AI in Financial Services: Foundations through future trends
Saïd Business School via Coursera Specialization
Overview
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The financial sector is being reshaped by Artificial Intelligence, Open Finance, and the rise of data-driven innovation. In this three-course specialisation, you’ll explore how AI technologies like machine learning and natural language processing are transforming financial services, while gaining a critical understanding of the ethical, regulatory, and strategic implications. You'll also examine how Open Finance is expanding beyond banking to include insurance, pensions, and investments, giving consumers greater control over their data and financial lives. From foundational concepts to advanced applications, the courses cover emerging global frameworks, API infrastructure, intelligent product design, and real-world use cases. Whether you're a finance professional, policymaker, entrepreneur, or technologist, this specialisation will equip you to navigate and shape the next generation of financial services.
Syllabus
- Course 1: AI Fundamentals in Financial Services
- Course 2: Designing the Future of Finance
- Course 3: Open Data and Intelligent Finance
Courses
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Artificial Intelligence (AI) is rapidly reshaping the financial services landscape. From fraud detection and algorithmic trading to customer service chatbots and credit scoring, AI is at the heart of a new era in finance. This course is designed to give you a clear, practical understanding of how AI works, what it enables, and how it’s transforming the way financial institutions operate. Through real-world examples, case studies, and engaging learning activities, you’ll gain insights into the key technologies that make AI possible, including machine learning, deep learning, and natural language processing, and see how they are applied across core functions in banking, fintech, and asset management. You’ll also explore how data drives these systems, the different learning methods AI uses, and the implications for strategy, governance, and ethics. Whether you’re a financial professional, policymaker, or simply curious about the future of finance, this course will equip you with the knowledge and confidence to engage in AI-related conversations and decision-making. No programming background is required, just an interest in how technology is shaping the future of financial services. By the end of the course, you will be able to: • Understand the foundational technologies that underpin Artificial Intelligence (AI), including Machine Learning, Natural Language Processing, and Deep Learning. • Explore the central role of data in powering AI systems, and the key learning methods used to train them. • Identify how AI is applied in financial services, including use cases such as fraud detection, credit scoring, customer service, and algorithmic trading. • Critically evaluate the risks, limitations, and ethical challenges associated with deploying AI in financial services. This course is the first in the AI in Financial Services: Foundations through Future Trends specialization. It provides the essential groundwork for understanding how AI works and why it matters in finance. After completing this course, we recommend continuing with 'Designing the Future of Finance' and 'Open Data and Intelligent Finance' courses to explore how AI intersects with Open Finance, embedded systems, and intelligent, ethical financial innovation.
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Artificial Intelligence is reshaping financial services, but its success depends on the infrastructure that powers data access, control, and interoperability. This course explores how Open Banking, Open Finance, and platform-based models are transforming the design and delivery of financial services around the world. You’ll examine how regulatory frameworks, API ecosystems, and evolving consumer expectations are enabling smarter, more personalized financial products. Building on the foundation of Open Banking, you’ll learn how Open Finance expands access to a broader set of financial data and what this means for innovation, competition, and inclusion. Through real-world case studies, strategic insights, and global policy comparisons, this course offers a practical, forward-looking view of the open financial ecosystem. Whether you’re a policymaker, technologist, financial professional, or curious learner, you’ll come away with the context and confidence to engage with the future of AI-enabled finance. By the end of the course, you will be able to: • Explain the evolution of financial infrastructure from traditional institutions to open, platform-based ecosystems. • Describe the core principles, objectives, and regulatory frameworks underpinning Open Banking and Open Finance initiatives. • Evaluate the strategic role of data accessibility and interoperability in enabling AI applications in financial services. • Analyse real-world case studies that illustrate how Open Finance and AI are being implemented globally. • Identify the opportunities and challenges presented by embedded finance, disintermediation, and platform envelopment. • Assess how emerging financial infrastructure impacts the design and deployment of intelligent, data-driven financial products. This is the second course in the 'AI in Financial Services: Foundations through Future Trends' specialization. We recommend completing 'AI Fundamentals in Financial Services' course first for a strong foundation before exploring the technologies and strategies shaping the future of Open Finance.
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Financial services are changing, from how they’re designed to how they’re delivered. Increasingly, the tools we use to bank, borrow, save, and invest are powered by artificial intelligence, delivered through platforms, and built on open data infrastructure. But what happens when finance becomes invisible? When decisions are automated? When users don’t realise they’re engaging with a financial product? This course explores the rise of intelligent, data-driven finance and how to design systems that are not only efficient but also ethical and inclusive. You’ll learn how Open Data and Open Finance enable cross-sector innovation, and how AI transforms static products into real-time, personalised services. You’ll explore embedded finance models and platform architectures, and examine real-world case studies from global leaders like the UK, India, and Brazil. Along the way, you’ll investigate risks, from consent fragmentation and data inequality to black-box decision-making and regulatory blind spots. Through hands-on activities and a final design project, you’ll apply your learning to propose responsible, user-centred innovations for the future of finance. By the end of the course, you will be able to: • Define the principles and evolution of Open Data and its relationship to Open Banking and Open Finance. • Analyse the key technical, legal, and ethical components that support intelligent, data-driven financial ecosystems. • Evaluate how AI and blended data sources can improve personalisation, credit access, and service delivery. • Interpret global Smart Data initiatives and policy frameworks in countries like the UK, India, Brazil, and Australia. • Identify risks and governance challenges associated with AI, privacy, consent, and data inequality in finance. • Design responsible, inclusive data-sharing strategies that align with transparency, fairness, and innovation goals. This is the third course in the 'AI in Financial Services: Foundations through Future Trends' specialization. We recommend completing 'AI Fundamentals in Financial Services' and 'Designing the Future of Finance' courses first for a strong foundation before exploring open data and intelligent finance.
Taught by
Martin Schmalz and Pinar Ozcan
Tags
Reviews
5.0 rating, based on 1 Class Central review
4.7 rating at Coursera based on 84 ratings
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This course is a must for anyone looking to understand how AI is transforming finance. It covers the foundations of AI, including machine learning, natural language processing, and data analytics, and connects them directly to financial services applications like fraud detection, algorithmic trading, credit scoring, customer service automation, and risk management.