Automatic cross-referencing of taxpayer declarations with third-party data

Purpose

1.1. Enable the automated cross-verification of taxpayer declarations with third-party data to quickly flag inconsistencies, reduce manual review effort, and increase compliance.
1.2. Fetch data from financial institutions, employers, payment processors, and relevant registries to detect undeclared income, inaccuracies, or suspicious financial activity.
1.3. Automate periodic reconciliation using up-to-date datasets for real-time compliance monitoring and streamlined enforcement processes.

Trigger Conditions

2.1. New taxpayer declaration submitted.
2.2. Scheduled compliance audit period reached.
2.3. Receipt of updated third-party data files.
2.4. Detection of anomalies or flagged risk criteria on incoming data.

Platform Variants

3.1. Microsoft Power Automate
• Feature/Setting: Scheduled flow using "Recurrence" and "Get Items" actions to fetch data from Dataverse and compare against incoming declarations.
3.2. Zapier
• Feature/Setting: Multi-step Zap using Webhooks and Formatter to pull government declarations and cross-reference with bank feeds.
3.3. UiPath
• Feature/Setting: Robotic Process Automation running daily batch jobs to ingest declaration CSVs and financial APIs for data-matching.
3.4. MuleSoft
• Feature/Setting: API orchestration with DataWeave Mapper for merging and comparing declaration and third-party data sources.
3.5. IBM App Connect
• Feature/Setting: Event-driven "Flow" to link ERP, banking APIs and parse declarations.
3.6. Workato
• Feature/Setting: Recipes combining secure file ingest and HTTP connectors for entity resolution.
3.7. Boomi
• Feature/Setting: Integration Process using Map and Decision shapes to reconcile declaration data with external account records.
3.8. Integromat (Make)
• Feature/Setting: Scenario with "Watch Files" (Dropbox/FTP) and HTTP Module for pulling third-party evidence and running data checks.
3.9. Salesforce
• Feature/Setting: Scheduled Apex/Flow to sync and verify custom objects representing declarations against financial data imported via API.
3.10. Google Cloud Functions
• Feature/Setting: Event-based triggers invoking Python scripts that compare incoming declarations to cloud-stored bank transactions.
3.11. AWS Lambda
• Feature/Setting: Lambda function triggered on S3 upload for declarations, cross-referencing DynamoDB tables of third-party/registry data.
3.12. Azure Logic Apps
• Feature/Setting: Recurring workflow executing Logic App connectors for FTP CSVs and RESTful tax/banking APIs; conditional alerting on mismatch.
3.13. Oracle Integration Cloud
• Feature/Setting: Integration Flow with pre-built connectors for ERP and financial institution data, JavaScript step for comparison logic.
3.14. Smartsheet
• Feature/Setting: Automated workflows capturing declaration changes and verifying against imported bank/export payroll feeds.
3.15. Trello
• Feature/Setting: Butler Automation: Scheduled card creation for flagged discrepancies, auto-linking to declaration records and third-party evidence.
3.16. Monday.com
• Feature/Setting: Automation to ingest data via API, trigger item updates where discrepancies arise, alert compliance teams.
3.17. Pabbly Connect
• Feature/Setting: Multi-step workflows integrating tax form submission webhook with Google Sheets and CRM, checking for anomalies.
3.18. Talend Data Integration
• Feature/Setting: Batch Job: ETL pipeline cross-matching declaration files against SFTP-sourced income data.
3.19. SAP Integration Suite
• Feature/Setting: Process integration scenario invoking function modules for data matching and error reporting as logs.
3.20. Elastic Stack (ELK)
• Feature/Setting: Logstash pipeline ingests declarations and third-party datasets, visualizes mismatches in Kibana.
3.21. Jitterbit
• Feature/Setting: Operation: Scheduled job extracting tax records, reconciling with third-party reports, error events to email/SFTP.

Benefits

4.1. Significant reduction of manual comparison work for tax compliance teams.
4.2. Faster detection and escalation of discrepancies for enforcement.
4.3. Increased accuracy and completeness of compliance review processes.
4.4. Consistent, auditable, and scalable application of reconciliation rules.
4.5. Enhanced deterrence and prevention of tax evasion via automated monitoring.