Manuscript Number : SHISRRJ236155

A Predictive Modeling Approach for Managing Accounts Payable Workflow Efficiency and Ledger Reconciliation Accuracy

Authors(3) :-Olawale Olasoji, Ebehiremen Faith Iziduh, Oluwatobi Opeyemi Adeyelu

This paper presents a predictive modeling framework designed to enhance the efficiency of accounts payable workflows and improve the accuracy of ledger reconciliation processes. Recognizing the critical role of accounts payable in financial operations and the challenges posed by workflow inefficiencies and ledger discrepancies, the study explores how data-driven predictive analytics can transform traditional manual and rule-based systems. The framework integrates diverse transactional data and applies advanced machine learning techniques to forecast processing delays and detect potential reconciliation errors proactively. Emphasizing robust data quality and feature engineering, the approach ensures reliable predictive outcomes that support timely intervention and operational optimization. Furthermore, the paper addresses strategic considerations for embedding predictive models within existing ERP environments, managing risks such as model bias and compliance, and sustaining continuous improvement through iterative feedback loops. This research contributes a comprehensive conceptual foundation for leveraging predictive analytics to foster smarter, more resilient financial processes, offering significant practical value to finance professionals and organizations seeking to modernize their financial operations.

Authors and Affiliations

Olawale Olasoji
TotalEnergies E&P Nigeria, Ltd, Nigeria
Ebehiremen Faith Iziduh
Shell Nigeria (SCiN), Lagos, Nigeria
Oluwatobi Opeyemi Adeyelu
Independent Researcher, Lagos, Nigeria

Accounts Payable, Predictive Modeling, Ledger Reconciliation, Workflow Efficiency, Machine Learning, Financial Process Automation

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Publication Details

Published in : Volume 6 | Issue 4 | July-August 2023
Date of Publication : 2023-08-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 106-120
Manuscript Number : SHISRRJ236155
Publisher : Shauryam Research Institute

ISSN : 2581-6306

Cite This Article :

Olawale Olasoji, Ebehiremen Faith Iziduh, Oluwatobi Opeyemi Adeyelu, "A Predictive Modeling Approach for Managing Accounts Payable Workflow Efficiency and Ledger Reconciliation Accuracy", Shodhshauryam, International Scientific Refereed Research Journal (SHISRRJ), ISSN : 2581-6306, Volume 6, Issue 4, pp.106-120, July-August.2023
URL : https://shisrrj.com/SHISRRJ236155

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