Narishah Mohamed Salleh

About

Driven by a passion for bridging the gap between unstructured financial data and enterprise efficiency, Narishah Mohamed Salleh is a researcher at the forefront of applying Natural Language Processing (NLP) to accounting and supply chain management. Her work centers on developing intelligent, automated strategies for processing complex business transactions, with a particular focus on improving the classification of supplier invoices within Enterprise Resource Planning (ERP) systems. Her most-cited paper, "A Novel Natural Language Processing Strategy to Improve Digital Accounting Classification Approach for Supplier Invoices ERP Transaction Process" (2023), introduces a groundbreaking method that uses semantic analysis to automatically categorize invoice line items, reducing manual data entry errors and accelerating procurement cycles. This contribution has already garnered 4 citations, signaling its growing relevance in the fields of digital accounting and business process automation. By demonstrating how NLP can transform traditional accounting workflows, Salleh is paving the way for more accurate, scalable, and cost-effective financial operations—a critical advancement for organizations navigating the complexities of digital transformation.

Research Focus

Key Achievements

Top Papers

1. 1
   A Novel Natural Language Processing Strategy to Improve Digital Accounting Classification Approach for Supplier Invoices ERP Transaction Process

   4 citations · 2023

Key Collaborators

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