Supervised Machine Learning (S-ML): An Introduction
Artificial intelligence systems can help solve business problems by answering questions and facilitating data-informed decisions. Machine Learning (ML) programs – which fall into two categories, supervised and unsupervised – use raw data to develop models that can produce actionable business intelligence. Both Supervised Machine Learning (S-ML) and Unsupervised Machine Learning (U-ML) systems can thus support […]
Unsupervised Machine Learning (U-ML)
When faced with large, unstructured, and unlabeled datasets, many companies use Unsupervised Machine Learning (U-ML) to discover patterns and identify previously unknown factors that may drive business outcomes. While U-ML is a potentially powerful tool, it is important to understand its limitations and the relative advantages of different approaches to it. This course provides a […]
Supervised Machine Learning (S-ML): In Practice
Supervised Machine Learning (S-ML) systems are widely used across business sectors. While they can help facilitate faster and better decision-making, however, there are pitfalls associated with their use. It is, therefore, important to understand their limitations before deploying such systems. It is also necessary to understand what types of data are needed to build effective […]
Datensicherheit
Running corporate systems involves more than guaranteeing that the system performs its function. Corporate IT also needs to manage software, database, and hardware maintenance, organize training and onboarding of new users, and ensure that systems are secure. The ongoing cost of achieving these goals far outstrips the upfront cost of buying software. This course provides […]
Crypto Assets
Blockchains and distributed ledger technologies can be used for various purposes. Among these is the creation of digital assets with certain unique features. Known as crypto assets, these are applications of distributed ledgers that are designed as a medium of exchange or store of wealth, although their infrastructure may be used for other purposes. The […]
Information Technology (IT) in Business
Information Technology (IT) has transformed business, and in recent years, this process has accelerated with the emergence of new networking and programming capabilities. While relatively few financial professionals need to develop coding skills, all can benefit from an enhanced understanding of the role of technology in the financial industry. This course provides an overview of […]
AI Applications: Credit Risk
Making credit decisions relies on careful analysis of all relevant information. Artificial Intelligence (AI) systems can help make the process of credit risk analysis more efficient, accurate, and effective. This course provides a high-level overview of the role that AI can play in credit analysis and credit decisions.
AI Applications: Robotic Process Automation (RPA) in Trade Processing
Trade processing includes operations such as settlements, lifecycle management, trade reconciliation, and reporting. These activities can be a significant cost center and businesses have made a major effort to streamline and simplify them. Robotic Process Automation (RPA) is a key tool for reducing errors, minimizing headcount, and increasing efficiency in trade processing. This course provides […]
AI Applications: Internet of Things (IoT)
As smart, connected devices proliferate, the Internet of Things (IoT) is growing rapidly, transforming businesses across industries. Increasingly, it is having a direct impact on financial services. This course provides a high-level overview of the IoT and its uses and limitations.
AI Applications: Fraud and Compliance
For financial companies, identifying fraud and managing compliance processes are key tasks that must be performed efficiently and effectively. Fortunately, AI systems have the potential to make these tasks easier, cheaper, and better. This course provides a high-level overview of the role that AI can play in fraud detection and compliance.