Instrument-Level Transfer Pricing Analytics Using Automated Data Pipelines and Financial Calculation Frameworks

  • Authors

    • Bhargavaram Potharaju Systems Operations Engineer, Wells Fargo Charlotte, NC, USA. Author
    • Radha Rani Sajja Asst Professor, Vigan University Guntur, Andhra Pradesh, India. Author

    DOI:

    https://doi.org/10.67228/3071642X/IJCFDE-2021PII7J3Q

    Published 12-07-2021

  • Transfer Pricing Analytics, Instrument-Level Calculations, Treasury Analytics, Balance-Sheet Analytics, Net Interest Margin, Financial Data Modelling, ETL Automation, Batch Processing, Reconciliation, Audit-Ready Analytics

    Issue

    Vol. 4 No. 2 (2021)

    Section

    Articles

    How to Cite

    Potharaju, B., & Sajja, R. R. (2021). Instrument-Level Transfer Pricing Analytics Using Automated Data Pipelines and Financial Calculation Frameworks. International Journal of Commerce, Finance and Digital Economy, 4(2), 01-34. https://doi.org/10.67228/3071642X/IJCFDE-2021PII7J3Q

  • Abstract

    Transfer pricing is an important means by which multinational corporations allocate income, expenses and risks among their global operations. However, traditional manual data collection and spreadsheet calculations are error-prone, take a long time to report and invite more regulatory scrutiny. In this paper we propose an integrated analytical framework to address these vulnerabilities. The framework is focused on instrument-level transfer pricing, enabled by automated enterprise data integration pipelines and standardized calculation models. Legacy systems are based on high-level aggregate data, whereas this architecture automatically ingests and validates transactional data from heterogeneous systems to assess individual financial instruments against parameters such as interest rate structures, liquidity profiles, credit risks and market benchmarks. The modular solution comprises automated computational workflows, interactive visualization dashboards, compliance reporting and scenario-based financial simulations to assess pricing sensitivity in changing market environments. Performance insights indicate that automation of instrument level analytics dramatically decreases the processing lead time and improves pricing consistency, audit trail and regulatory compliance, providing a scalable foundation for financial control at the enterprise level.

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