澳大新語 • 2023 UMAGAZINE 28 16 封面專題 • COVER STORY 人的違約風險較高。該模型在評估信用卡申請者的債 務違約風險上也表現突出，商業價值顯著。」 大數據引領金融業 正如航海者參考精確的氣象數據來決定航向，今日的 金融機構和投資者同樣需要先進的數據科學技術來推 測市場走向和擬定投資策略。李教授指出：「運用大 數據是金融業人士維持競爭力的關鍵，也是澳門現代 金融業發展的重要方向。」 Master of Science in Data Science programme. Prof Lei, who also serves as the coordinator of the specialisation, says, ‘Developing the modern financial services industry is crucial for Macao as the city moves towards economic diversification. We foresee a growing demand for specialists in areas like data analytics, business analytics, and financial analytics in the coming years.’ According to Prof Lei, the specialisation encompasses the application of artificial intelligence, blockchain technology, cloud computing, and big data in the financial domain. ‘In addition to data collection and cleaning, students learn to use machine learning models ranging from decision trees to neural networks,’ Prof Lei adds. ‘This year, a graduate developed a system that integrates various machine learning models to predict default risks among peer-to-peer [P2P] lenders. The model also has the advantage of evaluating the default risk of credit card applicants, which underlines its considerable commercial value.’ Big Data at the Forefront of Modern Finance Just as navigators rely on accurate weather data to determine their course, financial institutions and investors need advanced data technologies to decode market trends and formulate investment strategies. Prof Lei concludes, ‘Tapping into the vast potential of big data is important for finance professionals to stay competitive. It is also a promising direction for Macao’s modern financial services industry.’ 李振國教授 Prof Henry Lei An immense volume of data flows through the financial sector every second. Henry Lei, associate head of the Department of Finance and Business Economics in the Faculty of Business Administration (FBA) at the University of Macau (UM), emphasises that machine learning models, by harnessing this data, can enhance investment strategies, reduce investment risks, and contribute to the development of new financial products. Nurturing Modern Financial Professionals The recent pandemic, wars, and the rise of artificial intelligence have amplified the fluctuations in financial markets. Using traditional econometric models alone may fall short in providing accurate analyses and forecasts for today’s dynamic markets. ‘By leveraging machine learning models trained on big data, financial institutions can devise superior investment strategies,’ says Prof Lei. ‘More importantly, they can gain a deep understanding of client needs, allowing them to provide tailored products.’ Experts in economics and finance also increasingly rely on big data for their research. Prof Lei, for example, has explored sentiments on social media regarding financial and asset markets. This approach provides insight into the correlation between poor financial or asset market performance and declining consumption. Recognising the evolving needs of the financial sector, UM’s Institute of Collaborative Innovation, in collaboration with FBA, has introduced the Financial Technology specialisation under the university’s
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