Banking in and before the 20th century lied on the analog end of the spectrum. Today, Banking and financial services has undergone a critical transformation. Banks are obliged to collect, analyze, and store massive amounts of data. Data Lakes and Knowledge Lakes, do a great job in organizing big data and providing answers on known questions, e.g., to understand the potentially interconnected data stored in various data islands and to prepare them for analytics. Machine learning is now crucial for effective detection and prevention of fraud involving credit cards, accounting, insurance, and more. Data science revolutionised banking tasks and activities such as risk modeling, lifetime value prediction, personalized marketing, real-time and predictive analytics and customer segmentation.
In particular, the advancement in Artificial Intelligence (AI), Data Science, Machine Learning, Natural Language Processing (NLP), Knowledge Representation, Software-as-a-Service and more, has the potential to transform the Banking ecosystem in fundamental ways. The core of the idea for AI-enabled Banking Stream is to advance the scientific understanding of Intelligence-Led and AI-enabled banking and to identify novel applications of AI and Data Science (from process automation, to cognitive assistants and smart entities) in banking and financial services.
Research Grants:
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Research Grant: "AI-enabled Banking"; Linkage: Tata Consultancy Services (TCS) and Macquarie University, 2019-2023 |