Philip C.
Philip is a User Support Specialist at a finance data institution, where he leads his department's Python automation initiative. Previously, as a Support Engineer, he monitored the company’s entire fleet of transformers and analyzed data from its IoT sensor network. His research on machine learning in transformer health analysis was awarded the HKIE Outstanding Paper Award, one of two institutional recipients.
He holds a Master's in Engineering from HKU and is a licensed insurance intermediary.
Hong Kong SAR China
Machine Learning in Predictive Maintenance (https://youtu.be/mhnrzp9WgOA)
Session
Hong Kong’s Mandatory Provident Fund (MPF) is supposed to secure your retirement—but what if it’s secretly shrinking your savings? Using Python, we’ll simulate how high fees erode your returns over time, compare MPF performance against low-cost alternatives (like index funds), and uncover whether sticking with the default plan could cost you millions. Through interactive visualisations, we’ll expose the maths behind, and explore how self-directed investing might be the escape hatch.