OP Jindal Online M.Sc Artificial Intelligence & Finance 2026: Fees, Eligibility & Helpline Number

October 7, 2026

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Artificial Intelligence is rapidly transforming the financial sector. From algorithmic trading and portfolio management to fraud detection, risk analysis, digital banking and financial forecasting, AI is becoming an important part of modern finance. This changing industry landscape has created a growing demand for professionals who understand both financial concepts and artificial intelligence.

The OP Jindal Online M.Sc Artificial Intelligence & Finance 2026 is designed for graduates and professionals who want to develop expertise at the intersection of finance, artificial intelligence, data analytics and emerging financial technologies.

The programme is offered by the Jindal School of Banking & Finance (JSBF) at O.P. Jindal Global University. The current 2026 programme information lists it as a 12-month online master’s programme, with 66 credits, a total fee of ₹2,75,000, and a batch start date of 1 September 2026.

The programme combines financial management, financial markets, Python programming, financial data analytics, machine learning applications, fintech, digital banking, portfolio management, algorithmic trading, blockchain and Agentic AI.

For students and working professionals searching for OP Jindal Online M.Sc Artificial Intelligence & Finance fees, eligibility, syllabus, admission process, career scope and helpline number, this detailed guide covers the important information.

OP Jindal Online M.Sc AI & Finance 2026 – Highlights

Particular	Details
Programme	M.Sc Artificial Intelligence & Finance
University	O.P. Jindal Global University
School	Jindal School of Banking & Finance
Mode	Online
Duration	12 Months
Batch Start	1 September 2026
Total Credits	66
Total Tuition Fee	₹2,75,000
Minimum Eligibility	Undergraduate degree with 50% marks
Lower Marks Route	JSAT examination may be required
Major Areas	AI, Finance, FinTech, Data Analytics, Machine Learning
Admission Helpline	7973104914

The programme is listed among JGU’s online postgraduate offerings and is positioned at the intersection of technology, finance and digital transformation.

What is OP Jindal Online M.Sc Artificial Intelligence & Finance?

The OP Jindal Online M.Sc Artificial Intelligence & Finance is a postgraduate programme that combines financial knowledge with artificial intelligence and emerging technologies.

Traditional finance programmes generally focus on areas such as financial management, accounting, investment, markets and corporate finance. The AI & Finance programme adds technological capabilities such as Python, financial data analytics, natural language processing, Agentic AI, algorithmic trading and blockchain.

This interdisciplinary approach is designed to prepare students for a financial industry where technology and data are becoming increasingly important.

The programme focuses on areas including:

Artificial Intelligence
Financial Analytics
Machine Learning
Python Programming
Financial Markets
FinTech
Digital Banking
Algorithmic Trading
Portfolio Management
Robo-Advisory
Blockchain
Digital Currency
Technology Risk
AI Governance
Financial Data Analysis

The programme also includes real-world projects, case studies and practical applications related to financial markets and technology.

Why Choose M.Sc Artificial Intelligence & Finance in 2026?

The finance industry is changing quickly because of artificial intelligence, automation and data-driven decision-making.

Banks, investment firms, fintech companies and financial institutions are increasingly using technology for:

Risk assessment
Fraud detection
Credit analysis
Portfolio management
Financial forecasting
Customer analytics
Algorithmic trading
Automated investment services
Digital banking
Compliance
Financial research

This creates opportunities for professionals who can understand both the financial problem and the technology used to solve it.

A professional who understands finance but also knows how AI, machine learning and financial data analytics work can potentially explore a broader range of career opportunities.

The OP Jindal programme specifically focuses on applying AI and data science to financial markets, risk analysis, algorithmic trading and fintech.

OP Jindal Online M.Sc AI & Finance Fees 2026

The current programme listing shows the total tuition fee as:

₹2,75,000

The fee structure currently listed for the 2026 programme is:

Fee Component	Amount
Registration Amount	₹25,000
Instalment 1	₹1,25,000
Instalment 2	₹1,25,000
Total	₹2,75,000

The registration amount is listed as payable upon acceptance of the offer, while the first instalment is due before batch commencement and the second instalment is listed for 15 January 2027.

Students should confirm the applicable payment schedule at the time of admission because fee deadlines and admission policies may be updated for different intakes.

OP Jindal Online M.Sc AI & Finance Eligibility 2026

The eligibility criteria are designed for graduates who want to develop expertise in both finance and artificial intelligence.

Basic Eligibility

Applicants should have:

An undergraduate degree or equivalent qualification
At least 50% marks in graduation

Candidates with less than 50% marks may be required to appear for the JSAT examination according to the current programme information.

This makes the programme suitable for graduates from a variety of disciplines who are interested in developing skills in finance and technology.

Can Students From Different Backgrounds Apply?

Yes. The programme is designed for graduates and professionals interested in combining financial knowledge with AI, machine learning and analytics.

Students may come from backgrounds such as:

Commerce
Finance
Economics
Business Administration
Mathematics
Statistics
Computer Science
Information Technology
Engineering
Management
Other related undergraduate disciplines

The key requirement is meeting the prescribed graduation eligibility criteria and demonstrating an interest in the programme.

OP Jindal Online M.Sc AI & Finance Duration

The programme has a duration of:

12 Months

The course is divided into four academic terms and carries a total of 66 credits. The current programme listing gives the 2026 batch start as 1 September 2026.

The one-year structure makes it particularly relevant for graduates and working professionals who want to acquire specialised postgraduate knowledge within a relatively short period.

OP Jindal Online M.Sc AI & Finance Syllabus 2026

The curriculum combines finance fundamentals with artificial intelligence, data analytics and emerging technologies.

The programme consists of four terms.

Term 1 – Finance & Technical Foundations

The first term establishes the foundation in finance, statistics and programming.

Financial Management

Students learn the fundamentals of financial decision-making and management.

Important areas include:

Financial planning
Capital decisions
Financial analysis
Business finance
Financial decision-making

Financial Mathematics and Statistics

This subject introduces mathematical and statistical concepts relevant to finance.

Students can develop an understanding of:

Financial calculations
Probability
Statistical analysis
Quantitative decision-making

Financial Markets and Instruments

Students learn about financial markets and instruments and how they operate within the broader financial system.

Python Programming for Financial Applications

Python is increasingly important in financial analytics and AI.

Students learn how programming can be applied to financial problems and data.

The first term carries 16 credits.

Term 2 – Financial Data & Risk

The second term moves toward financial data analysis and technology risk.

Financial Data Analytics and Time Series

This subject focuses on analysing financial data over time.

Time-series analysis can be useful for:

Market analysis
Financial forecasting
Trend identification
Investment research
Economic analysis

International Corporate Social Responsibility and Ethics

Students explore ethical and responsible business practices within an international context.

Technology Risk Management

As financial organisations increasingly rely on technology, technology-related risks have become important.

Students can explore areas involving:

Technology risk
Operational risk
Digital systems
Risk controls
Financial technology

Global Economy and Geopolitical Risk

This subject connects financial decisions with global economic and geopolitical developments.

The second term carries 18 credits.

Term 3 – AI, FinTech & Investment

The third term introduces several important applications of technology in modern finance.

Natural Language Processing for Financial Markets

Natural Language Processing, or NLP, enables computer systems to analyse and process human language.

In finance, NLP can be applied to:

Financial news analysis
Market sentiment
Company reports
Research documents
Financial communications

FinTech Innovations and Digital Banking

Students explore technologies transforming banking and financial services.

Topics can include:

Digital banking
FinTech platforms
Digital payments
Financial automation
Emerging financial technologies

Portfolio Management and Robo-Advisory

This subject combines investment management with technology.

Students can learn about:

Portfolio construction
Investment decisions
Risk and return
Automated advisory
Robo-advisory systems

Corporate Governance and Compliance

Students also develop an understanding of governance and regulatory considerations within financial organisations.

The third term carries 16 credits.

Term 4 – Advanced AI & Financial Innovation

The final term focuses on advanced applications of artificial intelligence and financial technology.

Theories and Applications of Agentic AI

Agentic AI represents a newer direction in artificial intelligence, involving systems capable of performing tasks and taking actions based on defined objectives.

Understanding such technologies can be valuable for students interested in the future of intelligent financial systems.

Algorithmic Trading and Quantitative Strategies

Students explore how algorithms and quantitative methods can be applied to financial markets.

Potential applications include:

Market analysis
Trading strategies
Quantitative research
Automated trading
Financial modelling

Blockchain and Digital Currency

Students learn about blockchain technology and its relevance to digital financial systems.

Capstone Project

The programme concludes with a capstone project that allows students to apply their learning to a practical or research-oriented problem.

The fourth term carries 16 credits.

OP Jindal Online M.Sc AI & Finance Total Credits

The programme carries:

66 Credits

The credit structure is:

Term	Credits
Term 1	16
Term 2	18
Term 3	16
Term 4	16
Total	66

This structure combines finance, technology, analytics and practical learning throughout the programme.

Key Skills You Can Develop

One of the main advantages of an interdisciplinary programme is that students can develop both domain knowledge and technical capabilities.

1. Financial Analysis

Students develop an understanding of financial management, markets and financial instruments.

2. Python Programming

Python can be used for financial analysis, data processing and automation.

3. Financial Data Analytics

Students learn how data can be analysed to support financial decisions.

4. Artificial Intelligence

AI concepts can be applied to financial problems and business decisions.

5. Machine Learning

Machine learning can help identify patterns in financial data and build predictive models.

6. Algorithmic Trading

Students can explore quantitative strategies and algorithmic approaches to financial markets.

7. FinTech

The programme provides exposure to digital banking and financial technology.

8. Blockchain

Students learn about blockchain and digital currencies and their potential financial applications.

9. Risk Management

Technology and financial risk are important components of modern financial institutions.

10. Strategic Decision-Making

The combination of finance and AI can help students understand data-driven decision-making.

Career Opportunities After M.Sc Artificial Intelligence & Finance

The combination of finance and AI can lead to career opportunities across financial services and technology.

Potential career areas include:

AI-Finance Specialist

Professionals can work at the intersection of financial knowledge and artificial intelligence.

FinTech Analyst

FinTech analysts can work with digital financial products, platforms and technology-driven financial services.

Financial Data Analyst

These professionals analyse financial datasets to identify trends and generate insights.

Risk Analyst

Risk analysts evaluate financial and technology-related risks.

Investment Analyst

Investment professionals analyse markets, companies and financial information.

Quantitative Analyst

Quantitative roles involve using mathematics, statistics, programming and financial data to solve market-related problems.

Algorithmic Trading Professional

Professionals can work on quantitative trading strategies and automated financial systems.

Portfolio Analyst

Portfolio analysts support investment decisions and portfolio monitoring.

AI Consultant

AI consultants help businesses identify and implement suitable AI applications.

Digital Banking Professional

Graduates can explore roles involving technology-driven banking and financial services.

Career Scope in FinTech

FinTech is one of the most important areas connecting technology and finance.

The growth of:

Digital payments
Online banking
Digital lending
Robo-advisory
Blockchain
Digital assets
AI-based financial services
Automated investment systems

has increased the importance of technology within financial services.

Students with knowledge of both finance and technology can therefore explore opportunities in fintech companies as well as traditional financial institutions undergoing digital transformation.

AI in Financial Markets

Artificial intelligence is increasingly being used to analyse financial information.

AI can support areas such as:

Market research
Pattern recognition
Sentiment analysis
Financial forecasting
Risk analysis
Portfolio management
Fraud detection
Automated decision-making

The programme’s curriculum includes Natural Language Processing for Financial Markets, Algorithmic Trading and Quantitative Strategies, Portfolio Management and Robo-Advisory, giving students exposure to several technology-driven financial applications.

AI and Risk Management

Risk management is an essential function in financial institutions.

AI and data analytics can be used to analyse large datasets and identify patterns that may indicate financial risk.

Potential applications include:

Credit risk analysis
Fraud detection
Market risk analysis
Operational risk
Technology risk
Predictive modelling
Compliance monitoring

The OP Jindal programme includes Technology Risk Management as part of the curriculum, helping students understand the relationship between technology and financial risk.

AI and Algorithmic Trading

Algorithmic trading is an important application of technology in financial markets.

Instead of relying entirely on manual decisions, algorithmic systems can use predefined strategies and quantitative models to analyse market information and execute trades.

Students interested in this area can explore:

Quantitative strategies
Market data
Financial modelling
Trading algorithms
Risk management
Portfolio optimisation

The programme includes Algorithmic Trading and Quantitative Strategies in its fourth term.

AI and Portfolio Management

Portfolio management involves balancing investment objectives, risk and returns.

Technology can support portfolio management through:

Data analysis
Risk modelling
Automated recommendations
Portfolio monitoring
Asset allocation
Performance analysis

The programme specifically includes Portfolio Management and Robo-Advisory, allowing students to explore the role of technology in modern investment management.

What is Robo-Advisory?

Robo-advisory refers to technology-enabled investment advisory systems that use algorithms and data to provide automated portfolio recommendations or investment services.

Robo-advisory can combine:

Investor information
Risk profiles
Financial goals
Market data
Portfolio models
Automated recommendations

It represents one of the areas where artificial intelligence, data analytics and investment management increasingly overlap.

What is Agentic AI in Finance?

Agentic AI is an emerging area of artificial intelligence involving systems that can perform sequences of tasks based on objectives and available information.

In financial services, future applications could include:

Automated research
Financial analysis
Workflow automation
Risk monitoring
Portfolio support
Financial operations
Decision-support systems

The programme includes Theories and Applications of Agentic AI, giving students exposure to this emerging area.

What is Blockchain and Why Does It Matter in Finance?

Blockchain is a distributed digital record-keeping technology that can support secure and transparent transactions.

Its applications in finance can include:

Digital currencies
Payments
Settlement
Smart contracts
Digital assets
Financial record management

The programme includes Blockchain and Digital Currency as part of the fourth term.

Online Learning Format

The programme is delivered online and is designed to provide flexibility for graduates and professionals.

The current programme information highlights:

Live online classes
Digital learning resources
Practical projects
Real-world case studies
Financial datasets
Virtual learning experiences
Expert faculty

This format can be useful for working professionals who want to pursue postgraduate education without completely stepping away from their professional responsibilities.

Is OP Jindal Online M.Sc AI & Finance Suitable for Working Professionals?

Yes, the programme is specifically positioned for graduates and professionals who want to combine finance knowledge with AI, machine learning and analytics.

Working professionals from areas such as:

Banking
Finance
Accounting
Investment
Insurance
Business
Consulting
FinTech
IT
Data Analytics

can consider the programme if they want to develop interdisciplinary skills.

The online format can make it easier to continue professional commitments while studying.

Who Should Choose M.Sc Artificial Intelligence & Finance?

This programme can be suitable for students and professionals who:

Have completed graduation
Are interested in finance and technology
Want to learn AI applications
Want to enter FinTech
Are interested in financial analytics
Want to learn Python for finance
Are interested in algorithmic trading
Want to understand digital banking
Are interested in investment analytics
Want to explore AI-driven financial careers

It may be less suitable for students who have no interest in either finance or technology.

Admission Process for OP Jindal Online M.Sc AI & Finance 2026

Students planning to apply should follow the prescribed admission process.

Step 1: Check Eligibility

Confirm that you have an undergraduate degree with the required marks.

Step 2: Submit Application

Complete the application with the required academic and personal information.

Step 3: Submit Academic Documents

Applicants may need to provide academic transcripts and other supporting documents.

Step 4: Statement of Purpose

The selection process considers the candidate’s profile and Statement of Purpose (SOP).

Step 5: Review by the University

Applications are reviewed based on academic performance, transcripts and overall profile.

Step 6: Interview, If Applicable

Shortlisted applicants may be invited for a personal interview depending on the review of their application and SOP. Candidates with less than 50% marks are required to follow the applicable JSAT route.

Step 7: Final Admission

Selected students can proceed with offer acceptance and the applicable fee payment.

Selection Criteria

The current programme information states that admission decisions consider:

Academic performance
Academic transcripts
Statement of Purpose
Overall applicant profile

A personal interview may also be conducted for shortlisted candidates.

Students should therefore prepare a clear SOP explaining:

Why they want to study AI and Finance
Their academic background
Their career goals
Their interest in financial technology
How the programme fits their future plans

Documents Students Should Keep Ready

Applicants should generally keep the following documents available:

Class 10 certificate
Class 12 certificate
Graduation marksheets
Graduation degree or provisional certificate
Government-issued identity proof
Passport-size photograph
Academic transcripts
Statement of Purpose
Other documents requested during admission

The exact document requirements can vary according to the applicant’s academic background and admission cycle.

Benefits of OP Jindal Online M.Sc AI & Finance

1. One-Year Master’s Programme

The programme is structured over 12 months, allowing students to pursue specialised postgraduate education within a relatively short duration.

2. Finance + AI Combination

Students develop knowledge across two highly interconnected areas.

3. Python for Finance

The curriculum introduces Python specifically for financial applications.

4. FinTech Exposure

Students explore digital banking and financial technology.

5. Algorithmic Trading

The programme provides exposure to quantitative strategies and algorithmic trading.

6. Portfolio Management

Students learn about portfolio management and robo-advisory.

7. Blockchain

The curriculum includes blockchain and digital currency.

8. Agentic AI

Students can explore an emerging generation of AI systems.

9. Capstone Learning

The programme includes a capstone project for practical application of concepts.

10. Flexible Online Format

The online format can be particularly useful for working professionals and learners who require greater flexibility.

How to Build a Career in AI and Finance

A master’s degree can provide a strong academic foundation, but students should also build practical skills.

Learn Python

Start with Python fundamentals and gradually move into libraries used for financial data analysis.

Learn SQL

SQL is important for accessing and analysing financial databases.

Strengthen Statistics

Understand probability, statistics, regression and quantitative methods.

Learn Machine Learning

Develop knowledge of supervised and unsupervised learning and model evaluation.

Understand Financial Markets

Follow market developments and learn how different financial instruments work.

Build Financial Projects

Students can create projects such as:

Stock-market analysis
Portfolio optimisation
Financial forecasting
Credit-risk modelling
Fraud detection
Sentiment analysis
Robo-advisory simulation
Algorithmic trading strategy

Develop Communication Skills

AI professionals must be able to explain complex analytical results to business and finance teams.

Suggested Projects for M.Sc AI & Finance Students

Students can strengthen their portfolios through practical projects.

Project 1: Stock Market Prediction

Use historical financial data to experiment with predictive modelling.

Project 2: Financial Sentiment Analysis

Use NLP to analyse financial news or text and classify market sentiment.

Project 3: Portfolio Optimisation

Develop a model that evaluates risk and return across multiple assets.

Project 4: Fraud Detection

Build a machine-learning model to identify unusual financial transactions.

Project 5: Robo-Advisory System

Create a basic system that generates portfolio recommendations based on an investor’s risk profile.

Project 6: Algorithmic Trading Simulation

Develop and back-test a basic quantitative trading strategy using historical data.

These types of projects can help students demonstrate practical skills to prospective employers.

Career Scope After M.Sc Artificial Intelligence & Finance

The career scope of the programme extends across several sectors.

Banking

Banks are increasingly adopting AI for risk management, customer analytics, fraud detection and automation.

FinTech

FinTech companies use AI and data to create digital financial products and services.

Investment Management

Investment companies use analytics and technology for portfolio management and research.

Consulting

Consulting organisations require professionals who can understand both business and emerging technologies.

Insurance

AI can be used for underwriting, claims analysis, fraud detection and risk assessment.

Financial Technology

Professionals can work on digital banking, payments, lending and investment platforms.

Risk Management

AI and analytics can support financial and technology-risk monitoring.

OP Jindal Online M.Sc AI & Finance Admission Helpline

Students who want admission assistance for the programme can contact:

7973104914

The admission assistance helpline can be used for guidance regarding:

Programme details
Eligibility
Fees
Admission process
Application
Documents
Course structure
Intake information
Career scope

Admission Helpline: 7973104914

Frequently Asked Questions

1. What is OP Jindal Online M.Sc Artificial Intelligence & Finance?

It is a one-year online master’s programme combining artificial intelligence, finance, financial analytics, FinTech and emerging financial technologies.

2. What is the duration of the programme?

The programme duration is 12 months.

3. What is the total fee for OP Jindal Online M.Sc AI & Finance?

The current listed total tuition fee is ₹2,75,000.

4. What is the eligibility for M.Sc AI & Finance?

Applicants should have an undergraduate degree with at least 50% marks. Candidates with less than 50% marks may need to appear for the JSAT examination.

5. What is the batch start date?

The current programme listing shows the 1 September 2026 batch start.

6. How many credits does the programme have?

The programme carries 66 credits across four terms.

7. Is Python included in the programme?

Yes. The curriculum includes Python Programming for Financial Applications.

8. Does the programme include Machine Learning?

The programme includes AI-related applications and advanced technologies, along with subjects such as NLP for financial markets and Agentic AI.

9. Does the programme include FinTech?

Yes. FinTech Innovations and Digital Banking is part of the third term.

10. Does the programme include algorithmic trading?

Yes. Algorithmic Trading and Quantitative Strategies is included in Term 4.

11. Does the programme include blockchain?

Yes. The fourth term includes Blockchain and Digital Currency.

12. Is there a project at the end of the programme?

Yes. The final term includes a Capstone Project.

13. Can working professionals pursue this programme?

Yes. The online format is designed to support graduates and professionals interested in combining finance with AI, analytics and emerging technologies.

14. What career options are available after M.Sc AI & Finance?

Depending on skills and experience, graduates can explore roles in FinTech, financial analytics, risk management, investment analytics, algorithmic trading, digital banking and AI-driven financial innovation.

15. What is the admission helpline number?

The admission assistance helpline for this programme is:

7973104914

Final Conclusion

The OP Jindal Online M.Sc Artificial Intelligence & Finance 2026 is a specialised postgraduate programme for graduates and professionals who want to build expertise in the rapidly developing intersection of Artificial Intelligence and Finance.

The programme has a 12-month duration, 66 credits, and a currently listed total tuition fee of ₹2,75,000. The 2026 batch is listed to begin on 1 September 2026.

Its curriculum goes beyond conventional finance education by introducing students to Python programming for financial applications, financial data analytics, NLP for financial markets, FinTech, digital banking, portfolio management, robo-advisory, algorithmic trading, quantitative strategies, blockchain, digital currency and Agentic AI.

For students interested in FinTech, banking, investment analytics, financial data, risk management, algorithmic trading and AI-driven financial innovation, this interdisciplinary programme can provide a useful foundation for building a technology-focused finance career.

At the same time, students should focus on developing practical capabilities alongside their degree. Learning Python, SQL, statistics, machine learning and financial analysis, while building real-world projects, can make the academic qualification more valuable in the employment market.

If you are planning to apply, make sure you check your graduation eligibility, prepare your academic documents and understand the applicable fee and admission requirements before proceeding.

OP Jindal Online M.Sc Artificial Intelligence & Finance Admission Helpline

7973104914

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