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Cover image for I implemented an automated transaction
I implemented an automated transaction reconciliation system using Python, designed to match platform transactions with bank records, developed as part of a larger Admin Portal for financial operations. What this system supports: • Automated matching of bank & platform transactions • Keyword-based and rule-driven reconciliation logic • Batch processing for large transaction datasets • Configurable matching rules per account or merchant • Clear linking between matched records for auditing • Scheduled reconciliation via cron jobs running on Render • Designed to integrate with existing APIs and databases This project focused heavily on: ✨ Reducing manual reconciliation time within the Admin Portal ⚡ Performance-focused processing for large datasets 🧠 Clear, maintainable Python logic developed iteratively using Cursor
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Cover image for THE PROBLEM The organization carried 600
THE PROBLEM The organization carried 600 admin accounts with unreviewed entitlements. JML processes ran manually. New hire provisioning averaged 72 hours from request to access. Offboarding gaps left orphaned accounts active in production systems. WHAT WE DID ▪  Conducted full identity inventory across all AD domains and connected SaaS platforms. ▪  Designed a SAML 2.0 JIT provisioning pipeline tied to HR system joiner events. ▪  Validated the pipeline in a 600-user simulated Active Directory forest on Windows Server 2025. ▪  Built automated deprovisioning triggers for leaver events, removing manual offboarding steps. ▪  Delivered a Zero Touch onboarding architecture with IT team runbook for ongoing operations. THE RESULTS ▪  JML provisioning time: reduced from 72 hours to Zero Touch automated delivery. ▪  IT support ticket volume: 55% reduction within 60 days of architecture deployment. ▪  Admin account review: 600 accounts audited and remediated. ▪  Orphaned account risk: eliminated via automated leaver event triggers. 55% Reduction in IT support tickets within 60 days
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