analyze-financials

Name: analyze-financials
Availability: InStock
Author: jdrodriguez

Trace money flows and detect anomalies across bank statements and transaction records.

6|Updated Feb 10, 2026

Search Tags:#visualization #data-analysis #anomaly-detection #financial-forensics #money-flow #bank-statements

Ready to run

npx skills add https://github.com/jdrodriguez/legal-toolkit --skill analyze-financials

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: analyze-financials
Source: https://github.com/jdrodriguez/legal-toolkit/tree/main/legal-toolkit/skills/analyze-financials
Command: npx skills add https://github.com/jdrodriguez/legal-toolkit --skill analyze-financials

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, networkx, plotly, openpyxl, docx, and includes scripts (resource) components.

What problem does it solve?

Forensic financial analysis is needed to trace money flows, detect anomalies, and map entity relationships across statements, spreadsheets, and financial records.

Core Features & Use Cases

Ingest bank statements (CSV, Excel, OFX/QFX) and transaction data to build a complete money-flow map.
Detect anomalies such as structuring, unusual timing, rapid in-out sequences, and new large payees.
Generate interactive visualizations (money-flow Sankey, transaction timeline) and summary reports for audits.

Quick Start

Analyze a provided set of bank statements to identify where money moved, what patterns appear, and where anomalies lie.

Frequently Asked Questions about analyze-financials

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I detect structuring and rapid in-out anomalies in bank statements?▼

You can trace money flows across bank statements by ingesting CSV, Excel, or OFX/QFX transaction data to build a money-flow graph that maps where money moved and flags structural anomalies for audits.

What is financial forensics anomaly detection for transaction records?▼

Financial forensics anomaly detection maps entity relationships across transaction records to identify unusual timing patterns and structuring by building a money-flow graph from ingested bank statements.

Does this financial forensics analysis work with OFX and QFX bank statement formats?▼

Yes, financial forensics analysis works with OFX and QFX bank statement formats, alongside CSV and Excel files, normalizing the transaction data to build a complete money-flow map for audits.

Can I generate interactive visualizations and reports from transaction data analysis?▼

Yes, you can generate interactive visualizations from transaction data analysis, producing money-flow Sankey diagrams, transaction timelines, and summary audit reports.

What's the best way to trace money flows across multiple transaction records?▼

The best way to trace money flows across transaction records is to normalize CSV, Excel, and OFX/QFX data into a money-flow graph that maps entity relationships and flags financial anomalies.

Do I need pandas and networkx to analyze financial anomalies in spreadsheets?▼

You need pandas and networkx to analyze financial anomalies in spreadsheets, along with plotly for visualizations and openpyxl for reading Excel bank statements.