Jahanzaib
All Work
AutomationFinTechFinTech / Venture Capital

Automated Fund Reporting for FinTech

Weekly reports that took 2 days now generate in 8 minutes. Zero manual errors. LPs noticed the improvement.

Early Stage Venture Fund·$45M AUM, 3 person operations team·Shipped in 3 weeks

Client details anonymized under NDA. The work, approach, and results shown here are real. Contact me for references.

Financial analytics dashboard with trading data and market charts
0

Report Generation

0

Manual Errors

0

Human Review Time

0

On Time Delivery

The Challenge

What they were dealing with

An early stage venture fund managing $45M across 28 portfolio companies was producing weekly performance reports manually. One analyst spent nearly two full days every week pulling data from six different sources, formatting spreadsheets, building charts, assembling investor decks, and sending emails. The process was error prone, often delayed, and consumed 40% of the operations team's bandwidth.

Data lived in six separate systems including the portfolio tracker, bank accounts, cap table software, CRM, market data feeds, and email

Every report required manual copy and paste from multiple dashboards into a master spreadsheet

Formatting errors in investor decks had caused two embarrassing corrections in the past quarter

The analyst who owned the process was a single point of failure and could not take time off without reports being delayed

Before

2 days

Report Generation

4+

Manual Errors/Quarter

16 hours

Analyst Time/Week

30%

Report Delay Rate

The Approach

How I solved it

The fundamental problem was not the reports themselves. It was that a human was acting as the middleware between six data systems that did not talk to each other. The analyst was literally copying numbers from one dashboard, pasting them into a spreadsheet, formatting charts, copying those charts into a slide deck, then emailing the deck to investors. Two days of copy paste work that added zero analytical value.

I built an automated reporting pipeline that connects directly to every data source via API, pulls the numbers on schedule, reconciles them across systems (the portfolio tracker and the bank accounts never agreed, so I built a reconciliation layer), validates everything against historical ranges to catch anomalies, and generates three publication ready outputs: a detailed weekly performance spreadsheet with charts, an investor facing PDF summary with the fund's exact branding and formatting standards, and a Slack digest with key metrics and flags.

The anomaly detection is what the partners love most. If any data point falls outside expected ranges (for example, a portfolio company's revenue drops 20% week over week, or a bank balance does not match expected wire transfers), the system flags it and pings the partner on Slack before the report goes out. They caught two accounting errors in the first month that would have gone to investors unnoticed under the old process. The analyst who used to spend two days on this now spends 15 minutes reviewing the output and clicking approve.

1

Data Source Mapping

Audited all six data sources, documented their APIs and export formats, and built a unified data schema for cross system reconciliation.

2

Ingestion Pipeline

Automated data pulls from portfolio tracker, banking APIs, cap table software, CRM, and market data. Scheduled and on demand.

3

Report Generation

Templated outputs for weekly spreadsheets, investor PDFs, and Slack digests. Anomaly detection flags any data outside expected ranges.

4

Review and Distribution

One click approval workflow. Auto distribution to investors via email with read receipts. Slack alerts for the internal team.

Python AutomationBanking APIsPortfolio Tracker APIPDF GenerationSlack BotAnomaly Detection

The Results

What changed

8min

Report Generation

0

Manual Errors

15min

Human Review Time

100%

On Time Delivery

Shipped in 3 weeks
16 hours per week freed for the operations team. Zero reporting errors since launch.
Our analyst was spending two days a week just pulling numbers and formatting decks. Now the reports generate themselves and she reviews them in 15 minutes. Zero errors since we switched. Our LPs actually noticed the improvement.

Daniel Reeves

Managing Partner, Venture Fund

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