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Fund Reporting Automation
End-to-end reporting pipeline that replaced repetitive spreadsheet workflows and improved accuracy.
PythonVBAExcelTask Scheduler
Impact Highlights
20+ hrs/mo
Time saved
99.7%
Accuracy rate
3 days → 4 hrs
Turnaround
8 funds
Scale
Before vs After
Before
- • Manual data entry from 4 different custodian portals
- • Copy-paste into Excel templates with frequent formula breaks
- • 3-day turnaround for monthly reporting pack
- • Error rate of ~2% requiring constant reconciliation
After
- • Automated data extraction via Python scripts
- • Template generation with built-in validation checks
- • Same-day delivery with automated email distribution
- • 99.7% accuracy with exception-based review only
Key Decisions
1
Chose Python over RPA tools — lower cost, more flexible, team could maintain
2
Built incremental: automated extraction first, then formatting, then distribution
3
Designed for handoff: documented every script with inline comments and README
Interactive Demo
Mini Financial Model
Adjust assumptions to see operating income impact
15%
50%
35%
Operating Income by Year
2025$1.7K
2026$2.0K
2027$2.3K
Gray = revenue · Blue = operating income
What I'd do next (given more time)
- →Add anomaly detection to flag unusual NAV movements automatically
- →Build a Slack/Teams integration for real-time completion notifications
- →Create a web dashboard for fund managers to self-serve reports