Automating Financial Data Integration for Tyler Incode

A mid-sized municipality was facing challenges with manually importing financial transactions from an external application into Tyler Incode, their ERP system. The finance team was spending hours each week formatting and correcting data before import, leading to delays and errors in financial reporting.

Challenges Faced

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• The municipality received financial export data from an external system in a format that was not directly compatible with Tyler Incode.
• Manual data entry was time-consuming and prone to human errors.
• The finance team lacked an automated solution to validate, transform, and properly format transactions for seamless import.
• Missing or incorrect fields in the import process led to data discrepancies in reports, requiring additional reconciliation.

Our Approach & Process

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To streamline the integration, we developed a custom Python automation script that:

1. Extracted financial data from the external system’s export files.
2. Validated the data to ensure required fields were present and properly formatted.
3. Transformed the data into a format compatible with Tyler Incode's import specifications.
4. Automated the import process, eliminating manual data entry.
5. Generated reports and error logs, providing the finance team with a clear view of any potential discrepancies before final submission.

Technologies used:

• Python & Pandas for data manipulation and transformation.
• Regex-based validation to ensure field accuracy.
• Automated file parsing and reformatting to match Tyler Incode’s import structure.