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The latest Blockchain and Digital Assets session brought together global participants to explore one of the most transformative shifts now reshaping global trade: the tokenisation of trade finance assets. Led by Saloi Benbaha, Head of XDC Network Enterprise Alliance & Ventures and Global Women in AI Ambassador, the session unpacked how tokenisation, harmonised standards and cross-industry collaboration are redefining efficiency, transparency and trust across the trade ecosystem.

With a career spanning telecom, banking, blockchain and energy, and fresh from receiving the Policy Pioneer Award at the House of Lords, Saloi delivered a masterclass on what financial institutions must understand to stay competitive in a rapidly digitising world.

Tokenisation as a Catalyst in Trade Finance

Saloi began by outlining why tokenisation is emerging as a foundational pillar in trade finance. Traditional trade processes are burdened by fragmented systems, inconsistent data, paper-heavy workflows and long settlement cycles. Tokenisation offers a fundamentally different model—one where assets, documents and processes can be digitised, standardised and exchanged with programmable trust.

By converting trade assets such as invoices, letters of credit, guarantees or receivables into tokens, institutions can benefit from:

• Faster settlement

• Improved liquidity

• Greater transparency and auditability

• Reduced operational risk

• Enhanced interoperability across platforms and borders

Tokenisation, Saloi emphasised, is not simply a technology upgrade. It represents a structural shift toward digital-native trade finance.

Why Standards and Interoperability Matter

A central theme in Saloi’s presentation was the critical need for standards. Tokenisation cannot scale in isolation. It requires:

• Shared data models

• Common identity frameworks

• Legal and compliance harmonisation

• Industry-wide agreement on asset definitions

Saloi highlighted how emerging frameworks—such as the Digital Standards Initiative (DSI) and those developed by leading industry bodies—are paving the way for unified digital trade ecosystems. Without such standards, tokenisation risks becoming siloed, fragmented and incompatible across markets.

Collaboration as the Engine of Adoption

Tokenisation thrives through collaboration, not competition. Banks, corporates, fintechs, regulators and technology networks must co-design solutions. Saloi’s work at the XDC Network Enterprise Alliance exemplifies this collaborative model, bringing stakeholders together to build shared infrastructure and tackle adoption barriers collectively.

She also emphasised the growing importance of public-private coordination, particularly around regulatory clarity and cross-border legal frameworks.

Becoming Tokenisation-Ready: Skills and Capabilities

Saloi provided a clear blueprint for organisations preparing to embark on tokenisation initiatives. Key skill areas include:

• Understanding digital asset frameworks

• Navigating compliance and regulatory design

• Smart contract literacy

• Process redesign and workflow digitisation

• Cross-functional collaboration between technology, operations and legal teams

Tokenisation is not an IT project, it is an organisational transformation that requires new digital competencies across the value chain.

Integrating Tokenised Solutions with Legacy Infrastructure

One of the session’s most practical discussions centred on how banks can integrate tokenisation into existing trade finance systems. Saloi highlighted that the most effective strategy is to begin with well-defined, high-value use cases, and then:

1. Identify assets that benefit most from digitisation

2. Map the current processes and pain points

3. Build tokenised modules that integrate via APIs

4. Adopt a phased rollout that maintains continuity with legacy operations

The goal is not to replace existing infrastructure immediately but to extend it with digital layers that introduce automation and interoperability.

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5 Key Learning Outcomes from the Session

1. Tokenisation transforms trade finance by digitising assets end-to-end
It streamlines processes, increases liquidity, accelerates settlement and reduces friction that has long slowed global trade.

2. Standards are essential for scalable adoption
Without alignment on data, identity and legal frameworks, tokenisation remains isolated. Industry-wide standards unlock interoperability and global connectivity.

3. Collaboration drives real-world implementation
Tokenisation succeeds when banks, corporates, regulators and networks work together to redesign trade processes, not when each operates alone.

4. Successful tokenisation requires new digital skills across organisations
Teams must understand blockchain concepts, regulatory expectations, smart contracts and process redesign, not just technology.

5. Integration with legacy systems must be phased and strategic
Institutions should start with clearly defined assets and use cases, then layer tokenisation onto existing infrastructure through modular, API-driven approaches.

As trade finance undergoes rapid digital transformation, tokenisation stands out as a powerful enabler of transparency, speed and global interoperability. Saloi’s session showed that the future of trade will not simply be digitised, it will be standardised, collaborative and token-powered. For institutions looking to stay competitive, now is the moment to build the skills, partnerships and technological foundations needed to thrive in this new era. With growing momentum across industries and governments, the shift toward digital trade finance is no longer a possibility, it is already underway.

 

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If you want to become an expert in Artificial Intelligence to pivot the career, optimise work tasks or reskill into a new job, you are at the right place. Structured knowledge is key to understanding how technology works, especially in the highly complex domain of Artificial Intelligence. Therefore, we picked the best courses on the market as of today – combining focused learning structure, leading experts and well-regarded certifications. Designed for beginners, students, or c-suite executives, no course is the same.

Explore the leading AI courses of 2023:

1. CFTE – Generative AI 360 Course

Summary: The Generative AI 360 specialisation curated with leaders at the forefront of AI is designed for those hungry to learn AI, but with little time to spare. This specialisation includes video lectures, industry experts interviews, hands-on projects to use Generative AI tools in finance, supplementary readings and tests, which guide participants through the entire Generative AI environment. The specialisation also includes 12 optional monthly live sessions with leading ecosystem players to provide you with the skill-set needed to thrive in Generative AI.

Advantages:

• Bite-sized Courses: You can easily fit in 15 minute bite-sized courses into your your busy daily schedule;
• Learn form top executives: You will gain knowledge directly from leading experts in finance, tech, consulting and academia;
• Gain all-rounder Knowledge: This programme will help you cover all the fundamentals of Generative AI, applications and regulations;
• Learn to apply technologies on real projects: The course will help you build the right skills to apply Generative AI to financial services;
• Interact with leading experts: You will learn directly from those who build the AI ecosystem from the monthly live sessions on Generative AI.

Key lecturers:

• Huy Nguyen Trieu (CEO – The Disruptive Group | Co-Founder – CFTE | Associate Fellow – Oxford)
• Dr Prag Sharma (Global Head of AI – Citi)
• Mehdi Ghissassi (Director & Head of Product – Google DeepMind)
• Gilles Moyse (Co-founder/CEO – Récital)
• Yasmina Benkhoui (Senior Manager – NVIDIA)
• Jeremie Cornet-Vuckovic (Senior Manager in Data Consulting – Artefact)
• Nikola Lazarov (Co-founder/CEO – Eilla AI)
• Petar Petrov (Co-founder/CCO – Eilla AI)

Level: Beginner/Intermediate

Cost: £450

Duration: 15 minutes a day, over 6 weeks

Study Structure/Method:

• Course Format: 100% Online
• Course Access: 6 months access to content from the start date
• Course Model: Instructor-Led

2. CFTE AI in Finance Specialisation

Summary: The specialisation explores how machine learning and new AI technologies are transforming all sectors of the banking and finance landscape. Thousands of professionals including those in financial institutions, industry associations, Tech companies, Fintechs and entrepreneurs have already enrolled. The specialisation is composed of 4 individual courses from AI fundamentals, AI technology to implementations.

CFTE offers Corporate Training for teams with our AI in Finance program.

Advantages:

• In-depth Knowledge: Understand the foundations and applications of AI technology as well as the opportunities and risks associated with it;
• Applications and Implementation: Understand the potential benefits and challenges of AI in the industry;
• The Underlying Mechanisms of AI: Understand the development of AI and its training stages;
• Global landscape and market trends: Explore real-world use cases in customer service, risk management, wealth management and many more;
• Workplace Incorporation. Use AI knowledge and apply it in diverse settings from generating market reports to writing code;
• Enhance your skillsets and get employment opportunities in finance and technology with the most up-to-date and insightful industry knowledge on AI.

Key lecturers:

• Jean-Philippe Desbiolles (Managing Director – Financial Services, IBM)
• David Hardoon (Group Chief Data & AI Officer – Union Bank)
• Shonali Krishnaswamy (Chief Technological Officer – AiDA
• Frank Chen (Senior Software Engineer – Google Research)
• Winnie Cheng (Director of the AI Lab – PwC)

Level: Beginner/Intermediate

Cost: £600

Duration: 2-3 hours per week for 8 weeks

Study Structure/Method:

• Course Format: 100% Online
• Course Access: 6 months access to content from the start date
• Course Model: Instructor-Led

3. MIT Sloan School of Management: Artificial Intelligence: Implications for Business Strategy Online Short Course

Summary: The course focuses on the organizational and managerial implications of artificial intelligence technologies and how they can be applied in the workplace, rather than on their technical dimensions. The design of this course prepares current managers and high-level executives with strategic decision-making skills to effectively analyze and articulate key AI management and leadership insights in their work with teams and organizations.

Advantages – The course introduces AI and its practical use cases for business applications, helping participants transform organisations into a future-forward business.

Key lecturers:

• Thomas Malone (Professor of Management – MIT Sloan School of Management)
• Daniela Rus (Director – MIT Computer Science and Artificial Intelligence Laboratory (CSAIL))

Level: Intermediate

Cost: £2,600

Duration: 6–8 hours per week over 6 weeks

Study Structure/Method: fully online, check for the next enrolment date

4. The University of Texas at Austin: AI & Machine Learning in the Financial Industry

Summary: Having a good grasp of machine learning is becoming a necessary skill in the labor market. This course provides an overview of machine learning applications in finance. After you complete this course, you will be able to have a detailed understanding of what machine learning is, and how it is applied in the financial sector.

Advantages – The course is structured into three main modules and shows how large financial institutions and fintech startups use machine learning to improve their financial products.

Key lecturers:

• Cesare Fracassi (Associate Professor of Finance – University of Texas at Austin)

Level: Intermediate

Cost: £646

Duration: 5–6 hours per week over 4 weeks

Study Structure/Method: fully online, check for the next enrolment date

5 . The Wharton School of the University of Pennsylvania: AI applications in Marketing and Finance

Summary: AI-powered applications can enhance the customer journey and extend the customer lifecycle. Students will learn how this AI-powered data can enable you to analyze consumer habits and maximize their potential to target your marketing to the right people; fraud, credit risks, and how AI applications can combat the ever-challenging landscape of protecting consumer data.

Advantages – The course teaches how to set KPIs to measure performance of your brand new AI strategy and select metrics to gauge and tweak performance.

Key lecturers

• Michael R. Roberts (Professor of Finance – The Wharton School of the University of Pennsylvania)
• Kartik Hosanagar (Professor – The Wharton School of the University of Pennsylvania)
• Raghu Iyengar (Professor – Wharton School and faculty director of Innovation)

Level: Beginner/Intermediate

Cost: $99

Duration: 2 hours per week over 4 months

Study Structure/Method: self-paced online learning

6. Quant University: Machine Learning and AI for Financial Professionals

Summary: This course aims to bring clarity on how AI and machine learning are revolutionizing financial services. Get an introduction of the key concepts and, through examples and case studies, understand the role of machine learning, data science techniques, and AI in the investment industry.

Advantages – The course provides knowledge of Machine Learning and AI techniques and practical case studies of AI in finance with fully functional code.

Key lecturers

• Sri Krishnamurthy (Founder – Quant University)

Level: Mid to senior level professionals

Cost: $581

Duration: 13-14 hours

Study Structure/Method: self-paced online learning

7. Udacity – AI for Trading 

Summary: The course provides complete real-world projects designed by industry experts, covering topics from asset management to trading signal generation. It also teaches on AI algorithms for trading to build a career-ready portfolio.

Advantages – The course deep dives into different financial knowledge in trading and discuss the AI algorithms for trading with use cases.

Key lecturers

• Parnian Barekatain (Self-taught AI programmer and Researcher)
• Elizabeth Otto Hamel (PhD in Applied Physics from Stanford University)

Level: Beginner/Intermediate

Cost: £659

Duration: 4 months

Study Structure/Method: self-paced online learning

8. Harvard Professional Certificate in Computer Science for Artificial Intelligence 

Summary: This certificate takes a deep dive into the concepts and algorithms at the foundation of modern artificial intelligence. This series will lead you through the common programming languages, then carries that foundation through CS50’s Introduction to Artificial Intelligence with Python.

Advantages – The course focuses on theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence to teach participants on how to design intelligent systems of their own.

Key lecturers

• Doug Lloyd (Senior Preceptor in Computer Science – Harvard University)
• David J. Malan Gordon McKay (Professor of the Practice of Computer Science – Harvard University)
• Brian Yu (Senior Preceptor in Computer Science – Harvard University)

Level: Intermediate

Cost: $466

Duration: 5 months

Study Structure/Method: self-paced online learning

9. Oxford Artificial Intelligence Programme

Summary: The programme aims to provide with a sound understanding of AI: its history, functionality, capabilities, and limitations. On completion, particpants develop an informed opinion about the possibilities AI holds, and be able to reflect on its ethical implications and potential applications in your organisation.

Advantages – The programme provides participants with diverse insights and perspectives on the ethical, legal, and social considerations around AI so that they are equipped to critically appraise AI technologies.

Key lecturers

• Matthias Holweg (Professor of Operations Management – Saïd Business School, University of Oxford)

Level: Beginner/Intermediate

Cost: £2,200

Duration: 6 weeks

Study Structure/Method: self-paced online learning

10. Artificial Intelligence: Business Strategies and Applications by Berkeley

Summary: This program helps introduce the basic applications of AI to those in business. While participants learn about AI’s current capabilities and potential, they also gain deeper knowledge about the reach of automation, machine learning, and robotics..

Advantages – This program helps introduce the basic applications of AI to those in business. While participants learn about AI’s current capabilities and potential, they also gain deeper knowledge about the reach of automation, machine learning, and robotics.

Key lecturers

• Sameer B. Srivastava (Professor and Harold Furst Chair – Management Philosophy and Values)
• Thomas Lee (Associate Adjunct Professor – Research Scientist)
• Zsolt Katona (Assistant Professor of Marketing at Berkeley)

Level: Intermediate

Cost: $ 2492

Duration: 2 months

Study Structure/Method: self-paced online learning

Which AI course should I choose?

What AI course is best for you really depends on your final goal and what angle of AI you are interested in. Practice-based courses like the ones offered by Generative AI 360 and AI in Finance by CFTE allow to gain a clear understanding between the AI technologies, tools, and how those can be used in every day business processes.

Our list shows that AI is a wide subject – and some of the courses provide a narrow approach to learning. For example, courses by Harvard and Udacity would be greatly beneficial for those looking to optimise their trading success, or bring AI into their code.

On the flip side, if you want a general introduction to AI, then the CFTE Generative AI 360 or Oxford Artificial Intelligence Program would be great options.

In any case, the impact of AI on modern skills is undeniable, learning is essential, so you are on the right track!

Looking to Upskill Your Organisation?

Join the AI revolution organisational learning solutions by CFTE

The post 10 Best AI Online Courses & Certifications in 2023 [UPDATED] appeared first on CFTE.

CFTE is proud to be a partner of the MENA Future of Fintech event, on the 9th & 10th of February, that aims to navigate the fate of a growing fintech sector in the region. MENA has experienced accelerated growth in fintech, catalysed by COVID-19. The region’s aim now is to strategically plan how to reap true benefits from this evolving landscape. Aligned with MENA’s goal, CFTE aims to extend their support as Tram Anh Nguyen, CFTE’s co-founder, delivers a keynote, during the event, on the roadmap to reskill the workforce for this booming sector.

The COVID-19 pandemic has accelerated fintech growth in MENA’s financial sector, forcing businesses and governments to craft a strategic response to this sudden spurt of growth. The MENA Future of Fintech event on the 9th and 10th of February 2021, aims to bring together thought leaders in the fintech scene so they can collaboratively fabricate the best way forward. Aligning with their vision, the Centre of Finance, Technology and Entrepreneurship (CFTE) is honoured to partner with MENA Future of Fintech to support their efforts, along with CFTE’s valued partner, ADGM. 

CFTE has been an active contributor in bolstering the growth of finance professionals in the MENA region by upskilling and reskilling the workforce to disrupt the traditional mindset in finance. Notably with Abu Dhabi Global Market’s Academic body, ADGM Academy, as they co-developed the AI in Finance certification, aiming at making banks in MENA AI-Ready.

Extending our efforts to help the MENA region gain new skills at scale, Tram Anh Nguyen, CFTE’s co-founder, will be delivering a keynote speech on the “Reskilling Urgency”. The Keynote aims to prompt action by addressing the reskilling urgency, demystifying the current skills gap and shedding light on possible opportunities to overcome challenges in the education and training landscape.

CFTE is proud to join forces with the MENA Future of Fintech event, that will also feature an astounding line up speakers, comprising of David Hardoon, Senior Advisor for Data and AI at UnionBank of the Philippines and Ritesh Jain, Co-Founder of Infynit, who are also Senior Lecturers and Experts at CFTE.

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CFTE Co-Founder Tram Anh Nguyen was vocal at Malaysia Digital Economy Corporation’s #MyDigitalWorkforce week on the HOWs to upskill and re-skill in a digital world, as unemployment is rising and the pandemic reaches its peak.

In a post-COVID19 world, where the acceleration of digitalisation is widening the skills gap, it is essential for governments and businesses to take the necessary steps to stay relevant and ahead of these constant changes.

Last week, MDEC’s #MyDigitalWorkforce aimed to tackle this ongoing issue to find solutions at scale for businesses and governments. Tram Anh Nguyen, CFTE’s Co-Founder, shared that in the midst of the current pandemic it is no longer about the WHY but about the HOW to reskill.

Alongside Tram Anh, a panel discussion between EdTech leaders took place to share thoughts and insights on COVID19’s impact on the industry, the most engaging training methods, and future skills needed for the workforce.

Speakers included:

 – Maria Khor, Malaysia Digital Economy Corporation’s Head of Digital and Data Workforce

 – Ming chin kok, CIMB’ Head of Regional Learning & Development

 – Manmeet Singh, Citi’s Digital Skills Practice Area Lead

At CFTE, we believe that governments and regulators play a critical role in upskilling and re-skilling millions, but that this is a challenging task because of 3 main reasons:

 – Governments have traditionally focused on education for children, rather than systematic training for     adults,

 – The role of government – vs employer – is usually not well defined,

 – The best practices in this area are not clearly defined.

The event’s final thought was that the urgency of reskilling is NOW, and we need to take action. Read More.

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