Alvarez & Marsal Hong Kong Business Case Competition 2024

Alvarez & Marsal Hong Kong Business Case Competition 2024

Congratulations to our students for winning the Champion and Best Presenter in the Alvarez & Marsal Hong Kong Business Case Competition 2024!

The competition, organised by Alvarez & Marsal, aims to provide students with an opportunity to apply their business knowledge and skills to real-world challenges. The theme of the competition is “Embracing Digital Compliance: Navigating the Dynamic Tax Landscape”.

The competition consisted of two rounds. In Round One, teams submitted a detailed proposal on their strategy, and the Top 5 teams advanced to the Final Round where they presented their solutions at the Alvarez & Marsal Hong Kong Office.

From over 100 participating teams, our student team stood out by articulating innovative strategies while addressing the challenges of the tax industry in an increasingly digitalising economy. Congratulations again to our Champions.

More about the competition: https://ug.hkubs.hku.hk/competition/alvarez-and-marsal-hong-kong-business-case-competition-2024

 

Champion

Team Name: MBS Consulting

Mr. Leung Chun Long, BBA(IBGM), Year 2

Miss Mak Ho Yan, BEcon&Fin, Year 2

Mr. Tse Pun Yiu, BEcon&Fin, Year 2

(The team comprises 1 other team member from other university.)

 

Best Presenter

Mr. Tse Pun Yiu, BEcon&Fin, Year 2

 

Student Sharing:

During my internship at a financial institution, I worked on automation projects, and it was rewarding to apply that experience in the tax space during the competition, highlighting the importance of automation in the digital economy. Presenting to senior directors at Alvarez & Marsal provided valuable insights and further inspired me to explore how technology can shape the financial industry.

(by Mr. Leung Chun Long, Bowen)

 

This competition provided me with the opportunity to venture into the complex tax landscape, offering insights I had never imagined! It was an incredibly eye-opening experience that pushed me to quickly adapt and acquire knowledge in an unfamiliar domain. The challenge has strengthened my ability to navigate complexity with confidence and now I am feeling more prepared to embrace challenges in new and unfamiliar areas!

(by Miss Mak Ho Yan, Stephanie)

 

This was an incredibly rewarding experience to address the challenge of identifying a serviceable market within a vast potential client base in the tax services sector. We conducted a thorough feasibility analysis to evaluate the project’s practicality, while I dove deep into financial modelling to assess the value it could bring to Alvarez & Marsal. Our approach was grounded in detailed market research, exploring competitors and alternative solutions, which helped us craft a tiered pricing structure with premium features to drive adoption. Ultimately, it was exciting to present our idea and confidently address the judges’ doubts, making it even more satisfying to finally win a case competition with the right team after many previous attempts.

(by Mr. Tse Pun Yiu, Matthew)

Other Events
HKU Business School Releases a Comprehensive Evaluation Report on the Image-Generation Capabilities of AI Models
2025 | News
HKU Business School Releases a Comprehensive Evaluation Report on the Image-Generation Capabilities of AI Models
HKU Business School released a Comprehensive Evaluation Report on the Image Generation Capabilities of Artificial Intelligence Models, providing a systematic assessment of 15 text-to-image models and 7 multimodal large language models (LLMs). The results showed that ByteDance’s Dreamina and Doubao, as well as Baidu’s ERNIE Bot ranked among the top performers in terms of image content quality for new-image generation and image revision. However, despite DeepSeek having attracted global attention, its newly released text-to-image model, Janus-Pro, did not perform as well in new-image generation. HKU Business School researchers also found that while some text-to-image models excelled in content quality, their performance in safety and responsibility was significantly lacking. In general, multimodal LLMs demonstrated better overall performance compared to text-to-image models.
AI Image Generation Evaluation Results Released: ByteDance and Baidu Perform Well, DeepSeek Janus-Pro Falls Short
2025 | Research
AI Image Generation Evaluation Results Released: ByteDance and Baidu Perform Well, DeepSeek Janus-Pro Falls Short
The frontier of AI models has evolved beyond text processing to encompass the ability to understand and generate visual content. These models not only comprehend images but also generate visual content based on textual prompts. This study presents a systematic evaluation of the image generation capabilities of AI models, focusing on two core tasks: generating new images and revising existing images. Using carefully curated multidimensional test sets, we conducted a comprehensive evaluation of 22 AI models with image generation capabilities, including 15 text-to-image models and 7 multimodal large language models. The results show that ByteDance’s Dreamina and Doubao, as well as Baidu’s ERNIE Bot, demonstrate impressive performance in both new image generation and image revision tasks. Overall, multimodal large language models deliver superior performance compared to text-to-image models.