The same record as below, told in order: where the research question came from, what I built, what it found, and what I want to study next. Present it to step through one highlight at a time.
1Who I am
Accounting and finance graduate, doing empirical research on digital payments
BSc (Hons) Accounting and Finance from the University of Birmingham, taught in English at its Singapore campus: Class II (Division I), GPA 3.25, with the degree to be conferred on 12 November 2026. I am seeking graduate roles in financial data analysis and master's study in finance or business analytics.
2Where the question came from
A coursework finding became my research question
In my Business Analytics Tableau story, submitted in December 2025, digital payment use ran ahead of debit-card ownership. That raised the question my final-year project tested: what happens to banks' fee income as payments move away from cards?
3What I studied
A bank panel I built and estimated myself
39 commercial banks in Indonesia, Malaysia and Thailand, 344 bank-year observations, 2014–2022. I built the Python pipeline, merged in the IMF digital-payment indicator, and estimated bank and year fixed-effects models with bank-clustered standard errors. The research report scored 80/100, above the cohort's upper quartile.
4What it found
A negative association, stated with its limits
The log model shows a negative, statistically significant pooled association between digital payment pressure and net fee margins. The decomposition suggests it comes mainly from differences between countries, so I report a conditional association, not a causal effect.
At Evershine CPAs, from July to September 2025, I worked on Philippines tax incentive applications, preparing and checking supporting documentation, including BOI Form 501. I also mapped the procedure into SOP flowcharts that the team used for the workflow and for handover.
6What next
From associations to identification
In master's study I want to test designs that can identify an effect: event studies around staggered payment-licensing reforms, inference suited to few clusters, and fee income broken down into payments, cards and merchant services.
Education, research and practice, 2023–2027
Dates as on this CV. The final-year project is drawn across the 2025–26 academic year; hover or tab to a bar for its dates.
Step {n}Step {s} of {n} · note {c} of {m}Link copied: {h}Could not copy. The link is {u}Numbers behind step {n}{t} of {total} · this step about {step} sTimeline, 2023 to 2027: SIM Diploma from April 2023 to June 2024; BSc at the University of Birmingham from September 2024 to June 2026; internship from July to September 2025; Tableau story submitted in December 2025; final-year research project in 2025–26; degree conferred on 12 November 2026; next, master's study.EDUCATIONRESEARCHPRACTICESIM DiplomaBSc, BirminghamDegree conferredNext: master'sFinal-year researchEvershine internshipTableau storyApril 2023 – June 2024September 2024 – June 2026 · Class II (Division I) · GPA 3.2512 November 2026Applying for master's study2025–2026 · report component 80/100July – September 2025 · tax advisory teamSubmitted December 2025 · 70/100My markCohort meanUpper quartileMaximumShaded: upper quartile to maximumResearch report component: my mark 80 against a cohort mean of 67, an upper quartile of 73 and a maximum of 84.Tableau assignment: my mark 70 against a cohort mean of 63.7, an upper quartile of 70 and a maximum of 76.{name}: {i} of {n} · press again for the next
YCYu-Chen Chao (趙于楨)
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Profile
I am seeking graduate roles in financial data analysis, banking analytics, and FinTech strategy, and master's study in finance or business analytics.
Accounting and finance graduate with a completed empirical research project on digital payment pressure and bank net fee margins in an ASEAN-3 bank panel (39 banks, 344 bank-year observations, 2014–2022). Comfortable across the whole research workflow: building a clean panel dataset, documenting variable definitions, estimating fixed-effects models with clustered standard errors, testing robustness, and communicating what the evidence does and does not support. Additional experience in Tableau data storytelling and cross-border tax work.
Education
Degree
BSc (Hons) Accounting and Finance — University of Birmingham
September 2024 – June 2026 · Degree to be conferred 12 November 2026 · Class II (Division I) · Overall weighted mark 61/100 · GPA 3.25
University of Birmingham · Singapore · Campus: Totally Taught Abroad · Language of instruction: English.
Diploma
SIM Diploma in International Business
April 2023 – June 2024
Research experience
2025–2026 · Final-year project
Digital payment pressure and bank net fee margins — ASEAN-3 bank panel
Accounting and Finance Research Project · University of Birmingham
Research report component: 80/100 (65% of module; module total 77/100 on transcript) · above the component's upper quartile (73), i.e. top 25%; cohort mean 67, maximum 84
Designed the study around an explicit research question and defined the estimation sample: 39 listed commercial banks, 344 bank-year observations, 2014–2022.
Built a Python pipeline to prepare the bank panel, discover and extract the IMF Financial Access Survey indicator IMF_FAS_FCMIBT, and merge the country-year measure into the bank-year panel.
Constructed Net_Fee_Margin and financial controls, winsorised continuous variables at the 1st and 99th percentiles, and formed a complete-case estimation sample.
Estimated bank and year fixed-effects models with bank-clustered standard errors using linearmodels, then tested log, bank-size interaction, nonlinear and country-subsample specifications; checked the result with Driscoll–Kraay errors, a Mundlak decomposition, a one-year lag and a net-interest-margin placebo.
Reported results as conditional associations, stating the data-level, coverage, and omitted-variable limitations explicitly.
Published a public research report, variable definitions, and a methodology appendix, plus a runnable synthetic fixed-effects example with an automated test.
Python
pandas
NumPy
linearmodels
statsmodels
matplotlib
pytest
Git and GitHub
Business Analytics coursework
Mobile money adoption in the Global South — Tableau story
Business Analytics module · University of Birmingham
Tableau assignment 70/100 (module mark 70/100 on transcript) · equal to the cohort's upper quartile (70); cohort mean 63.7, maximum 76
Cleaned and documented the dataset in a data-cleaning log, then designed an interactive Tableau story covering adoption trends, regional comparison, and inclusion drivers.
Presented the findings as a management narrative and published the story on Tableau Public.
Mapped 437 coded World Bank Findex fields across 174 economies and 12 population groups into 24 business-readable measures, then excluded the 2011 and 2022 waves for coverage, leaving 171 economies and four survey waves (2014–2024).
Findings: mobile money adoption leads in Sub-Saharan Africa; digital payment use runs ahead of debit-card ownership; savings lag far behind payment usage; and mobile money drives women's financial participation more than traditional banking does.
Submitted December 2025. Its finding that digital payment use runs ahead of debit-card ownership raised the question my final-year project then tested: what happens to banks' fee income as payments move away from cards.
Tableau
Tableau Story and filters
Tableau calculated fields
Tableau Public
Excel
Python data preparation
World Bank Global Findex
Technical skills
Where each skill shows up in this CV
Pick a skill to mark the lines in this CV that show it; press it again to move to the next line.
Research data restrictions mean the thesis bank panel cannot be published; the public repository therefore provides the documented workflow and a runnable synthetic example instead.
This CV is generated from the same source as the rest of this site, so it stays consistent with the published research pages.