The Undoing of Cyber Financial Crime
Articles and Commentaries
Katelyn Wan Fei Ma has published in a number of leading journals and periodicals.
As a young researcher, Katelyn has gained a name as a leading voice in the area.
Training Anti-Fraud Professionals and Managing Anti-Fraud Operations: Challenges and Opportunities
Dec 23, 2021
As financial transactions move online, financial crimes also transition to cyberspace. The technological intricacies, social implications, and economic challenges implicit in cybercrime are pertinent concerns for the digital era. While the financial sector relies heavily on anti-fraud professionals to investigate and intervene in cyber fraud, operational complexities and training obstacles persist. Katelyn Wan Fei Ma highlights three common challenges to the training of professionals and management of anti-fraud operations and offers potential solutions: establishing a comprehensive, regularly updated fraud typology; strategic management of fraud victimization profiles; and an interdisciplinary approach to fraud data analysis.
Covid-19 and Cyber Fraud: Emerging Threats During the Pandemic
May 12, 2021
The emergence of the novel coronavirus (COVID-19) has threatened physical and mental health, and changed the behaviour and decision-making processes of individuals, organisations, and institutions worldwide. As many services move online due to the pandemic, COVID-19-themed cyber fraud is also growing. This article explores cyber fraud victimization and cyber security threats during COVID-19 using psychological and traditional criminological theories. It also provides a COVID-19-themed cyber fraud taxonomy using empirical evidence from institutional and agency reports. Through organizing COVID-19-themed cyber fraud into four different categorizations, we aim to offer classification insights to researchers and industry professionals so that stakeholders can effectively manage emerging cyber fraud risks in our current pandemic.
Artificial Unintelligence: How Computers Misunderstand the World
Aug 23, 2019
Siri, Amazon, Netflix, Uber, Tesla, Airbnb – as technologies have enabled greater conveniences for consumers, artificial intelligence (AI) has become ingrained in the fabric of our daily lives. AI is instrumental in systems of engineering, finance, education, marketing, media, and medicine. Machine learning, as a popular form of AI, now mines data and effectively predicts outcomes. Training data can be used to engage in supervised learning, unsupervised learning, or reinforcement learning processes, which can help existing algorithms improve programed and automated tasks, and consequently better serve the end-users with the preferred and intended responses. But should we be purely optimistic about the power of AI? In Artificial unintelligence: How computers misunderstand the world, Meredith Broussard questions this assumption. Although algorithms can calculate desired results and answer the questions we ask with a high degree of accuracy, AI does not always get things right.