When finance and data meet! Finance is a sector that generates an enormous amount of data. Managing this data is now becoming a crucial issue for financiers, and the correlation between data analytics and finance is crucial… As a result, it is our responsibility to offer tailor-made training to big data professionals who want to work in the financial sector. We interviewed Mr Foued AYARI, a lecturer in finance and real estate at the Paris campus, to get his views on the importance of opening this new Master of Science Data Management & Finance programme, which will be offered at the start of the new academic year in September 2024.
How has Data impacted finance in recent years and what is the positioning of this new MSc Data Management & Finance?
According to IBM, 2.5 billion trillion bytes of data are produced worldwide every day, and the finance sector is the industry that generates the most data. With the Covid crisis, we are witnessing a rapid acceleration in digitisation, cybersecurity and AI. Everyone has seen the importance of data and the need to master a certain number of tools in virtually every job in banking, finance and insurance.
This means that, given the volume of data processed, the financial industry requires dual skills: Finance and Data (collecting, storing and processing structured and unstructured data that can be used to analyse models, develop new products, manage risks and detect fraud, anticipate behaviour or process transactions more efficiently, etc.), whether in corporate finance at finance department level or in market finance. Skills in Python, C++, SQL, R and SAS are therefore highly desirable.
So it’s only natural that INSEEC is launching this new MSc Data Management & Finance to meet these new skills requirements in the finance sector.
Everyone, including the famous CFA Institute, is on the data bandwagon, since from 2024 modules in python/machine learning/data science and AI will be compulsory for financial analysis, credit analysis and valuation. The CFA Institute has also published the following results from a survey of asset managers, showing that the 2 skills (Finance and Big Data) are the most sought-after:
Source: CFA Institute Handbook on AI and Big Data
What is the aim of the MSc Data Management & Finance?
The aim of the Master’s programme is to provide students with dual expertise in Finance and Big Data, giving them hybrid skills.
The MSc will enable students to meet a growing need on the job market in the Banking, Finance and Insurance sector, as well as in large companies. It will provide students with dual skills in finance and data:
a) Finance: Students will have expertise in corporate and market finance
b) Data
b1) Data processing and technologies (machine learning, AI, deep learning, big data) and mathematical, algorithmic, statistical and IT tools
b2) Programming: VBA, Python, SAS, R, C++
Among other things, this programme will make it possible to:
- Mastering Data science and Big Data
- Mastering Data programming languages
- Analysing and managing financial data
- Mastering the concepts of financial product valuation
- Mastering data in asset allocation and risk management…
- Mastering financial market predictive models
- Analysing and detecting market sentiment
- Mastering Generative AI in risk and compliance management
- Mastering algorithmic trading
- Mastering data visualisation
- Mastering Data regulations
- Managing risks: cybersecurity (reducing fraud, monitoring transactions and anticipating financial risks)…
What type of profile is this MSc aimed at?
This Master of Science is aimed at those who are looking for this dual skill, and I should point out that you don’t need to be good at maths at all! You need to hold a level 6 RNCP qualification and/or have validated the equivalent of 240 ECTS acquired in a course equivalent to the field concerned.
What opportunities are there for students?
As well as the classic job opportunities in finance, students can also apply for positions such as :
- Financial Data Manager
- Big Data Specialist
- Data scientist
- Data Engineer
- Data Analyst
- AI & Machine Learning specialist
- Financial Analyst
- Credit Analyst
- Investment Data Analyst