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AI and Data Foundations for Financial Services
Discover how data science, machine learning, and AI are transforming financial services. This programme equips professionals with the skills to harness these technologies for efficiency, innovation, improved risk management, and ethical, data-driven decision-making.
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Introduction to Data Science in Finance
Machine learning, artificial intelligence, supervised learning, clustering... there are a lot of data science terms and not much clarity. However, these concepts are becoming increasingly more common in our technological society. Join Carlos Salas as he breaks down what these concepts mean and their application in finance.
Carlos Salas • 11:21
Introduction to Data and AI
In this video, Elizabeth explores the transformative impact of data science, big data, and AI on the finance industry, highlighting innovations such as AI-driven fraud detection and personalized customer service. She delves into the essential concepts of these technologies, their roles in decision-making, and their broader societal implications, providing valuable insights for anyone looking to understand the future of finance.
Elizabeth Stanley • 10:46
Digital Authentication Introduction
Every time we buy online, post on social media or send a work email, we're using some form of personal identification. But how do the companies know if it's really us doing these things or an imposter? Your password is a good start. In this video, Ciarán Rooney lays the groundwork on digital authentication, from how the concept of passwords came to be and how we measure how good a password is.
Ciaran Rooney • 07:40
Types of Fintech Data and Data Privacy
The media often talks about privacy in the Fintech world. In this video in the series on Fintech Data, Marta answers key privacy questions, including what anonymised data is, what pseudonymised data is and what the advantages of using pseudonymised data are.
Marta Dunphy-Moriel • 07:54
Types of Machine Learning Models
The choice machine learning model is dependent on the specifics of the problem and the data at hand. Join Carlos Salas as he guides you through the differences between supervised and unsupervised machine learning models, including principal component analysis, generalised linear models and support vector machines.
Carlos Salas • 09:05
Accelerating Climate Action with AI
Climate-related data is booming. More organisations are publishing data related to their net zero targets and sustainability commitments. But how can we track it all? Join James Zhang as he explains how artificial intelligence is solving climate data challenges.
James Zhang • 11:14
Email Encryption Techniques
Now you understand the basics of cryptography, you can learn how it is applied to email encryption. Join Ciarán Rooney in this video as he explains why it is needed, the different stages at which a mail can be intercepted and the standards used for email encryption today.
Ciaran Rooney • 10:45
Implementing GDPR Privacy Compliance
In this video Punit outlines three crucial steps to implementing privacy compliance in your company. The first being to set up a strong foundation, for example appointing a DPO. Secondly, manage different actions that help compliance with various requirements of GDPR with a checklist. Thirdly, ensure it is sustainable.
Punit Bhatia • 10:11
Your Role in a Data or AI Project
In this video, Paul explains the essential elements for successful AI projects in financial services, covering the importance of clear goals, realistic expectations, and strong data strategies. He highlights key warning signs, such as overambitious goals and poor data quality, that can jeopardise project success. He also discusses the crucial role of non-practitioners in evaluating AI initiatives, emphasising their responsibility to bridge technical and business teams. By collaborating with AI experts and prioritising ethical and legal considerations, non-practitioners can support AI projects that deliver value aligned with organisational goals.
Paul dos Santos • 09:55
