Page 38 - CMA Journal (Jul-Aug 2026)

F oc us S ec t ion

Role of Management Accountants and
Practical Case Study
Internal Auditors
Consider an organization that purchases electrical and construction materials from hundreds of suppliers.
Management notices that procurement costs are increasing despite relatively stable demand. To understand Advanced technologies, AI tools and data analytics
the reason, the organization uses data analytics to review suppliers and procurement transactions. alone cannot eliminate the risk of fraud or misconduct.
Management accountants and internal auditors still
The analysis identi es several warning patterns requiring further reviews: remain responsible for ensuring that technology
• About suppliers’ bank account details enabled control are well designed, implemented,
Introduction Arti cial • Repeated purchases or purchases orders just below the approval thresholds monitored and regularly evaluated for results.

Procurement fraud does not arise from a single weak Intelligence and • Excessive purchasing compared with actual requirements ML and AI depends on quality and accuracy of input
control. It arises as a consequence of a whole system Machine • Repeated invoices from the same suppliers data, proper supervisions continuous monitoring and
involved, proper planning and manipulation of the Learning • Suppliers and management relationship professional evaluations and de ned threshold. • Identify procurement red ags: Establish clear
system, involvement of unauthorized management, • About Suppliers history Inaccurate and incomplete input data may lead to indicators for unusual employees’ suppliers’
ignoring the internal controls checks. Arti cial Intelligence (AI) inaccurate results.
and Machine Learning These warning patterns do not prove that fraud has occurred but they provide as a starting point to identify relations, suddenly changes in prices, invoices and
In this article I would like to explore all these possible (ML) can make the risky areas for further investigation and analysis. So, Management and internal audit can examine for a Management accountant can also connect payment patterns
weaknesses and explain how gaps in procurement procurement process detailed review of suppliers’ records, purchases orders, quotations, approvals, goods receipts, invoices and procurement fraud analytics with nancial planning, • Introduced Auto Preventive Controls: Use
procedure can create opportunities for fraud and more e cient, cost payment details. cost e ective and evaluating the performance. A system-based approaches, Entry Checks, Alerts to
manipulation. And then how AI, ML and data analytics e ective and provide In this way, data analytics can move the review from broad examination of hundreds of suppliers to a focused procurement anomaly that initially appears prevent and highlight unusual transactions
tools work as anti-fraud technologies to overcome accurate results. With bases risk-based investigation of suppliers and transactions showing unusual patterns. operational may ultimately a ect pro t margins,
these weakness and frauds. help of AI large and project cost and cash ow. Professional input, • Maintain Human Reviews: Maintain regularly basis
complex data can monitoring and evaluation the results are essential management accountant and internal audit
The Association of Certi ed Fraud Examiners (ACFE), in provide excellent results. AI and ML identify and • Analyzing goods descriptions, quantities, qualities, Blockchain is therefore mainly valuable for improving when advanced technologies are used. reviews, monitoring and take signi cate corrective
its report to the nations, estimated that a loss of 5% of prevent ctitious suppliers, duplicate or fake invoices, prices and other details transparency, accountability and the reliability of actions.
revenue due to fraud each year based on cases studied. control quality of goods and alert about large and procurement records. It’s e ectiveness still depends Challenges and Limitations
The report analyzed 1921 occupational fraud cases unusual transactions. • Identifying sudden changes in supplier ledgers and upon accurate information being entered into the Technology introduces new capabilities like time Conclusion
from 138 countries, and corruption was identi ed in bank account details system, together with appropriate governance and saving, accurate results and cost e ectiveness. But, on Throughout the overall article, I describe that in
48% of the cases. Machine learning can analyze historical and current • Detecting payments made before getting approvals access controls. OECD research identi es blockchain as the other hand, creates new risks and challenges. modern era, Technologies like AI, ML, Data analytics
data relating to suppliers, purchase order, goods Procurement needed review, system updating and the
The World Bank also identi es warning of fraud and receipts records, prices, quantities, description of or goods receipts an emerging technology that can support tools and other forms are important in procurement
corruption in procurement. These ndings show that goods and bank account details of suppliers. AI based • Monitoring frequent or unusual changes in accountability, vendor compliance and transparency. introduction of technologies in order to eliminate the function eliminating the risk of fraud and misconduct
fraud prevention should be treated as responsibility of monitoring of large volumes of transactions can purchase orders (POs) E-Procurement and Automated risk of fraud. in an organization, but at the same time human review,
management and governance rather than only audit highlight risky areas. AI and ML should support Controls AI and ML tools should not be trusted blindly. Regular monitoring and results evaluation still more important.
concern. professional judgements rather than replace These tools can check and identify red ags at an early human review and professional supervision remain AI, ML, Data analytics, blockchain and e-procurement
stage and focus resources on higher-risk transactions.
Common Procurement Fraud Risks management accountants or internal auditors. Here, Recent OECD work identi es data and predictive A properly well-designed and automated procurement important. The e ectiveness of technology depends can strengthen procurement controls, but technology
on data quality proper system con guration and
an important point is that input data in AI and ML must system can improve e ciency, transparency and is not a substitute for sound procedures and
In this section, I would like to explore the common be correct and accurate in order to produce accurate analytics for detecting fraudulent activities and control. E-procurement means managing continuous system monitoring. professional judgment.
procurement fraud risk that may arise in this function. results. improving risk assessments. procurement through a structured and digital system. New technology adoptions can itself be challenging References
These include creating ctitious suppliers, fake or OECD research also notes that AI and machine learning Blockchain and Procurement In this system required procurement activities are because of cost, employee’s acceptance, training, • Association of Certi ed Fraud Examiners (ACFE), Occupational Fraud
duplicate invoices, placing most orders with the same can support the identi cation, prediction and Transparency carried out through proper documentation, approvals system integration and changing existing work 2024: A Report to the Nations. ACFE, 2024.
suppliers, ordering goods in large quantities, goods mitigation of fraud and corruption risks, including pre and post control activities and adoption of system patterns. For successful adoption therefore required • World Bank, Warning Signs of Fraud and Corruption in Procurement,
protocols.
not meeting the required standards, description of irregularities in public spending and procurement. Blockchain is a distributed ledger technology designed planning, management support and continuous Integrity Vice Presidency / Integrity Compliance Knowledge Sharing
Platform.
goods not being properly mentioned. to record transactions in a secure and tamper-resistant For example, an invoice should proceed for processing evaluation.
Data Analytics: The Foundation of only when the required purchase order, approvals, • OECD, Anti-Corruption and Integrity Outlook 2024, section on Arti cial
Failure to properly disclose the relationships of Continuous Monitoring manner. In procurement, it can support preventive goods receipt and other relevant information have Recommendations Intelligence and its use in preventing and detecting fraud and
corruption.
controls by maintaining transparent records of
employees or management with suppliers may also been completed and recorded. Such controls can Organization’s procurement function required to • OECD, Analytics for Integrity: Data-Driven Approaches for Enhancing
create a possibility of fraud. The risk of fraud does not Among all anti-fraud technologies, data analytics plays transactions, approvals and other procurement reduce manual intervention, prevent incomplete assess either through advanced technology or just by Corruption and Fraud Risk Assessments, OECD Publishing, 2019.
arise only at the stage of payment but can happen an important role in monitoring the organization’s activities. transactions from moving forward and strengthen the strengthen internal policies and control systems. • OECD, Digital Transformation of Public Procurement, Public Governance
throughout the overall procurement procedure. internal control system and procurement function. When combined with appropriate systematic rules and procurement process. Technologies should be adopted according to actual Policy Papers, 2025.
Most e ective strategies by data analytics are as
Failure to follow up the procedure of procurement follows: smart contracts, blockchain-based systems can restrict The OECD's 2025 work on digital transformation of requirements, risk level and available resources rather
such as obtaining quotations, conducting rate and or prevent a process from moving forward when public procurement identi es applications across than simply because it is available.
quality comparison analysis, approval of quotation, • Identifying suppliers receiving unusual high de ned conditions, approval requirements or pre-tendering, tendering and post-tendering, Four factors are important in this regard:
generating purchase orders (PO), preparing goods volumes or values of transactions thresholds have not been met. This can reduce the risk including supplier’s performance monitoring, fraud • Clean and accurate Suppliers Data: Ensuring
receipt notes (GRNs) and nal payments, should also • Reviewing the history and pattern of business of unauthorized transactions, record manipulation and detection, risk assessment, automated invoice suppliers data, banking details and transaction data
be checked. relationships with suppliers bypassing established controls. processing and blockchain-supported transparency. accurate and complete

36 ICMA’s Chartered Management Accountant, Jul-Aug 2026