Deloitte (Accounting & Audit Division)
Date: 00.00.00
Problem:
Manual extraction of transactional data from 10+ banking portals into Excel, leading to 8+ hours/day wasted on data entry.
Frequent errors in reconciliation due to inconsistent formatting across sources.
Delayed financial reporting for clients.
Goal:
Automate daily accounting report generation by:
Scraping transactional data from banking portals.
Cleaning, standardizing, and consolidating data into a unified Excel report.
Reducing manual effort by 90% while ensuring audit-ready accuracy.
Technologies Used:
Python: Web scraping (Selenium, BeautifulSoup), data cleaning (pandas).
Excel/VBA: Automated report formatting, reconciliation macros.
Power BI: Dashboards for anomaly detection.
Reduced report generation time from 8 hours to 45 minutes daily, with 99.8% data accuracy.
Results (Detailed):
Automated Data Scraping: Built Python scripts to log into banking portals, extract CSV/PDF data, and convert it into structured Excel tables.
Data Standardization: Created VBA macros to auto-format currencies, dates, and account IDs across sources.
Error Flagging: Integrated Power BI dashboards to highlight mismatches in reconciled totals.
Client Deliverables: Auto-generated Excel reports with pivot tables and audit trails emailed daily.
A zero-touch reporting system enabling Deloitte to:
Deliver client reports 2 days faster.
Reassign 5 FTEs to high-value tasks.
Lorem ipsum dolor sit amet, 
conse ctetur adipiscing elit. Sed varius ornare turpis, ut luctus lectus efficitur vel. Quisque a ipsum laoreet, porttitor ipsum quis, imperdiet nisi. Sed varius ornare turpis, ut luctus lectus efficitur vel. Lorem ipsum dolor sit amet, conse ctetur adipiscing elit. Sed varius ornare turpis.
John Doe
Co-Founder at Google