"I'm a Finance student at KMITL. I'd describe myself as curious, calm under pressure, and someone who takes ownership. I enjoy solving problems with data and working closely with people."
A finance student who gravitates toward messy problems, data, and the people trying to solve them together.
Win Ko Aung is a Finance student at King Mongkut's Institute of Technology Ladkrabang (KMITL) Business School in Bangkok, pursuing a BBA in Global Business and Financial Management on a full scholarship. His experience spans research and consulting internships across Thailand, Singapore, and the US (remote), alongside a parallel track in data analytics, strategic research, and youth leadership across Myanmar and Thailand — from building Power BI dashboards to co-authoring an academic poster on AI investment strategy in supply chains, to directing a literature & arts committee for a youth leadership association.
He describes himself as curious, calm under pressure, and someone who takes ownership — equally comfortable building a revenue forecasting model for a Singapore fintech or coordinating a volunteer data team during a public health crisis.
Research, consulting, and finance internships across three countries — remote and on the ground.
Design sales-approach and income-approach comparable analyses for multi-family deals (using cap rates, NOI, and adjusted sales) to establish underwriting benchmarks, while concurrently analyzing 30+ single-family homes and duplex properties.
Built a 1,500+ partner database (agents, GCs, lawyers, PMs) across 15+ North Carolina & South Carolina cities from scratch to support deal origination.
Researched 100+ development projects and delivered weekly insight decks to senior executives, directly informing market entry and investment decisions.
Modeled market-sizing frameworks for MNC clients, validating an 8.62B market opportunity by breaking down demand top-down and bottom-up, delivering insights to Engagement Managers and Directors.
Evaluated 1,000+ products across quality, price, and type to benchmark competitors, with deep dives on 5–7 key competitors from a pool of 20+ across financials, marketing, and distribution.
Conducted industry entry research across 10+ APAC markets, synthesizing regulatory, competitive, and market size insights into actionable recommendations.
Built a weekly revenue forecasting model covering 200+ accounts with 2–3% variance accuracy, supporting cash flow management and revenue protection.
Investigated payment behavior across 1,400+ accounts, reducing overdue payments by 20% (~15K+ SGD weekly) and cutting bad debt exposure.
Resolved 50+ weekly payment issues, proposing and documenting revised SOPs that reduced recurring errors by 30%.
Led market entry and financial feasibility assessments for a pet care client, delivering strategic recommendations to executive stakeholders across 2 ASEAN markets.
Supported sector research and expansion strategy for a 15M+ follower Thai lifestyle media client; the strategy was implemented and contributed to market share growth in Indonesia.
Coordinated with 15+ cross-border teams while documenting project progress and ensuring timely execution.
A mix of analytical hard skills, collaborative soft skills, and the software fluency to act on both.
Data analysis, market simulation, and social impact — projects that show a few different sides of the same interest: turning information into decisions.
Analyzed structured sales data and built an interactive dashboard to identify performance trends and growth opportunities. Presented key insights and actionable recommendations to support business decision-making.
Athipay is a community-based health application designed for the prevention and mitigation of COVID-19, developed during the pandemic. The project was led by Impact Hub Yangon and young digital entrepreneurs as a voluntary initiative. Win contributed as a member of the Social & Data Team, responsible for collecting up-to-date data and gathering essential information for the application.
Poster presentation at a national undergraduate conference.
Abstract
Although artificial intelligence (AI) is changing at a rapid rate in how companies use supply chains, there has been no structured model or criteria developed by companies to help them decide where to allocate their money when it comes to investing in AI to benefit the financial success of the company and to support the advancement of the technical capabilities of the AI technology. In this paper, the authors develop a hybrid multilevel decision-making model. The model combines the concept of an AI capability maturity model (predictive, prescriptive, autonomous), the Supply Chain Operations Reference (SCOR) process framework (PLAN, SOURCE, MAKE, DELIVER, RETURN), and standard financial performance metrics to provide a method for evaluating strategic investment priorities within the context of supply chain processes. The model uses the Analytic Hierarchy Process (AHP) with an AI suitability coefficient to evaluate the strategic investment priorities for each of the different supply chain processes. Data from Amazon, Walmart, DHL, Maersk, and JD.com (2020–2024) were used to test the model; results suggest that the sourcing and production processes will have the largest structural-financial impact. Additionally, the SAIPI (Strategic AI Prioritization Index) provides a SCOR process-grounded and maturity-calibrated platform for the implementation of informed and evidence-based digital investment decisions.
Keywords: Artificial Intelligence, Supply Chain Management, SCOR model, Investment Analysis, AI Prioritization
Structured programs completed outside the classroom, in data, strategy, and design.
A running record of participation — from hackathons to academic conferences.
Leadership and volunteer roles across youth organizations and professional societies.
Supports faculty outreach, student engagement, and social media management for the school's international-facing initiatives.
Directed the Literature & Arts Committee and completed a four-week ANGL × MYEO leadership training, recognized for outstanding performance and dedication despite a demanding schedule.
Open to internships, research collaborations, and data-driven projects. Reach out any time.