Authors

  • Viktoriia Lezhanina
    Bookkeeper at SC LLC, FL, USA, Auditor at Compliance Audit LTD, Ukraine

DOI:

https://doi.org/10.37547/tajmei/Volume07Issue05-05

Keywords:

Internal Audit Financial Reporting Digitalization Audit Risk Small and Medium-Sized Enterprises (SMEs) Cybersecurity Data Analytics Control Environment

Abstract

This paper examines the core challenges confronting internal audit functions and evaluates their implications for the quality of financial reporting. Drawing on prior research emphasizing the role of internal audits in enhancing transparency, the study situates its analysis in the context of small and medium-sized enterprises (SMEs) that experience acute resource constraints and heightened vulnerability to fraud and misstatements. Key findings reveal that methodological incoherence—evidenced by a lack of unified audit standards—coupled with incomplete adoption of advanced data-analytics tools significantly undermines the reliability of financial disclosures. Moreover, widespread digitalization introduces additional complexities, including cybersecurity threats and the need for specialized IT expertise. These deficiencies can inflate audit risk and detection failures, ultimately jeopardizing stakeholder trust. The paper concludes with targeted recommendations to refine audit procedures, integrate robust technological solutions, and foster stronger engagement of managerial and shareholder communities in sustaining high-quality financial statements.


background image

The American Journal of Management and Economics Innovations

45

https://www.theamericanjournals.com/index.php/tajmei

TYPE

Original Research

PAGE NO.

45-51

DOI

10.37547/tajmei/Volume07Issue05-05



OPEN ACCESS

SUBMITED

20 March 2025

ACCEPTED

22 April 2025

PUBLISHED

12 May 2025

VOLUME

Vol.07 Issue 05 2025

CITATION

Viktoriia Lezhanina. (2025). Internal audit issues and their impact on
the quality of financial reporting. The American Journal of Management
and Economics Innovations, 7(05), 45

51.

https://doi.org/10.37547/tajmei/Volume07Issue05-05

COPYRIGHT

© 2025 Original content from this work may be used under the terms
of the creative commons attributes 4.0 License.

Internal audit issues and
their impact on the quality
of financial reporting

Viktoriia Lezhanina

Bookkeeper at SC LLC, FL, USA,
Auditor at Compliance Audit LTD, Ukraine

Abstract:

This paper examines the core challenges

confronting internal audit functions and evaluates their
implications for the quality of financial reporting.
Drawing on prior research emphasizing the role of
internal audits in enhancing transparency, the study
situates its analysis in the context of small and medium-
sized enterprises (SMEs) that experience acute
resource constraints and heightened vulnerability to
fraud and misstatements. Key findings reveal that
methodological incoherence

evidenced by a lack of

unified audit standards

coupled with incomplete

adoption of advanced data-analytics tools significantly
undermines the reliability of financial disclosures.
Moreover,

widespread

digitalization

introduces

additional complexities, including cybersecurity threats
and the need for specialized IT expertise. These
deficiencies can inflate audit risk and detection failures,
ultimately jeopardizing stakeholder trust. The paper
concludes with targeted recommendations to refine
audit procedures, integrate robust technological
solutions, and foster stronger engagement of
managerial and shareholder communities in sustaining
high-quality financial statements.

Keywords:

Internal Audit; Financial Reporting;

Digitalization; Audit Risk; Small and Medium-Sized
Enterprises (SMEs); Cybersecurity; Data Analytics;
Control Environment.

Introduction:

An increasing demand for transparency

in financial reporting has amplified the impor-tance of
internal auditing in organizations across various sectors
[8, 9]. Stakeholders

ranging from investors to

regulatory

bodies

expect

corporate

finan-cial

statements to be both accurate and reliable,


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underscoring the need for robust internal audit
procedures. These procedures serve as a safeguard
against misstatements and fraud, ultimately supporting
market

confidence

in

reported

figures

[1].

Furthermore,

the

current

wave

of

digital

transformation, encompassing the growing application
of artificial intelligence (AI) and advanced data-
analytics methods, has introduced both additional
opportunities and heightened complexities into
internal auditing [2, 12]. While automation can
significantly enhance efficiency in detecting anomalies
and errors, the lack of standardized approaches for
auditing AI-driven processes poses new risks to the
quality of financial statements [6].

Simultaneously, small- and medium-sized enterprises
(SMEs) face unique obstacles when strengthening their
internal audit functions [15]. With relatively limited
resources and expertise, SMEs often lag in adopting
contemporary digital tools and platforms, leading to
potential vulnerabilities in their audit and control
environ-ment [13]. As SMEs comprise a substantial
portion of many economies, ensuring that these
enterprises have access to effective internal audit
frameworks becomes crucial for maintaining financial
stability [5].

A growing div of research highlights the
transformative role of internal auditing not only in
reducing fraud risk but also in contributing to strategic
decision

making

[3].

Studies

underscore

that

deficiencies in internal audit methodologies

such as

outdated control checklists or inadequate training in
emerging technologies

can directly compromise the

reliability of financial reporting [7, 10]. In addition,
recent works emphasize the heightened relevance of
digital risks, spanning cyber threats to shortcomings in
cloud-based systems integration [3, 11]. While large
corporations

often

have

dedicated

IT-audit

departments, SMEs with more constrained budgets
may find themselves unable to deploy strong digital
safeguards [4]. Consequently, research calls for more
standardized guidelines and greater investment in
developing the auditing capacity to address big-data
analytics, AI-based decision support, and overall
cybersecurity [16].

Despite growing academic attention, notable gaps
remain. For instance, many studies focus on auditing in
large entities, leaving the unique challenges of SMEs
relatively underexplored [14, 15]. Furthermore, the

interplay between newly adopted technological tools

like AI-driven risk assessment

and conventional

internal audit procedures still lacks cohesive
frameworks that would allow auditors to integrate
novel techniques reliably [12, 13].

In light of these considerations, the primary objective
of this study is to identify the key problems currently
confronting internal audit functions and to evaluate
how these issues affect the quality of financial
reporting. Special attention will be paid to the
influences of AI, cloud computing, and cybersecurity
requirements on audit procedures. Based on the
findings,

the

paper

will

propose

specific

recommendations aimed at refining methodological
and procedural aspects of internal auditing to ensure
more accurate and trustworthy financial statements in
both SMEs and larger entities.

1. Key issues in internal auditing

Methodological

and

organizational

constraints,

inadequate adaptation to digital technologies, and
escalating cyberrisks together form a complex set of
challenges that affect the effectiveness of internal
auditing and, ultimately, the quality of financial
reporting [4, 5, 12, 15]. Research findings indicate that
the absence of unified standards often leads to
duplicated procedures, incomplete testing, and a
higher probability of oversight. This issue is especially
acute for small and medium-sized enterprises (SMEs),
where resource shortages further complicate the
execution of high-quality internal audits.

In many countries, the development of detailed

methodological guidelines is left to industry
associations or individual firms. As a result,
organizations

must

rely

on

generalized

recommendations that do not always reflect specific
industry features or constrained financial and human
resources [15]. For instance, the classical approach to
reducing overall audit risk (AR) is to consider the
product of

IR × CR × DR,

where IR denotes inherent risk, CR represents control
risk, and DR refers to detection risk [2]. However, in an
environment where part of the audit sample is
processed manually and procedures are inconsistently
applied, IR and CR values may be miscalculated,
thereby inflating DR even at the audit planning stage.


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Financial and staffing constraints are particularly
significant in SMEs, which, according to Brodny and
Tutak (2022), make up a substantial segment of the
European economy. Their vulnerability lies in limited
access to advanced analytical instruments and in
difficulties

hiring

qualified

internal

auditors.

Consequently, several key control functions may be
partially overlooked, creating gaps in examining the
most risk-prone areas such as debtor

creditor

relationships and intangible-asset transactions [15].

Challenges related to digitalization and technological
innovations become more serious when IT systems

deployed at a given enterprise are insufficiently
integrated into the overall audit framework [4].
Fragmented

IT

infrastructure

gives

rise

to

inconsistencies

in

data

across

departments,

complicating the collection of audit evidence. Likewise,
a lack of expertise in big data and AI poses a dilemma:
even if modern analytics platforms are available, the
findings they produce may be misinterpreted [12]. The
shortage of tech-savvy professionals and data analysts
who can adapt big data to the specific needs of internal
auditing further heightens overall audit risk [2]. Table 1
summarizes some factors that hinder the full-scale use
of digital solutions in internal auditing.

Table 1. Key barriers to implementing digital technologies in internal auditing

Barrier

Description

Impact

1. Fragmented IT

systems

Lack of a unified platform and

inconsistent software solutions across

departments

Increased risk of data loss and

complications in transaction analysis

2. Skills shortages

in big data and AI

Few experts capable of interpreting

outputs from intelligent algorithms

Errors in risk assessment and low

effectiveness in anomaly detection

3. Suboptimal

data architecture

No clear procedures for data

accumulation and verification

Limited reproducibility of audit tests

and disruptions in control processes

Cyberrisks and information security take on critical
importance given the marked increase in electronic
document flows. According to Rikhardsson et al. (2022),
even small companies may handle a volume of financial
information comparable to that of much larger
organizations. The growing number of cyberattacks and
sophistication of malicious tools mean internal auditors
must assess not only accounting transactions but also
the overall security of IT infrastructure [4]. Neglecting
these considerations can lead to situations in which
data tampering or unauthorized copying goes

unnoticed, ultimately distorting an enterprise’s actual

financial standing. This risk is particularly high in SMEs,
where financial constraints often preclude the
installation of comprehensive encryption systems and
consistent IT security audits [5].

In sum, weak methodological foundations

especially

evident in resource-limited SMEs

combined with

technological challenges and cyberthreats create a

multifaceted set of problems. These factors intensify
classical audit risks and add new threats to the
reliability of financial statements. Overcoming such
barriers necessitates unified standards and an
expanded range of competencies for auditors, including
in-depth knowledge of digital platforms. However,
implementing such measures is complicated by budget
limitations and a shortage of qualified personnel at
most firms. Fragmented IT infrastructure and a lack of
codified procedures for secure data storage exacerbate
the threat of cyberattacks, further highlighting the
need for coordinated efforts between auditing and
information security teams. Addressing these obstacles
requires a reexamination of traditional audit methods,
focusing on advanced technological support and
ongoing staff training.

2. Impact of these problems on the quality of financial
statements


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Ongoing deficiencies in internal control, insufficient risk
management practices, and the evolving complexities
of digital audit techniques can significantly compromise
the reliability of corporate financial reporting [4, 5, 12,
15]. A crucial aspect of mitigating such challenges lies in
understanding how the absence of robust policies and
procedures

further exacerbated by inadequate

adoption of IT solutions

exposes an enterprise to

heightened risks of misstatements and fraud.

Weak internal control environments amplify the
probability of errors and fraudulent manipulations.
When classical audit risk (AR) is conceptualized as

AR = IR × CR × DR

where IR represents inherent risk, CR stands for control
risk, and DR refers to detection risk

ineffective

internal controls escalate CR, thereby increasing AR
overall. This relationship becomes especially precarious
if limited resources force small internal audit teams to
prioritize certain accounts or processes at the expense
of others [15]. In such scenarios, even routine data
entry mistakes or seemingly minor misclassifications
can

go

undetected,

fueling

larger

financial

discrepancies. Table 2 exemplifies how weak internal
control can interact with each component of AR,
illustrating the cumulative nature of potential
misstatements.

Table 2. Interaction of weak internal controls with audit risk components

Risk

component

Primary issue

Consequence

Inherent
risk (IR)

Complex transaction structures
or high estimation uncertainty

Greater

a priori

likelihood of errors in specialized

areas like intangible assets

Control risk
(CR)

Deficient segregation of duties,
incomplete

reconciliation

processes

Systemic flaws enable misstatements or fraud to
remain hidden from basic checks

Detection
risk (DR)

Restricted

audit

scope,

insufficient testing procedures

Key anomalies may go unexamined, leading to
unqualified opinions despite financial distortions

Equally critical is the sequence and thoroughness of
audit actions. An internal audit function that frontloads
data analytics or invests more resources in planning is
often better equipped to spot irregularities early.
Conversely, a disorganized approach

where random

checks precede risk assessment

may misalign testing

efforts with high-risk transactions [12]. Findings from
Brodny and Tutak (2022) reinforce that smaller entities,
in particular, benefit from structured, step-by-step
audit plans, which ensure that all major accounts and
disclosures receive proportionate scrutiny.

The importance of risk management and IT adoption
becomes evident in the context of new digital platforms
and data analytics. Enterprises employing big data
solutions or cloud-based accounting systems often
achieve more transparent recording of transactions,
thus

narrowing

the

scope

for

undetected

misstatements [15]. However, digital platforms alone
do not guarantee higher data quality. Auditors must be
capable of interpreting analytics outputs, including
anomaly detection flagged by AI algorithms, and then
aligning these insights with the established control
environment [4]. If an organization underinvests in
analytical capabilities or staff training

especially

around big data governance and data integrity

financial statements may not reflect actual
performance, thereby increasing litigation risk and
damaging stakeholder trust.

The potential for erroneous or manipulated data
emphasizes the need for continuous investments in
robust monitoring mechanisms. In many cases,
organizations assume that once a set of control
procedures is in place, ongoing oversight remains
minimal [12]. This misconception frequently emerges in


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smaller firms, where limited resources and cost
considerations can deprioritize periodic upgrades or
maintenance of IT systems. Table 3 highlights how
improving internal controls and IT solutions can

tangibly enhance financial statement reliability,
framing these efforts as a cyclical process of
reassessment and improvement.

Table 3. Key investments in control systems for enhanced financial reporting

Investment

area

Action required

Expected outcome

Advanced

analytics

tools

Acquire or update software to capture,

store, and interpret high-volume datasets

Reduced detection risk through

improved anomaly spotting and

predictive modeling

Continuous

staff training

Regular skill development in data

governance, machine learning applications,

and financial audit expertise

Higher accuracy in financial statement

verifications and deeper domain

expertise

Integrated

control

frameworks

Align separate IT subsystems and create

unified compliance checklists for main

business processes

More coherent audit trails, boosting

internal and external confidence in

disclosures

Additional value in fortifying controls arises from the
involvement of management and shareholders in
ensuring data quality and transparency. When top
executives demonstrate a visible commitment to
thorough internal audit reviews, this endorsement

serves as a cornerstone for a “tone at the top”

environment conducive to ethical compliance [5]. In
publicly traded companies, heightened shareholder
scrutiny can reinforce the diligence of the board of
directors, driving a culture that prioritizes robust
financial disclosures. Such a culture not only instills
stronger operational discipline but also heightens the
sense of accountability among mid-level managers [12].
Moreover, the presence of a reliable internal audit
function can attract more risk-averse investors, who

seek assurance that the firm’s reported earnings

genuinely reflect economic reality.

Investor confidence thus thrives when organizations
commit to transparent oversight frameworks [4].
Evidence from small and medium-sized enterprises
indicates that even incremental upgrades

such as

routine digital backups, timely reconciliations, and
systematic staff training

can lower perceived

investment risk [15]. In contrast, enterprises that
routinely bypass internal checks risk fostering an

environment where financial manipulations remain
undetected, thereby undermining the trust of lenders,
regulators, and capital market participants.

In sum, the interplay between strong controls,
sophisticated IT-enabled methodologies, and active
stakeholder involvement is paramount for delivering
credible financial statements. An environment that
neglects any of these dimensions

whether through

weak sequential testing or limited technological
investment

risks producing financial data that are

both inaccurate and susceptible to fraudulent
influences.

Nonetheless,

organizations

that

consistently refine their internal auditing protocols,
integrate advanced digital platforms, and engage their
managerial and shareholder communities build a more
sustainable foundation for long-term financial integrity
[12, 15].

CONCLUSION

This research underscores the pivotal relationship
between internal audit efficacy and the caliber of
financial disclosures. The absence of harmonized audit
methodologies not only generates inconsistencies but
also expands the scope for unchecked errors and fraud.


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While SMEs face particularly pronounced difficulties
stemming from limited finances, human capital
shortages, and less sophisticated IT infrastructures,
these challenges also manifest in larger entities striving
to align with emerging best practices. Evidence from
recent studies highlights the growing relevance of
digital platforms in both detecting anomalies and
broadening the range of potential misstatements.
Cyberrisks further amplify the need for concerted
investment in security protocols and staff training,
ensuring that technological adoption does not merely
introduce new vulnerabilities.

Ultimately, the results show that upgrading traditional
internal audit frameworks to reflect the demands of
modern, data-intensive operating environments can
strengthen

managerial

oversight

and

elevate

stakeholder confidence. Management teams, board
members, and shareholders therefore bear collective
responsibility for establishing clear procedural
guidelines, investing in continuous professional
development, and embracing integrated analytical
tools. Such measures not only bolster audit reliability
but also contribute to the stability of financial markets
by promoting consistent and transparent reporting.

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Commerford, B. P., Dennis, S. A., Joe, J. R., & Warne, R.
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IFAC. (2018). Handbook of International Quality
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Omoteso, K. (2012). The application of artificial
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8495.

Raschke, R. L., Trewin, U., & Williams, P. F. (2018). A
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147.

Rikhardsson, P., Thórisson, K. R., Bergthorsson, G., &
Batt, C. (2022). Artificial intelligence and auditing in

small‐ and medium‐sized firms: Expectations and

applications. AI Magazine, 43(3), 323

336.

Sun, T., & Vasarhelyi, M. A. (2017). In digital accounting:
The effects of cognitive computing on assurance and
the evolution of auditing. Journal of Emerging
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Sutton, S. G., Holt, M., & Arnold, V. (2016). The reports
of my death were greatly exaggerated

artificial

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background image

The American Journal of Management and Economics Innovations

51

https://www.theamericanjournals.com/index.php/tajmei

Tîrcovnicu, G.-I., & Hategan, C.-D. (2023). The audit risk
assessment of European small- and mid-size
enterprises. Journal of Risk and Financial Management,
16(3), 158.

Vasarhelyi, M. A., Sun, T., & Issa, H. (2016). Research
ideas for artificial intelligence in auditing. Journal of
Emerging Technologies in Accounting, 13(2), 1

20.

References

AICPA. (2015). Reimagining auditing in a wired world: A call to action for the profession. American Institute of Certified Public Accountants.

Alles, M. G., & Gray, G. L. (2020). Will audit analytics and AI transform the audit? Current Issues in Auditing, 14(2), 9–20.

Basuony, M. A. K., Mohamed, E. K. A., Hussain, M. M., & Marie, L. (2017). The effect of internal audit function on the financial performance of small and medium enterprises: An emerging market perspective. International Journal of Accounting and Information Management, 25(2), 159–180.

Broccardo, L., Tenucci, A., Agarwal, R., & Alshibani, S. M. (2024). Steering digitalization and management control maturity in small and medium enterprises (SMEs). Technological Forecasting & Social Change, 204, 123446.

Brodny, J., & Tutak, M. (2022). Digitalization of small and medium-sized enterprises and economic growth: Evidence for the EU-27 countries. Journal of Open Innovation: Technology, Market, and Complexity, 8(2), 67.

Chan, D. K., & Kim, S. H. (2020). Emerging AI applications in auditing: Opportunities, challenges, and ethical considerations. In Proceedings of the AAA Annual Meeting (pp. 55–68). American Accounting Association.

Commerford, B. P., Dennis, S. A., Joe, J. R., & Warne, R. C. (2021). Who or what is the auditor? The influence of the nature of the auditor’s work on intrinsic motivation and interactions with AI audit technology. Journal of Accounting Research, 59(5), 1536–1576.

ICAEW. (2018). Artificial Intelligence and the Future of Accountancy. Institute of Chartered Accountants in England and Wales.

IFAC. (2018). Handbook of International Quality Control, Auditing, Review, Other Assurance, and Related Services Pronouncements. International Federation of Accountants.

Omoteso, K. (2012). The application of artificial intelligence in auditing: Looking back to the future. Expert Systems with Applications, 39(9), 8490–8495.

Raschke, R. L., Trewin, U., & Williams, P. F. (2018). A cognitive style perspective of AI usage in auditor inquiry. Journal of Information Systems, 32(3), 125–147.

Rikhardsson, P., Thórisson, K. R., Bergthorsson, G., & Batt, C. (2022). Artificial intelligence and auditing in small‐ and medium‐sized firms: Expectations and applications. AI Magazine, 43(3), 323–336.

Sun, T., & Vasarhelyi, M. A. (2017). In digital accounting: The effects of cognitive computing on assurance and the evolution of auditing. Journal of Emerging Technologies in Accounting, 14(2), 27–43.

Sutton, S. G., Holt, M., & Arnold, V. (2016). The reports of my death were greatly exaggerated—artificial intelligence research in accounting. International Journal of Accounting Information Systems, 22, 60–73.

Tîrcovnicu, G.-I., & Hategan, C.-D. (2023). The audit risk assessment of European small- and mid-size enterprises. Journal of Risk and Financial Management, 16(3), 158.

Vasarhelyi, M. A., Sun, T., & Issa, H. (2016). Research ideas for artificial intelligence in auditing. Journal of Emerging Technologies in Accounting, 13(2), 1–20.