Economic and Financial Information System Course
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The advantages of the training program

  • Since 2019, the Faculty of Economics has had a trading room that implements innovative teaching practices in real-life trading situations and financial data and information analysis.
  • It is the only master's degree in the Hérault department and in the region that offers students a real opportunity to pursue a career in financial engineering. It should be noted that this will be one of the few financial engineering programs offered by a faculty of economics in France.
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Objectives

The Market Risk Analysis course provides students witha thorough understanding of the structure and functioning of the most common financial products (stocks, bonds, etc.) as well as speculative markets (energy, commodities, basic products, etc.).

The Banking Risk Analysis program allows students to acquire skills in banking risk modeling tools and the banking environment. A good knowledge of banking operations and products is required.

The Actuarial Science program allows students to acquire skills in actuarial methods and tools and to apply them in a professional setting. It provides the theoretical and methodological knowledge necessary to pursue a career as an actuary and to prepare future researchers in this field.

The Financial Engineering program enables students to acquire advanced financial engineering techniques, techniques that enable them to integrate the global dimension of the problems to be addressed and their strategic challenges, and which are open to the international environment.

The Information Systems program allows students to acquire skills in computer science, information systems modeling, and economic and financial data mining.

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Know-how and skills

This statement allows you to:

                - Provide students with the skills necessary to work as risk analysts (analyzing different types of risk) so that they can propose personalized solutions in the field of risk management (assessing the risks of complex products, constructing structured products or complex portfolios, etc.) and actuarial science.

                - Provide students with the skills necessary to conduct research within public organizations and to understand regulations and financial and banking operations, to detect, assess, and model risks, and to evaluate financial products.

                - Master financial modeling tools as well as financial econometrics, banking, and financial engineering techniques that enable you to apply for jobs as a market operator, portfolio manager, financial risk analyst, back office staff, or actuary analyst.

               - Acquire sufficient knowledge to apply for doctoral contracts and/or enroll in a doctoral program

               - Possess computer skills and know how to model and use computer tools, software, or software packages commonly used in the markets.

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Organization

Special facilities

Study and exam accommodations are available for students with recognized disabilities and/or high-level athletes.

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Program

The Master's program is organized into two years: Master 1 and Master 2.

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Select a program

Actuarial science

Actuarial Science is a course of study within the Money, Banking, Finance, and Insurance program.

This program provides students with the theoretical and methodological knowledge necessary to pursue a career as an actuary and prepares future researchers in this field.

  • What is an actuary?

Professional specializing in the application of probability theory and statistics to insurance, finance, and social security issues.

To do this, they analyze the financial impact of the risk and estimate the associated future cash flows. Actuaries use mathematical techniques, mainly derived from probability theory and statistics, to describe and predict certain future events, such as human life expectancy, the frequency of claims, or the extent of associated financial losses.

See the full page for this route

  • Theoretical econometrics

    5 credits
  • Market finance

    4 credits
  • Monetary and financial macroeconomics

    3 credits
  • Forecasting methods

    5 credits
  • Algorithms and Programming

    3 credits
  • Data mining and big data

  • Data warehouse

  • Language selection list

    • Choose one of two options:

      • English for Finance 1

        2 credits
      • Spanish 1

  • Economics of Bancassurance

    3 credits
  • Introduction to Stochastic Calculus

    4 credits
  • Corporate finance

    4 credits
  • Introduction to SAS

    2 credits
  • Actuarial models in Excel VBA

    3 credits
  • Time series econometrics

    5 credits
  • Technical analysis

    2 credits
  • Applied econometrics project

    5 credits
  • Actuarial techniques

    3 credits
  • Choose one of two options:

    • English for Finance 2

      2 credits
    • Spanish 2

      2 credits
  • Optional

    • UM Student Engagement

  • Financial markets and financial theory

    2 credits
  • Professional development conferences

  • Trading algorithm

    1 credit
  • Portfolio management under R

    1 credit
  • Non-Life Actuarial Science

    3 credits
  • Financial analysis (Bank of France)

    1 credit
  • Introduction to Artificial Intelligence in Python

    0.5 credits
  • Primary stock market: initial public offering

    0.5 credits
  • Stochastic calculus

    2 credits
  • Financial English

    1 credit
  • Enterprise risk management

    1 credit
  • Exploratory statistics (SAS)

    1 credit
  • Computer techniques (VBA)

    1 credit
  • Modeling emerging risks

    2.5 credits
  • Life Actuarial Science

    2.5 credits
  • Cybersecurity and cryptography

    1 credit
  • Econometrics applied to finance

    2 credits
  • Financial market econometrics

    2 credits
  • Financial big data

    1 credit
  • FinTechs, Blockchain, and Cryptocurrencies

    1 credit
  • Numerical methods in actuarial science "VBA"

    2 credits
  • Banking and insurance regulations

    1 credit
  • Introductory seminars on research

Banking risk analysis

This program trains banking finance professionals and researchers in this field.

He offers modern programming practices combined with statistical methods applied to large financial databases, with the ultimate goal of managing banking risks.

This course constantly takes into account developments in the banking sector, particularly changes in the field of banking risk analysis. In recent years, banking professions have undergone profound changes. These changes in banking professions and the globalization of operations have given rise to new risks. International operations now account for a growing share of credit institutions' on-balance-sheet and off-balance-sheet activities, while market interventions are becoming more diverse and complex. These developments have given rise to new types of risk and altered the factors of financial fragility that can affect the quality of the situation of banking players. As a corollary, banking supervisory authorities have imposed prudential rules to prevent banks from failing. These rules are part of preventive action programs aimed at promoting the stability of domestic banking systems.

This new training program enables participants to integrate the regulatory constraints of Basel III into the measurement of banking risks such as liquidity risk, asset and liability management (ALM), etc.

 The aim is to equip students with three types of skills: expertise in quantitative methods (econometrics, analysis of large databases, etc.), risk analysis (particularly banking risk) and banking regulation, and proficiency in IT tools (SAS, R, VBA, Python, etc.). The quantitative courses in this master's program are held in the MUSE Trading Room.

 These skills provide students with powerful tools for measuring the risks faced by financial institutions, enabling them to join risk control departments.

Strong ties have been established over many years with regional and national professionals, such as the Regional Director of the Ecole Supérieure and the Regional Delegate of the French Banking Federation. Many professionals contribute to the Master's 2 program, either through lectures or through the EU's professionalization conferences. These professionals share their professional experiences and explain the careers that are open to students upon completion of the Master's program. Internships are often obtained as a result of these presentations.

Conferences on Big Data, Artificial Intelligence (Python programming), etc. are organized by Data Scientist specialists.

Students thus benefit from excellent professional training based on solid theoretical knowledge and professional application by recognized experts in the field through supervised projects or professional conferences . This enables the vast majority of graduates to find employment within six months of completing their Master's degree. The employment rate is over 77%. 

See the full page for this route

  • Choose one of two options:

    • English for Finance 1

      2 credits
    • Spanish 1

  • Theoretical econometrics

    5 credits
  • Market finance

    4 credits
  • Monetary and financial macroeconomics

    3 credits
  • Forecasting methods

    5 credits
  • Algorithms and Programming

    3 credits
  • Data mining and big data

  • Data warehouse

  • Economics of Bancassurance

    3 credits
  • Optional

    • UM Student Engagement

  • Choose one of two options:

    • English for Finance 2

      2 credits
    • Spanish 2

      2 credits
  • Introduction to Stochastic Calculus

    4 credits
  • Corporate finance

    4 credits
  • Introduction to SAS

    2 credits
  • Banking techniques

    3 credits
  • Time series econometrics

    5 credits
  • Technical analysis

    2 credits
  • Applied econometrics project

    5 credits
  • Financial Mathematics in Excel VBA

    3 credits
  • Professional development conferences

  • Financial markets and financial theory

    2 credits
  • Numerical methods in banking "VBA"

    2 credits
  • Trading algorithm

    1 credit
  • Portfolio management under R

    1 credit
  • Financial analysis (Bank of France)

    1 credit
  • Primary stock market: initial public offering

    0.5 credits
  • Stochastic calculus

    2 credits
  • Operational and compliance risks

    2 credits
  • Financial English

    1 credit
  • Introduction to Artificial Intelligence in Python

  • Exploratory statistics (SAS)

    1 credit
  • Computer techniques (VBA)

    1 credit
  • Financial big data

    1 credit
  • Credit risk

    2 credits
  • Cybersecurity and cryptography

    1 credit
  • Econometrics applied to finance

    2 credits
  • Financial market econometrics

    2 credits
  • Asset-liability management (ALM)

    2 credits
  • Interest rate risks

    2 credits
  • FinTechs, Blockchain, and Cryptocurrencies

    1 credit
  • Numerical methods in actuarial science "VBA"

    2 credits
  • Programming in R

  • Banking and insurance regulations

    1 credit
  • Introductory seminars on research

Market risk analysis

This program trains professionals for careers in financial markets and researchers specializing in this field. It offers specialized instruction in theoretical and quantitative areas related to products traded on financial markets. In particular, it addresses the determination of risk management through the combination of statistical methods.

This course builds on what has been done up to the 2020-2021 academic year, with developments that allow for the integration of changes in the risk analyst profession. In particular, it involves integrating the regulatory constraints of Basel III into market risk measurement (calculation of Value at Risk (VaR) and Expected Shortfall (ES), and their validation (backtesting). The aim is to equip students with effective tools for measuring and hedging the risks faced by financial institutions (banks and insurance companies). With the skills acquired at the end of their training in market risk analysis, students will be able to join risk control departments. 

See the full page for this route

  • Choose one of two options:

    • English for Finance 1

      2 credits
    • Spanish 1

  • Theoretical econometrics

    5 credits
  • Market finance

    4 credits
  • Monetary and financial macroeconomics

    3 credits
  • Forecasting methods

    5 credits
  • Algorithms and Programming

    3 credits
  • Data mining and big data

  • Data warehouse

  • Economics of Bancassurance

    3 credits
  • Introduction to Stochastic Calculus

    4 credits
  • Asset valuation

    3 credits
  • Corporate finance

    4 credits
  • Introduction to SAS

    2 credits
  • Portfolio allocation

    3 credits
  • Time series econometrics

    5 credits
  • Technical analysis

    2 credits
  • Applied econometrics project

    5 credits
  • Optional

    • UM Student Engagement

  • Choose one of two options:

    • English for Finance 2

      2 credits
    • Spanish 2

      2 credits
  • Numerical methods

    3 credits
  • Financial markets and financial theory

    2 credits
  • Programming in VBA

    1 credit
  • Stochastic calculus

    2 credits
  • Portfolio management

    4 credits
  • Financial English

    1 credit
  • Trading algorithms

    2 credits
  • Data mining and big data

    3 credits
  • Exploratory statistics (SAS)

    1 credit
  • Computer techniques (VBA)

    1 credit
  • Market risks

    4 credits
  • Financial econometrics

    2 credits
  • Programming in R, Python

    1 credit
  • Professional speakers

  • Introductory seminars on research

Economic and financial information system

This program offers in-depth instruction in economics and econometrics.

It also enables students to acquire skills in information systems modeling and economic and financial data mining.

See the full page for this route

  • Choose one of two options:

    • English for Finance 1

      2 credits
    • Spanish 1

  • Theoretical econometrics

    5 credits
  • Market finance

    4 credits
  • Monetary and financial macroeconomics

    3 credits
  • Forecasting methods

    5 credits
  • Algorithms and Programming

    3 credits
  • Data mining and big data

  • Data warehouse

  • Economics of Bancassurance

    3 credits
  • Design of an IS (information system)

    3 credits
  • Database manipulation

    2 credits
  • Programming techniques

    2 credits
  • Data mining and big data

    3 credits
  • Survey

    2 credits
  • Computer Law (Polytech)

    2 credits
  • Data warehouse

    3 credits
  • Modeling an IS (information system)

    3 credits
  • Exploratory statistics (SAS)

    1 credit
  • Computer techniques (VBA)

    1 credit
  • Data visualization design

    2 credits
  • Econometrics

    3 credits
  • Safety

    3 credits
  • Optional

    • UM Student Engagement

  • Choose one of two options:

    • English for Finance 2

      2 credits
    • Spanish 2

      2 credits
  • Introduction to Stochastic Calculus

    4 credits
  • Corporate finance

    4 credits
  • Introduction to SAS

    2 credits
  • Programming in VBA

    3 credits
  • Econometrics of qualitative variables

    3 credits
  • Time series econometrics

    5 credits
  • Technical analysis

    2 credits
  • Applied econometrics project

    5 credits
  • Choice of internship or thesis

    30 credits
    • Choose one of two options:

      • M2 SIF internship

        30 credits
      • Research thesis as part of a research program

        30 credits
  • Introductory seminars on research

Financial Engineering

This program trains professionals in the field of financial engineering and researchers specializing in this area.

See the full page for this route

  • Choose one of two options:

    • English for Finance 1

      2 credits
    • Spanish 1

  • Theoretical econometrics

    5 credits
  • Market finance

    4 credits
  • Monetary and financial macroeconomics

    3 credits
  • Forecasting methods

    5 credits
  • Algorithms and Programming

    3 credits
  • Data mining and big data

  • Data warehouse

  • Economics of Bancassurance

    3 credits
  • Choose one of two options:

    • English for Finance 2

      2 credits
    • Spanish 2

      2 credits
  • Introduction to Stochastic Calculus

    4 credits
  • Corporate finance

    4 credits
  • Introduction to SAS

    2 credits
  • Project financing in Excel VBA

    3 credits
  • Time series econometrics

    5 credits
  • Corporate taxation

    3 credits
  • Technical analysis

    2 credits
  • Applied econometrics project

    5 credits
  • Optional

    • UM Student Engagement

  • Mergers-Spin-offs-LBOs-Bankruptcies-Restructuring

    2 credits
  • Quantitative risk management

    2 credits
  • Financial markets and financial theory

    2 credits
  • Investment science

    3 credits
  • Portfolio management under R

    1 credit
  • Innovative financing operations

    1 credit
  • Financial analysis (Bank of France)

    1 credit
  • Advanced financial management "case studies"

    2 credits
  • Stochastic calculus

    2 credits
  • Tax optimization "Case studies"

    2 credits
  • Audit and control "case study"

    1 credit
  • Financial English

    1 credit
  • Exploratory statistics (SAS)

    1 credit
  • Computer techniques (VBA)

    1 credit
  • International accounting (GAAP or IFRS)

    2 credits
  • Project management and assembly

    1 credit
  • Panel econometrics

    2 credits
  • FinTechs, Blockchain, and Cryptocurrencies

    1 credit
  • Banking and insurance regulations

    1 credit
  • Corporate strategy and governance

    1 credit
  • Introductory seminars on research

Admission

Admission requirements

APPLICATIONS:

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Target audience

And after

Professional integration


Students in this program prepare for a wide range of careers in banking, finance, insurance, financial engineering, data processing (data analyst), and information systems design.

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