Notable Alumni Sharing Session titled Charting My Path : The Motivation That Led to My Achievements, that was held virtually on the 19th February 2025

Dear students and alumni,
 
We would like to extend our heartfelt appreciation for your participation to the Notable Alumni Sharing Session titled Charting My Path : The Motivation That Led to My Achievements, that was held virtually on the 19th February 2025.
 
A special thank you goes to our esteemed alumnus speaker, Mr. Wang Zhao Loon, who serves as an Assistant Manager at MSIG, specializing in Financial Risk within the Enterprise Risk Management (ERM) department. A former president of the UCSI Actuarial Science Student Association (ASSA) and completed an internship at NMG Consulting. With his strong actuarial foundation, he has advanced from an executive role in ERM to his current position, leveraging both quantitative and qualitative expertise to enhance organizational resilience.
 
Wang’s internship at NMG Consulting provided him with invaluable practical experience in the field of risk management enabling him to bridge theoretical concepts in practical settings. This formative experience was pivotal in shaping his career path and deepening his understanding the complexities of risk assessment and management complexities.
 
During the session, Wang shared his inspiring personal journey, from his time as a student at UCSI to his professional achievements at MSIG. He highlighted the motivations that have fueled his success, emphasizing the significance of personal drive and celebrating small milestones along the way. Wang encouraged attendees to uncover their intrinsic motivations and to embrace challenges as opportunities for growth. His heartfelt insights reminded everyone that every step, no matter how small, contributes to long-term and overall success.
 
The session was expertly moderated by Assistant Professor Dr. Khoo, the newly appointed Head of the Department for the UCSI Institute of Actuarial Science and Data Analytics for the programme of Actuarial Science and Applied Statistics.
 
 
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