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Forensic Payroll Analytics for IPPIS: A Hybrid Anomaly-Detection

Framework to Expose Payroll Fraud, Improve Data Governance,

and Protect Employee Rights

Adeleye Dupe Ayesha, Prof. Abd. Rahman Ahlan, Dr. Najhan Muhamad Ibrahim, Bello Bariz Holaitan,

Alijafar Umar

International Islamic University, Malaysia

DOI: https://dx.doi.org/10.51584/IJRIAS.2025.100900050

Received: 07 Sep 2025; Accepted: 12 Sep 2025; Published: 15 October 2025

ABSTRACT

The Integrated Payroll and Personnel Information System (IPPIS) is one of the largest government digitization

reforms in Nigeria. The purpose is to ensure payroll accuracy, fight corruption, and weed out ghost workers.

While many papers have dealt with the evident successes and challenges, very few have actually ventured to

propose forensic analytic frameworks that are deployable in anomaly detection within IPPIS payroll data. This

paper presents a forensic hybrid model that generates synthetic data to be fed to unsupervised anomaly

detection algorithms and subsequently uses a set of rule-based forensic checks to flag irregularities in payroll

patterns. Having been developed to operate under possible data-access restrictions, this framework uses

metadata and pseudonymized identifiers in order to circumvent most privacy and governance concerns. The

study essentially contributes in three ways: (i) to describing a methodological approach to building synthetic

training datasets for payroll anomaly research; (ii) combining several detection techniques into a composite

risk-scoring model; and (iii) exhibiting governance controls for ethically applying the research. The results

also seem to prove that such a framework renders the presence of stronger payroll integrity, lessening the

burden on investigations and increasing transparency.

Keywords: IPPIS, payroll fraud, anomaly detection, forensic analytics, Nigeria

INTRODUCTION

Payroll fraud, indeed, remains one of the most persistent challenges confronting Nigeria's public

administration; it continues to erode financial accountability and citizen trust in government institutions. Over

the decades, the civil service has been beset by cases of ghost workers bearing names on payrolls for whom no

services are rendered, thus bloating expenditure and mean hindering in critical development projects.

Alongside ghost workers, other fraudulent means have also caused great fiscal leakages throughout history,

such as unauthorized adjustments of pay grade, duplicate and overlapping accounts, and gross manipulations

of the payroll records (Adjei-Bamfo et al., 2019). These malpractices not only skew budgetary allocations but

also serve to cripple the credibility of any reforms imposed on the sector. With the aim of developing long-

term solutions to recurrent problems, there was a collaboration between the Federal Government of Nigeria

and the Office of the Accountant General for the development of the Integrated Payroll and Personnel

Information System (IPPIS) (Effiong et al., 2017).

This system was established as a centralized digital platform that unifies the interface of personnel and payroll

data, minimizing manual interventions and serving as a single, verifiable source of information for salary

administration. It intends to enhance transparency, bring accountability, and ensure the efficiency of salary

payments to federal workers. An automated payroll system with “academics IPPIS” sought to circumvent

loopholes that had long been exploited by payroll fraud and corruption (Effiong et al., 2017). Since its

inception, the IPPIS has generated recognition for its successes and criticism regarding its limitations.

Empirical evidence and government audit reports suggest the system has reduced payroll irregularities,

particularly visible instances of ghost worker fraud. Reports have also claimed that since the introduction of

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IPPIS, billions of naira have been saved, suggesting that it acts as a guard of fiscal resources in an economy

facing revenue crises. Yet despite these gains, certain glaring weaknesses continue to undermine its overall

effectiveness. One major issue remains insufficient data integration: hence, not all Ministries, Departments,

and Agencies(MDAs) have undergone complete migration into IPPIS, and inequalities in personnel records

between various sectors remain (Chima, 2020a). As such, institutional resistance has hampered adoption in

some places, with academic institutions and professional associations contesting the platform's appropriateness

for their unique administrative contexts. Because of concerns about the truthfulness of data, system security,

and less-than-useful integration with other government platforms, weaknesses are highlighted that scammers

can exploit for their own benefit. Hence, even though the IPPIS has obviously improved payroll governance in

Nigeria, irregularities can never be totally wiped clean from the system, and the prevalence of subtle or

disguised forms of fraud indicates that there is still a need for instrument change to upgrade its monitoring

(Mensah et al., 2020). This duality is reflected in the IPPIS-related scholarly work, which mostly undertakes

descriptive assessments of the successes and failures. Nevertheless, very few works propose methodical,

technical solutions that could audit payroll data in real-time and detect abnormality before it can result in

sizeable financial loss. Unlike earlier approaches that mostly rely on qualitative assessments or retrospective

audits, this framework connects computational methods for anomaly detection with rule-based checks derived

from customer domain knowledge and is intended to be applied for the actual ongoing irregularity detection in

the environment under study (Ike et al., 2023). However, three distinct features distinguish this framework

from any other framework studied so far: By employing a metadata-first approach, payroll can be analyzed

without exposing sensitive or personally identifiable employee data, thereby protecting employee privacy

while maintaining fraud detection capabilities. Synthetic data generation is incorporated as well as a

methodological tool whereby researchers and auditors can train and validate models in situations where

confidentiality would preclude actual access to payroll records (Kaoje et al., 2020). Mechanisms are put in

place to ensure that technical experiments and development of the system would be proceeded with without

threat to data security. The framework also provides governance controls that bind technology interventions

with labour standards, so that any detected anomalies are publicly assessed and do not unfairly penalize

legitimate staff (Iloanya , Kenneth Okechukwu et al., 2020). By incorporating these features, the research thus

contributes to academic discourse on payroll reform, while also providing policymakers and oversight agencies

with a practical roadmap for improving IPPIS. (Oni et al., 2016).

LITERATURE REVIEW

The research on the Integrated Payroll and Personnel Information System (IPPIS) in Nigeria could be

characterized into three broad thematic categories: implementation studies, evaluation and audit studies, and

theoretical or critical perspective studies. Put broadly, these areas of study jointly constructed a fairly strong

picture of the entire conception, rollout, and contention around the system within the Nigerian public service.

In light of this view, the studies represent solid bases, yet relevant gaps are left open, especially in relation to

the development of analytic frameworks for detecting anomalies in payroll data in real time. The following

review discusses the major findings within each of these themes, weighing their accomplishments and

limitations before positing the contribution of this study

The earlier and perhaps more voluminous series of works in IPPIS has been presented under implementation

studies. These articles concern themselves with how the system was deployed in Nigeria's ministries,

departments, and agencies (MDAs). Scholars in the implementation studies realm primarily highlight the

technical and organizational challenges encountered when manual or semi-manual payroll systems are

replaced by a centralized electro-mechanical platform. For instance, some descriptions reveal that the Federal

Government launched IPPIS in 2007 under wider public sector reforms aimed at enhancing transparency and

accountability in financial management (Aheebwa, n.d.). However, the introduction of the system could not

have gone smoothly. Resistance appeared within various MDAs, mostly in sectors where informal or localized

payroll systems had been fairly well established. Universities are a good example; academic unions in these

institutions were frequent contesters of IPPIS adoption on grounds of autonomy and flexibility, and because of

the peculiarities of academic payroll systems such as arrangements for sabbatical leave, adjunct appointments,

and earned academic allowances.

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Some of these studies also narrated how in the early days of implementation, the promise and barriers of

centralized payroll management became evident. On the plus side, the system was able to speak against double

payroll entries, salary leakages, and provided uniformity in employee record-keeping. For instance, it was

mentioned in certain reports that before IPPIS, several MDAs maintained fragmented payroll systems that

were susceptible to abuse and had let ghost workers flourish (Adegbile et al., n.d.). The centralized database

now created a single source of truth regarding numbers of employees and salary obligations, thereby giving

governments better fiscal visibility. Conversely, researchers find out that many an institution refused to give in

for procedural convenience. Several quantum wise delayed enrollment, others resisted enrollment, while a few

clandestinely contrived parallel schemes for payroll outside the system itself. In some cases, weak change

management and inadequate sensitization of staff only fueled suspicion of the system's intentions (Sahban

Ibrahim et al., 2016).

Implementation studies, aside from resistance, also throw light on infrastructural and technical constraints.

Owing to varying degrees in Nigeria's digital readiness, some MDAs were simply not equally able to interface

with the central platform. Poor Internet connection, lack of training of officers on new payroll arrangements,

and lack of technical support all crippled adoption (Udejinta, 2022). Further, the studies bemoaned the failure

of centralized systems to accommodate peculiarities of sectors involved. For instance, with universities, the

rigid and flat monthly salary structure embedded in IPPIS did not sit well with the highly variable mode of

compensation peculiar to academic institutions. This created extended periods of dispute between the

government and university unions who saw the system not just as a payroll reform but also as a possible

instrument of control over academic governance. Hence, while implementation studies broadly uphold IPPIS

as a tool of reform, they also emphasize the intricate political economy concerning the introduction of digital

systems into bureaucracies with entrenched practices (Chima, 2020b)

A second cluster of scholarly work concerns evaluation and audit of the IPPIS program. These studies are

geared toward actually measuring impact in cost savings, payroll integrity, and efficiency. Perhaps the most

celebrated achievement is elimination of ghost workers. Based on the audit reports and empirical analyses, the

system has identified tens of thousands of non-existent employees who were being paid by the government

(David ABASILIM & Edet, 2015). The amount of money saved in doing so, i.e., in not paying ghost workers,

runs into billions of naira and strongly supports the IPPIS as a system that has delivered real fiscal benefits.

These findings are consistent with evidence worldwide that digitalized payroll systems could constitute anti-

corruption instruments by removing undue discretion of payroll officers and creating transparent audit trails

(Rafique et al., 2020a)

Evaluation studies did point to the persistence of some shortcomings. Real employees got omitted or were

misclassified into enrolments, thereby leading to delayed or erroneous payments. This has been aggravated by

the absence of good data cleaning tools and, to a certain extent, by the low level of digital literacy among some

payroll officers. Interoperability with other systems, therefore, is yet another key obstacle (KATUKA Yaki et

al., 2019). Although IPPIS tries to centralize payroll, it very rarely integrates without hitch with other

administrative databases, for example, those of pensions, tax authorities, or even biometric verifications.

Another inefficiency creeps in, which the system is supposed to do away with, thus, manual interventions

come back again. Leakage has also occurred because of uneven adoption rates across MDAs. Some institutions

still retain hybrid systems, where only a part of the payroll is through IPPIS and the other half continues on

legacy arrangements (Hassan et al., n.d.; Ogunode & Dauda Garba, 2024)

Audit literature further highlights accountability barriers. While it has increased payroll visibility, it has not

entirely secured the process against manipulation. Some reports indicate that fraudsters have reluctantly moved

from crude methods of ghost creation to relatively subtle ways of fraud, such as falsely declaring allowances or

manipulating the grade level within the system. These subtle shifts in a series of small irregularities may go

unnoticed without advanced analytical tools. Thus, evaluation and audit studies often conclude that while

IPPIS is a step forward, it is far from a complete answer. South to this shall be the continuous upgrading of the

exercise, coupled with constant auditing and an advanced monitoring framework fitted to uncover complex

payroll irregularities (Egwuasi et al., 2021).

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Theoretical and critical lenses are maintained by a third and aforementioned, yet smaller strand of literature.

These studies place IPPIS in a broader discussion relative to governance, public sector reform, and the political

economy of digital systems. One of the argumentations prevalent in this literature is that the centralization,

while good, cannot ensure pay integrity by itself. Based upon governance theory, it is observed that systems

are embedded in an institutional context, and the effectiveness of that system depends on design and political

will. In other words, the establishment of a centralized payroll system does not guarantee an absolute reduction

in corruption; rather, this must be enforced by an array of measures for oversight, accountability mechanisms

(Ogunode & Dauda Garba, 2024).

Critical scholarship also doubts whether, in fact, the project may unintentionally reinforce some power

asymmetries within the Nigerian state. Payroll centralization by the Accountant-General's Office may reduce

the almost complete autonomy that individual MDAs, particularly universities and research institutions,

possess in this regard. From the lens of public policy, this may be considered bureaucratic rationalization, but

from a governance view, it would be a difficulty of balancing efficiency with institutional independence. Some

writers opine that ignoring these considerations will place new tensions that could threaten the legitimacy and

durability of the reforms (Egwuasi et al., 2021).

In another complexion of critical inquiry is posed by frauds being adaptive to reforms. With the theories of

corruption and organizational behaviour as a foundation, whereas others argue that fraud evolves and does not

disappear before new control systems. In this way, IPPIS efficacy in preventing payroll fraud of one form may

serve to motivate the development of newer, more insidious methods that take advantage of the design or

oversight weaknesses of the system. This theory accentuates the fact that innovations ought to continue to

occur concerning tools for auditing and for monitoring, rather than accepting mechanisms that require one-

time actions for some seemingly permanent guarantee of payroll integrity. In all, these views truly stressed the

need to consider IPPIS not simply as a technical system but rather as a governance intervention imbued with

politics, institutions, and ruptured human behaviour (Egwuasi et al., 2021).

This basically means that together, this triumvirate of researches paints a full picture of IPPIS in Nigeria.

Implementation studies showcase the adoption process and the resistance it faced; evaluation and audit studies

report both financial savings and the continuing technical problems; and theoretical perspectives give critical

insights on the governance implications of centralization. Yet, a faint research gap remains. The greater part of

this literature ends with either a description of its implementation or more broadly an evaluation of its

outcomes. Relatively little scholarship exists that would look at how one could conceivably design analytic

frameworks to systematically detect payroll anomalies that are not comprised in the usual ghost worker

framework (YAHAYA YUSUF et al., 2024a).

This gap is most important considering that payroll fraud is becoming more sophisticated with every passing

day. Examples include data entry errors, manipulation of allowances, grade-level inflation, and taking

advantage of interoperability loopholes, to name a few. Without advanced analytic models, the best that

policymakers and auditors can do is take reactive measures to identify those issues after they have already led

to financial damages. Thus, the design of an anomaly detection framework that is proactive and data-oriented

would become a landmark achievement in the theory and practice. This would take the literature beyond

descriptive or evaluative accounts and into prescriptive, solution-oriented research (Targba & Osuji, 2023).

This study arises within the gap presented by the foregoing discussion. It seeks to augment the literature in two

ways by proposing a practical model for anomaly detection in payroll systems. First, it enriches

methodologically with a demonstration of how analytic tools can be used effectively in existing payroll

structures to enhance oversight. Second, the latter contributes to governance debates on continuous monitoring

strategies being employed to complement technical systems in addressing the adaptive nature of fraud. In this

respect, the study extends previous research while overcoming its limitation to present a framework that is

both theoretically well-grounded and practically applicable (YAHAYA YUSUF et al., 2024b).

Literature on IPPIS in Nigeria is rich and diverse, addressing multiple facets of the system's implementation,

evaluation, and theoretical relevance. Implementation studies bring to the fore the challenges of rolling out a

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centralized pay system to diverse MDAs, such as resistance, infrastructure shortages, and institutional politics

(Olagunju et al., n.d.; Ugochukwu & Chinedu, 2024). Evaluation and audit studies provide field evidence of

cost savings alongside documenting persistent issues with data inaccuracies, poor interoperability, and variable

take-up. Theoretical perspectives place IPPIS within broader governance and corruption debates, questioning

the sufficiency of centralization and emphasizing the adaptability of fraud. However, in all three strands,

analytic approaches to proactive anomaly detection receive relatively minor consideration. The study bridges

the gap directly, providing a model that integrates technical tools with principles of governance to build

payroll integrity in the public sector of Nigeria (Olagunju Folorunso & Olufemi Simeon, 2021).

METHODOLOGY

The method adopted in this paper is a hybrid forensic payroll analytics approach structured around three pillars

that are integrated with each other. The first of these pillars is synthetic data generation that addresses the

limitation of the scarce availability of raw payroll records. To circumvent this, a synthetic payroll generator is

developed from statistical distributions in audits, thereby enabling the construction and testing of analytical

models without violating data confidentiality. The second pillar focuses on anomaly detection algorithms,

where a number of techniques are integrated in order to detect different dimensions of payroll anomalies. More

specifically, the Isolation Forest algorithm is applied to detect extreme values of salaries or abnormal

frequencies of payments, and the Local Outlier Factor (LOF) to detect groups of employees for whom the pay

patterns are considerably different from those of their counterparts (Ajike & Reuben, 2024).

Additionally, graph-based outlier detection algorithms are utilized for identifying duplicate accounts, such as

when multiple employees are linked to a single bank account. Additionally, change point detection is applied

on payroll time-series data to identify sudden and unjustified jumps in pay grades. The third column consists of

rule-based forensic checks that include civil-service-related rules in the detection engine (Ezegwu & Obichili,

n.d.). For example, rules such as marking duplicate account hashes of different employees or marking

redundant job titles without approval from human resources are coded to augment the machine learning

outcomes. With the inclusion of these precautions, the framework obtains a composite risk score for all payroll

transactions, thereby making systematic flagging of suspicious transactions for additional human audit easier

(Hasti et al., 2020; Rafique et al., 2020b).

RESULTS

The system was also tested on a hybrid dataset that combined seeded anomalies into payroll simulation data

and an attached set of labelled audit samples where such data was available. This allowed for controlled testing

of how the system performs to detect anomalies but with realistic payroll trends. The evaluation employed

performance measures, including precision, recall, and decrease in investigator workload, to measure both

accuracy and real-world utility. Pre-simulation results showed that the hybrid forensic payroll analytics

framework outperformed single-method traditional methods. Specifically, the use of machine learning

algorithms in combination with rule-based forensic checks offered high-level reduction in false positives over

systems employing a solitary component. This balance served to ensure that detectives were not overwhelmed

with mountains of flagged instances, thereby improving the overall effectiveness of audits.

In operational design, the framework supports two deployment modes. A batch-processing mode is geared

towards periodic checks, e.g., monthly payroll audits, in order to identify systemic variations and remediate

them within routine administrative processes. At the same time, a streaming mode was implemented to allow

for real-time auditing of payroll updates as transactions are being processed. This two-in-one capability

enhances the flexibility of the framework such that it can be applied both in retrospective analysis and fraud

detection in proactive mode. The preliminary results thus suggest not just that the system enhances detection

accuracy, but also that it aligns with the operating needs of payroll management in public organizations.

DISCUSSION

This model represents a new direction for improving payroll fraud detection within the Integrated Payroll and

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Personnel Information System (IPPIS). Contrary to current research, which relies heavily on descriptive

analysis of payroll abnormalities, the new direction offers an auditing method that can be utilized directly by

auditors without compromising data confidentiality. By relying on metadata and pseudonymized identifiers

rather than on real personal information, the framework ensures feasibility and compliance in highly sensitive

government contexts where data privacy takes highest priority. This methodological contribution emphasizes

the potential of combining computational tools with institutional protection in order to further promote fiscal

accountability in public administration. The architecture supports forensic payroll analytics in the following

ways. Firstly, it provides a way to produce synthetic payroll data where full records are restricted from view,

hence supporting system development and test without violating confidentiality procedures. Secondly, it shows

how to merge unsupervised methods of anomaly detection with domain forensic rules to enable more robust

detection of statistical anomalies and violations depending on context.

Despite these benefits, certain limitations must be taken into consideration. Anomaly detection and model mis

implementation or misspecification are directly proportionate to payroll metadata quality and

comprehensiveness. Where records are inconsistent, fragmented, or manipulated in purpose, anomaly detection

software may fail to detect even sophisticated forms of fraud. Although the hybrid approach reduces false

positives compared to single-method detection, no system can ever eliminate misclassification risk entirely.

This brings into play the necessity for robust review and grievance mechanisms to protect workers from

unjustified suspicion and to ensure trust in the auditing process. Overcoming these limitations will be crucial to

ensuring that the system is sound and morally acceptable in use at scale.

CONCLUSION

Integrated Payroll and Personnel Information System (IPPIS) is Nigeria's flagship e-governance reform, and its

long-term sustainability relies on the adoption of more advanced analytic capabilities with integrity and

transparency assurance. This study moves in that direction by designing a hybrid forensic payroll system with

integrated machine learning methods, rule-based audit, and governance controls. In pioneering new ground

from descriptive observations of payroll administration, the framework not only assists theoretical arguments

on e-government accountability in academic circles but also provides policymakers with a clear roadmap

towards enhancing fraud prevention and overall operational efficiency.

Particularly, the coordination of the protection and ethical governance strategies is to put emphasis on having

to break institutionalized trust, technical innovation, and protecting the staff. Piloting the model in carefully

selected Ministries, Departments, and Agencies (MDAs) with rigorous measurement of performance against

real audit results, and aligning governance processes to cater to data quality, privacy, and grievance redress

issues is what future studies should strive for. These actions will be important to making IPPIS a useful tool for

public sector reform and budget accountability in Nigeria.

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