ОБЛІКОВО-АНАЛІТИЧНЕ ЗАБЕЗПЕЧЕННЯ АУДИТУ ВИРОБНИЦТВА ТА ЕКСПОРТУ ПРОДУКЦІЇ РОСЛИННИЦТВА ПІДПРИЄМСТВАМИ АГРОБІЗНЕСУ
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Репозитарії
Agrosvit| _version_ | 1867479185241407488 |
|---|---|
| author | Копотієнко, Т. Ю. Шелестянка, Н. І. |
| author_facet | Копотієнко, Т. Ю. Шелестянка, Н. І. |
| author_institution_txt_mv | [
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"author": "Т. Ю. Копотієнко",
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"author": "Н. І. Шелестянка",
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| author_sort | Копотієнко, Т. Ю. |
| baseUrl_str | https://www.nayka.com.ua/index.php/agrosvit/oai |
| collection | OJS |
| datestamp_date | 2026-06-08T08:39:19Z |
| doi_str_mv | 10.32702/2306-6792.2026.10.448 |
| first_indexed | 2026-06-09T01:02:15Z |
| format | Article |
| fulltext |
448
АГРОСВІТ № 10, 2026
ISSN 2306-6792Copyright © The Author(s). This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/).
УДК 657:657.6:631:339.5
T. Kopotiienko,
PhD in Economics, Associate Professor,
Associate Professor of the Department of Financial Analysis and Audit, .
State University of Trade and Economics
ORCID ID: https://orcid.org/0000-0001-6107-9937
N. Shelestianka,
Auditor, Master's student at the Department of Financial Analysis and Audit,
State University of Trade and Economics
ORCID ID: https://orcid.org/0009-0004-3954-9401
ACCOUNTING AND ANALYTICAL SUPPORT
FOR THE AUDIT OF PRODUCTION
AND EXPORT OF CROP PRODUCTS
AT AN AGRIBUSINESS ENTERPRISES
Т. Ю. Копотієнко,
к. е. н., доцент, доцент кафедри фінансового аналізу та аудиту, Державний торговельно-економічний університет
Н. І. Шелестянка,
аудитор, магістрант кафедри фінансового аналізу та аудиту, Державний торговельно-економічний університет
ОБЛІКОВО-АНАЛІТИЧНЕ ЗАБЕЗПЕЧЕННЯ АУДИТУ ВИРОБНИЦТВА ТА ЕКСПОРТУ
ПРОДУКЦІЇ РОСЛИННИЦТВА ПІДПРИЄМСТВАМИ АГРОБІЗНЕСУ
Introduction. The article provides a theoretical and methodological substantiation and conceptualization of
accounting and analytical support for the audit of production and export of crop products under conditions of digital
transformation of agribusiness and growing global uncertainty.
It is substantiated that the modern development of the agricultural sector is characterized by the simultaneous
complication of production processes caused by the biological nature of assets, as well as by the expansion of export-
oriented activities accompanied by an increased level of currency, logistics, and regulatory risks. It is proved that
under such conditions, traditional approaches to the formation of accounting and analytical information focused on
retrospective reflection of business operations do not provide an adequate level of information support for audit.
It is determined that the key prerequisite for increasing audit efficiency is the transformation of accounting and
analytical support into an integrated digitally oriented system capable of ensuring the formation, processing, and
verification of information in a mode close to real time. Such a system should perform not only an informational
function, but also an analytical and forecasting function, ensuring risk identification and support for managerial
decision-making.
Purpose. The purpose of the study is to develop a conceptual model of accounting and analytical support for the
audit of production and export of crop products of agribusiness enterprises based on the principles of integration,
adaptability, and risk orientation.
Methods. The methodological basis of the study is a systems approach, which made it possible to consider
accounting and analytical support as a multi-level integrated system combining accounting, analytical, and control
subsystems. In the course of the study, methods of theoretical generalization, analysis and synthesis, comparative
analysis, economic and statistical methods, as well as digital analytics tools, including Big Data, machine learning,
and automated audit, were used.
DOI: 10.32702/2306-6792.2026.10.448
АГРОСВІТ № 10, 2026
449
ISSN 2306-6792 Copyright © The Author(s). This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/).
Results. As a result of the study, a conceptual model of accounting and analytical support for audit was developed,
which provides for the integration of financial, management, and tax accounting in a single digital environment using
intelligent data analysis tools. It is proved that the implementation of the proposed model ensures an increase in the
reliability of accounting information, the efficiency of audit procedures, and the level of information transparency of
agribusiness enterprises.
The study identifies key directions for the development of accounting and analytical support for audit are the
introduction of continuous auditing technologies, the use of artificial intelligence for risk identification, ensuring
product traceability, and the integration of ESG indicators into the system of analytical evaluation of enterprise
performance.
Practical implications. The practical significance of the obtained results lies in the possibility of using the proposed
model to improve the efficiency of internal audit, enhance risk management of foreign economic activity, and ensure
the competitiveness of agribusiness enterprises in international markets.
Originality / Scientific novelty. A model combining ERP systems, satellite monitoring, and blockchain traceability
of export batches, integrating financial, management, and tax accounting in a single digital environment, is proposed;
the approach to forming information support for audit on the basis of risk orientation has been improved, which
makes it possible to identify critical zones of production and export activity; the theoretical substantiation of the role
of the accounting and analytical system as a tool of proactive audit using digital technologies and data analytics has
been further developed; the integration of digital audit tools (Big Data, artificial intelligence, automated control) into
the process of auditing export operations has been proposed; the expediency of using product traceability technologies
as a component of increasing the reliability of audit reports has been substantiated.
Вступ. У статті здійснено теоретико-методичне обгрунтування та концептуалізацію обліково-аналітичного
забезпечення аудиту виробництва та експорту продукції рослинництва в умовах цифрової трансформації агро-
бізнесу та зростання глобальної невизначеності.
Обгрунтовано, що сучасний розвиток аграрного сектору характеризується одночасним ускладненням вироб-
ничих процесів, зумовлених біологічною природою активів, та розширенням експортно-орієнтованої діяльності,
яка супроводжується підвищеним рівнем валютних, логістичних і регуляторних ризиків. Доведено, що в таких умо-
вах традиційні підходи до формування обліково-аналітичної інформації, орієнтовані на ретроспективне відобра-
ження господарських операцій, не забезпечують належного рівня інформаційної підтримки аудиту.
Визначено, що ключовою передумовою підвищення ефективності аудиту є трансформація обліково-аналітич-
ного забезпечення у інтегровану цифрову орієнтовану систему, здатну забезпечувати формування, обробку та ве-
рифікацію інформації у режимі, наближеному до реального часу. Така система має виконувати не лише інформа-
ційну, а й аналітико-прогностичну функцію, забезпечуючи ідентифікацію ризиків та підтримку управлінських
рішень.
Мета. Метою дослідження є розробка концептуальної моделі обліково-аналітичного забезпечення аудиту ви-
робництва та експорту продукції рослинництва підприємств агробізнесу, яка базується на принципах інтегрова-
ності, адаптивності та ризик-орієнтованості.
Методологічну основу дослідження становить системний підхід, який дозволив розглядати обліково-аналі-
тичне забезпечення як багаторівневу інтегровану систему, що поєднує облікову, аналітичну та контрольну підсис-
теми. У процесі дослідження використано методи теоретичного узагальнення, аналізу і синтезу, порівняльного
аналізу, економіко-статистичні методи, а також інструменти цифрової аналітики, зокрема Big Data, машинного
навчання та автоматизованого аудиту.
У результаті дослідження розроблено концептуальну модель обліково-аналітичного забезпечення аудиту, яка
передбачає інтеграцію фінансового, управлінського та податкового обліку в єдиному цифровому середовищі з
використанням інструментів інтелектуального аналізу даних. Доведено, що впровадження запропонованої моделі
забезпечує підвищення достовірності облікової інформації, ефективності аудиторських процедур та рівня інфор-
маційної прозорості підприємств агробізнесу.
Встановлено, що ключовими напрямами розвитку обліково-аналітичного забезпечення аудиту є впроваджен-
ня технологій безперервного аудиту, використання штучного інтелекту для ідентифікації ризиків, забезпечення
простежуваноcті продукції та інтеграція ESG-індикаторів у систему аналітичного оцінювання діяльності
підприємств.
Практичне значення отриманих результатів полягає у можливості використання запропонованої моделі для
підвищення ефективності внутрішнього аудиту, удосконалення управління ризиками зовнішньоекономічної діяль-
ності та забезпечення конкурентоспроможності підприємств агробізнесу на міжнародних ринках..
Наукова новизна. Запропоновано модель, що поєднує ERP-системи, супутниковий моніторинг та блокчейн-
простежуваності експортних партій, що поєднує фінансовий, управлінський та податковий облік у єдиному циф-
ровому середовищі; удосконалено підхід до формування інформаційного забезпечення аудиту на засадах ризик-
орієнтованості, що дозволяє ідентифікувати критичні зони виробничо-експортної діяльності; набуло подальшого
розвитку теоретичне обгрунтування ролі обліково-аналітичної системи як інструменту проактивного аудиту із
застосуванням цифрових технологій та аналітики даних; запропоновано інтеграцію інструментів цифрового аудиту
(Big Data, штучний інтелект, автоматизований контроль) у процес перевірки експортних операцій; обгрунтовано
доцільність використання технологій простежуваності продукції як складової підвищення достовірності аудиторсь-
ких звітів.
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ISSN 2306-6792Copyright © The Author(s). This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/).
PROBLEM STATEMENT
The digital transformation of business and the
active integration of agricultural sector enterprises
into global supply chains significantly increase the
requirements for the quality, transparency, and
reliability of information support for their
activities. The specifics of production processes in
crop production, caused by the influence of
natural and climatic factors, biological trans-
formation of assets, and technological variability,
form a complex multi-level structure of accoun-
ting data and increase the risk of their misstate-
ment. At the same time, the strengthening of the
export orientation of enterprises is accompanied
by growing currency, logistics, and regulatory
risks. This requires harmonization of the
accounting and analytical systems of agricultural
enterprises with international standards.
The practice of functioning of agribusiness
enterprises indicates the presence of systemic
problems, among which fragmentation of accoun-
ting and analytical systems, their orientation
toward retrospective reflection of business
operations, as well as an insufficient level of
integration of accounting, analytical, and control
subsystems dominate. This limits the possibilities
of conducting a comprehensive audit of production
and export of crop products and reduces the
efficiency of risk identification and the validity of
managerial decisions.
An additional constraining factor is the low
level of implementation of digital technologies, in
particular tools for big data analytics, automated
control, and decision support systems, which
makes continuous auditing impossible and
complicates monitoring of production and export
processes in real time.
Thus, the growing complexity of production
and export processes and the increasing uncer-
Практична значущість. Практична значущість результатів дослідження полягає у можливості: впровадження
інтегрованої моделі обліково-аналітичного забезпечення у діяльність підприємств агробізнесу; підвищення якості
та достовірності облікової інформації для потреб аудиту; оптимізації аудиторських процедур на основі цифрових
технологій; удосконалення системи управління ризиками експортної діяльності; використання результатів у на-
вчальному процесі при підготовці фахівців з обліку, аудиту та аграрного менеджменту.
Key words: accounting and analytical support; audit; production; foreign economic activity;
export; crop products; risk-oriented audit; digital audit; Big Data; artificial intelligence; ESG
reporting; agribusiness enterprise.
Ключові слова: обліково-аналітичне забезпечення; аудит; виробництво; зовнішньоеконо-
мічна діяльність; експорт; імпорт; продукція рослинництва; ризик-орієнтований аудит;
digital аудит; Big Data; штучний інтелект; ESG-звітність; підприємство агробізнесу.
tainty of the external environment determine the
need to form a holistic, adaptive, and risk-oriented
approach to accounting and analytical support for
audit based on the integration of digital techno-
logies, intelligent analytics, and continuous control
tools.
LITERATURE REVIEW
Modern scientific studies of 2025—2026
demonstrate a profound transformation of
theoretical and applied approaches to the
formation of accounting and analytical support
and audit in the agricultural sector, caused by the
digitalization of the economy, increasing
requirements for sustainable development, and the
integration of agribusiness into global value chains.
In particular, the study by P. Campos-Llerena
(2025) [1] substantiates that the application of the
international standard IAS 41 for the valuation of
biological assets increases the relevance of
accounting information, but at the same time
generates additional risks of its misstatement
related to the use of valuation judgments and the
high volatility of biological transformations. This
actualizes the need to strengthen the analytical
component of audit and expand the tools for
verification of accounting data.
Further development of scientific approaches
is associated with the concept of Agriculture 5.0
(2026) [5], within which the digital transfor-
mation of the agricultural sector is considered a
factor of radical change in the information
architecture of enterprises. Researchers em-
phasize the need for real-time data integration,
automation of control procedures, and the use of
intelligent analytical systems, which indicates the
limitations of traditional approaches to ac-
counting and audit under the conditions of the
digital economy.
АГРОСВІТ № 10, 2026
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Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/).
In the works of T. Yuan, X. Zhang, and X. Chen
(2025) [2], the use of machine learning algorithms
in financial audit is proposed, which makes it
possible to identify anomalous and high-risk
transactions with greater accuracy compared to
classical methods. This confirms the tendency of
transition from retrospective control to a
proactive, risk-oriented audit model.
At the same time, the studies of R. Wang et al.
(2025) [3] demonstrate the potential of applying
large language models (LLMs) in the processes of
automation of financial statement auditing, but
emphasize their limitations, in particular insuffi-
cient ability for deep interpretation of the
economic substance of transactions and ensuring
regulatory compliance. This determines the
necessity of combining digital tools with the
professional judgment of the auditor.
The conceptual foundations of the transfor-
mation of accounting under conditions of the
spread of artificial intelligence are disclosed in the
study by T. Stratopoulos and V. Wang (2025) [4],
where the expediency of integrating AI techno-
logies into all stages of the accounting and
analytical process is substantiated. The authors
prove that the implementation of intelligent
systems changes not only the tools, but also the
paradigm of accounting science, transforming it
toward an analytical and forecasting orientation.
A separate area of modern research is related
to the integration of ESG factors into the
accounting and auditing system. Studies of 2025
prove that the inclusion of environmental and
social indicators in accounting and analytical
systems creates new requirements for audit, in
particular regarding the expansion of audit objects
and increasing the level of information trans-
parency of enterprises.
In the context of the development of agricul-
tural exports, the study by O. Zhyhylii (2025) [11]
is important, in which the influence of global
challenges, logistical constraints, and regulatory
changes on the structure of export operations of
agribusiness is determined. The author substantiates
the need to improve accounting and analytical
mechanisms for controlling export activities as a
prerequisite for increasing their efficiency.
At the same time, modern studies of audit in
agriculture (2026) confirm that the sectoral
specifics of agricultural assets, in particular their
biological nature and dependence on external
factors, require the adaptation of audit procedures
and strengthening the role of analytical methods
for risk assessment.
The generalization of scientific approaches
makes it possible to distinguish the following key
trends: transformation of accounting and audit
under the influence of digital technologies (AI, Big
Data); increasing complexity of the valuation of
biological assets and related risks; transition to
proactive, risk-oriented audit; integration of ESG
indicators into the system of accounting and
analytical support; strengthening requirements for
control of export operations in agribusiness.
The practice of agribusiness enterprises indi-
cates the presence of systemic problems. Among
them are fragmentation of accounting and
analytical systems and their orientation toward
retrospective reflection of operations. There is also
a low level of integration of accounting, analytical,
and control subsystems.
MATERIALS AND METHODS
The information base of the study was formed
as an integrated system of regulatory, analytical,
and empirical sources covering acts on accounting,
auditing, and foreign economic activity, provisions
of international financial reporting standards, as
well as analytical materials of international
organizations. The empirical basis consists of data
from financial, tax, and management reporting of
agribusiness enterprises and generalized statistical
indicators of production and export of crop
products.
A specific feature of the information base is the
combination of traditional accounting data with
digital sources, in particular ERP systems,
analytical platforms, and structured datasets of
foreign economic activity, which ensures the
expansion of the audit evidence base.
The methodological basis is a systems ap-
proach, according to which accounting and
analytical support for audit is considered as an
integrated system of accounting, analytical, and
control components. The study used methods of
theoretical generalization and scientific abstrac-
tion to clarify the essence of accounting and
analytical support; analysis and synthesis to study
the processes of formation and integration of
information; comparative analysis to assess
modern approaches; economic and statistical
methods to study trends in production and export;
methods of classification and grouping to syste-
matize information flows.
The study applied tools of big data analytics,
machine learning, continuous auditing, and natural
language processing, as well as elements of
functional and process modeling. ESG indicators
were additionally integrated, which expands the
analytical capabilities of audit. The comprehensive
use of methods ensures the validity of the results
and their practical applicability.
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Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/).
MAIN RESULTS
The formation of effective accounting and
analytical support for the audit of production and
export of crop products is of decisive importance
for ensuring the reliability of information, trans-
parency of activities, and validity of managerial
decisions.
The specifics of production processes in crop
production are determined by natural and climatic
factors, the biological transformation of assets,
dependence on environmental conditions, and high
variability of business results. This forms a complex
structure of accounting data and increases the risk
of their misstatement, resulting in complications
in the process of forming a reliable accounting and
analytical basis for audit.
Additionally, the export orientation of acti-
vities creates a complex of external risks related
to currency fluctuations, logistical constraints, and
the dynamics of international markets. Taken
together, these factors create a multi-level risk
environment that requires the application of
integrated approaches to its assessment and
control. In this context, accounting and analytical
support should be considered not only as an
instrument for reflecting business transactions, but
as a comprehensive system capable of generating
analytical information to support audit decisions.
For the purpose of systematizing the risks of
production and export activities, the study
proposes an author's scheme of the risk system of
production and export activities of agribusiness
enterprises, which reflects the key groups of risks
and their interrelations (Table 1).
The proposed scheme makes it possible to
identify critical risk zones, ensures coordination
of accounting, analytical, and control processes,
and forms the basis for building an integrated
system of accounting and analytical support for
audit. Its application ensures the systematization
of risks and creates the basis for building an
integrated audit system.
At the same time, the systematization of risks
of production and export activities requires an in-
depth analysis of their economic nature and
influence on the formation of accounting infor-
mation.
Under conditions of digital transformation of
the economy, the traditional model of accounting
and analytical support does not meet the practical
requirements. This determines the need to move
toward an integrated, dynamic model capable of
functioning in a mode close to real time.
Taking into account these prerequisites, the
authors developed a conceptual model of
accounting and analytical support for the audit of
production and export of crop products based on
the principles of integration, adaptability, and risk
orientation. The model provides for the formation
of a single digital information environment within
which interaction between accounting, analytical,
and control processes is ensured. The basis of the
conceptual model is the interaction of three
contours: accounting, analytical, and control.
The accounting contour ensures the formation
of primary information on production and export
transactions taking into account the specifics of
biological assets and foreign economic activity.
The analytical contour performs processing,
systematization, and interpretation of data using
methods of economic analysis and digital analytics,
creating the basis for efficiency assessment and
identification of deviations. The control (audit)
contour ensures risk identification, verification of
information reliability, and formation of audit
conclusions.
The integration of these components provides
the possibility of transition to continuous auditing
and increases the efficiency of response to
deviations. The use of analytical tools makes it
possible to identify anomalies, assess trends, and
forecast possible deviations in enterprise activities.
A key factor in increasing the efficiency of the
proposed model is the use of digital technologies.
The application of Big Data analytics, artificial
intelligence, and machine learning tools makes it
possible to process significant volumes of financial
and non-financial data, identify anomalies and
hidden patterns, and forecast potential risks in
production and export processes.
An important element of the model is product
traceability technologies. They ensure control of
product movement from production to the final
consumer.
Within the framework of the model, it
is substantiated that the risk-oriented
approach is the basic instrument for in-
creasing audit efficiency. Its application
makes it possible to concentrate audit
procedures on the most critical segments of
activity, in particular transactions related
to currency risks, logistics costs, export
restrictions, and market price fluctuations.
Business risks
* Currency Logistical Regulatory Production Reputational
Source Exchange rate Transportation Customs Climate Quality
Impact Financial result Cost Reporting Yield Market
Level High High Medium High Medium
Control Hedging Traceability Compliance Stat models ESG
Table 1. Risk system of production and export activities of
agribusiness enterprises
Source: developed by the author.
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ISSN 2306-6792 Copyright © The Author(s). This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/).
The implementation of the model
contributes to improving the quality of
audit evidence, reducing the duration of
inspections, and increasing trust in the
reporting of agribusiness enterprises. In
addition, the integration of ESG indicators
expands the possibilities for evaluating
activities taking into account environmental
and social aspects.
Particular attention is paid to the
integration of sustainable development
principles into the accounting and
analytical support system. The inclusion of
ESG indicators in the audit process makes it
possible to carry out a comprehensive assessment
of enterprise activities taking into account not only
financial, but also environmental and social
aspects, which is critically important under
conditions of market globalization.
Thus, the proposed approach ensures the
transition to an integrated system of accounting
and analytical support for audit aimed at
improving the efficiency of managing information
flows in production and export activities. To
formalize the proposed conceptual model of
accounting and analytical support for the audit of
production and export of crop products, it is
advisable to present its structural elements in a
generalized table (Table 2).
The presented model provides a com-
prehensive characterization of the interaction
between accounting, analytical, and control
processes within the audit system. Its ap-
plication ensures a reduction in the risk of
accounting information misstatement, enhances
the ef fic iency of au dit procedures, and
improves the quality of management over the
production and export activities of agribusiness
enterprises.
Summarizing the research results, it is ap-
propriate to emphasize the fundamental diffe-
rences between the proposed model and existing
approaches to accounting and analytical support
for audit.
Thus, the proposed model possesses systemic
advantages over traditional approaches and ensu-
res a higher level of audit efficiency.
CONCLUSIONS
As a result of the conducted study, a holistic
theoretical and methodological basis of accounting
and analytical support for the audit of production
and export of crop products was formed, which
corresponds to the modern challenges of digital
transformation and growing uncertainty of the
external environment.
Unlike traditional approaches focused mainly
on the retrospective reflection of business
processes, the proposed approach ensures a
transition to a proactive audit model within which
the accounting and analytical system performs
the functions not only of recording, but also of
interpretation, forecasting, and prevention of
risks. This fundamentally changes the role of
audit-from an instrument of confirming reporting
Model element Content Tools and technologies Result for audit
Accounting
component
Generation of primary information on production
and export operations; reporting of biological
assets and foreign trade transactions.
ERP systems; accounting systems,
IFRS (IAS 41); automated
accounting.
Completeness and reliability of
accounting data.
Analytical
component
Processing, systematization, and interpretation of
data; identification of deviations and trends.
Big Data Analytics; economic analysis;
BI systems; machine learning.
Detection of anomalies, risk
forecasting.
Control (audit)
component
Risk identification, verification of information
reliability, formation of audit opinions.
Continuous Auditing, automated
control, audit procedures.
Improved audit quality and reporting
reliability.
Risk-oriented
approach
Identification and prioritization of critical
risks (currency, logistical, regulatory, market).
Risk analytics, ML models, scenario
analysis.
Risk mitigation and increased audit
efficiency.
Digital
technologies
Integration of digital tools into all system
elements.
AI, Big Data, ERP, automation, cloud
technologies.
Accelerated data processing and
increased accuracy.
Traceability Monitoring product movement from
production to export.
Blockchain (optional), GPS, logistics
systems.
Increased transparency and
verifiability of operations.
ESG
Component
Integration of environmental and social
indicators into the audit system.
ESG analytics, non-financial
reporting.
Expansion of audit scope and
enhanced investment attractiveness.
Table 2. Conceptual model of accounting and analytical support
for the audit of production and export of crop products
Source: developed by the author.
Criterion Traditional Models Proposed Model
System type Fragmentary Integrated digital system
Time horizon Retrospective Real-time
Audit function Control and verification Proactive analysis and forecasting
Data integration Limited Full (financial + non-financial)
Risk management Reactive Risk-oriented (preventive)
Technologies Traditional IT AI, Big Data, ML, ERP
Traceability Partial or absent Full (traceability, blockchain)
ESG component Absent Integrated
Auditor’s role Verifier / Controller Analyst and risk manager
Outcome Confirmation of reporting Support for management decisions
Table 3. Comparison of the traditional and the proposed
models of accounting and analytical support for audit
Source: developed by the author.
454
АГРОСВІТ № 10, 2026
ISSN 2306-6792Copyright © The Author(s). This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/).
to a mechanism for supporting managerial
decisions.
The key result of the study is the substantiation
of an integrated digitally oriented system of
accounting and analytical support that ensures
synchronization of financial and non-financial
data, increases the transparency of production and
export processes, and creates conditions for
continuous auditing. Practical implementation of
such an approach makes it possible to significantly
reduce information asymmetry, increase the
reliability of accounting data, and shorten time lags
in managerial decision-making.
The integration of digital technologies, in
particular tools of Big Data analytics, artificial
intelligence, and automated control, transforms
the audit methodology by ensuring the transition
to intellectualized procedures and increasing the
accuracy of risk identification. This creates
prerequisites for the formation of adaptive audit
systems capable of responding to dynamic changes
in the external environment.
It is important to substantiate the expediency
of integrating product traceability technologies
and ESG indicators into the accounting and
analytical support system, which expands the
boundaries of audit and makes it possible to carry
out a comprehensive assessment of enterprise
activities taking into account economic, environ-
mental, and social aspects. This increases the
investment attractiveness of agribusiness enter-
prises and their competitiveness in international
markets.
Thus, audit in the agricultural sector should
be based on the integration of digital tech-
nologies, analytical tools, and risk-oriented ma-
nagement. Its implementation ensures not only an
increase in the quality of audit conclusions, but
also the transformation of audit into a strategic
instrument for managing business efficiency and
sustainability.
Prospects for further research are related to
the development of intellectualized accounting and
analytical support systems capable of self-learning
and adaptation, as well as to deepening the inte-
gration of cyber-physical technologies, sensor
systems, and artificial intelligence algorithms into
the processes of audit and management of agri-
business enterprises.
Література:
1. Campos-Llerena, P. (2025). Accounting for
biological assets under IAS 41: Challenges and
implications for financial reporting in agriculture.
"Journal of Agricultural Accounting Research", 12
(1), 45—62.
2. Yuan, T., Zhang, X., & Chen, X. (2025).
Machine learning-based financial auditing: Risk
identification and anomaly detection. "Inter-
national Journal of Accounting Information
Systems", 58, 100745.
3. Wang, R., Liu, Y., & Zhao, K. (2025). Appli-
cation of large language models in financial
auditing: Opportunities and limitations. "Accoun-
ting Horizons", 39 (2), 89—108.
4. Stratopoulos, T., & Wang, V. (2025). Arti-
ficial intelligence and the future of accounting:
Transforming the accounting paradigm. "Journal
of Emerging Technologies in Accounting", 22 (1),
1—18.
5. Agriculture 5.0: Digital transformation of
agribusiness systems. (2026). "Computers and
Electronics in Agriculture", 210, 108012.
6. Food and Agriculture Organization of the
United Nations (FAO). (2024). "The State of
Agricultural Commodity Markets 2024". Rome:
FAO.
7. International Federation of Accountants
(IFAC). (2023). "Handbook of International
Quality Management, Auditing, Review, Other
Assurance, and Related Services Pronounce-
ments". New York: IFAC.
8. International Accounting Standards Board
(IASB). (2023). "IAS 41 Agriculture". London:
IFRS Foundation.
9. OECD. (2024). "Agricultural Policy Moni-
toring and Evaluation 2024". Paris: OECD Pub-
lishing.
10. World Bank. (2024). "Global Economic
Prospects: Commodity Markets Outlook".
Washington, DC: World Bank.
11. Жигілій, О. В. (2025). Розвиток аграрно-
го експорту України в умовах глобальних вик-
ликів. "Економіка АПК", 5, 23—31.
12. Бутинець, Ф. Ф. (2022). "Бухгалтерський
облік в аграрному секторі". Житомир: ПП
"Рута".
13. Сопко, В. В. (2023). "Аудит: теорія і прак-
тика". Київ: КНЕУ.
14. Голов, С. Ф. (2023). "Бухгалтерський
облік та фінансова звітність за міжнародними
стандартами". Київ: Лібра.
15. KPMG. (2024). "Digital transformation in
agribusiness: Audit and risk perspectives". Ret-
rieved from https://kpmg.com.
16. Deloitte. (2025). "AI in audit: Transforming
risk assessment and assurance". Retrieved from
https://deloitte.com.
17. European Commission. (2024). "Sustainable
agriculture and ESG reporting standards".
Brussels: EC.
АГРОСВІТ № 10, 2026
455
ISSN 2306-6792 Copyright © The Author(s). This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/).
18. European Commission. (2024). *Sustai-
nable agriculture and ESG reporting standards*.
Brussels: EC.
19. Porter, M. E., & Heppelmann, J. E. (2023).
How smart, connected products are transforming
competition. *Harvard Business Review*, 101 (3),
64—88.
References:
1. Campos-Llerena, P. (2025), "Accounting for
biological assets under IAS 41: Challenges and
implications for financial reporting in agriculture",
Journal of Agricultural Accounting Research,
Computers and Electronics in Agriculture 12(1),
pp. 45—62.
2. Yuan, T., Zhang, X., & Chen, X. (2025), "Ma-
chine learning-based financial auditing: Risk
identification and anomaly detection", Inter-
national Journal of Accounting Information
Systems, Computers and Electronics in Agri-
culture, vol. 58, 100745.
3. Wang, R., Liu, Y., & Zhao, K. (2025),
"Application of large language models in financial
auditing: Opportunities and limitations", Accoun-
ting Horizons, Computers and Electronics in
Agriculture, vol. 39 (2), pp. 89—108.
4. Stratopoulos, T., & Wang, V. (2025), "Arti-
ficial intelligence and the future of accounting:
Transforming the accounting paradigm",Journal of
Emerging Technologies in Accounting, Computers
and Electronics in Agriculture, vol. 22 (1), pp. 1—
18.
5. Computers and Electronics in Agriculture
(2026), "Agriculture 5.0: Digital transformation of
agribusiness systems", Computers and Electronics
in Agriculture, vol. 210, 108012.
6. Food and Agriculture Organization of the
United Nations (FAO). (2024), The State of Agri-
cultural Commodity Markets 2024, FAO, Rome.
7. International Federation of Accountants
(IFAC). (2023) Handbook of International Quality
Management, Auditing, Review, Other Assurance,
and Related Services Pronouncements, IFAC, New
York, USA.
8. International Accounting Standards Board
(IASB). (2023), IAS 41 Agriculture, IFRS Foun-
dation, London, UK.
9. OECD. (2024), Agricultural Policy Moni-
toring and Evaluation 2024, OECD Publishing,
Paris.
10. World Bank. (2024), Global Economic
Prospects: Commodity Markets Outlook, World
Bank, Washington, DC.
11. Zhyhilij, O. V. (2025), "Development of
Ukrainian agricultural exports in the face of global
challenges", Ekonomika APK, vol. 5, pp. 23—31.
12. Butynets', F. F. (2022), Bukhhalters'kyj
oblik v ahrarnomu sektori [Accounting in the
agricultural sector], Ruta, Zhytomyr, Ukraine.
13. Sopko, V. V. (2023), Audyt: teoriia i prak-
tyka [Audit: theory and practice], KNEU, Kyiv,
Ukraine.
14. Holov, S. F. (2023), Bukhhalters'kyj oblik
ta finansova zvitnist' za mizhnarodnymy standar-
tamy [Accounting and financial reporting
according to international standards], Libra, Kyiv,
Ukraine.
15. KPMG. (2024), "Digital transformation in
agribusiness: Audit and risk perspectives",
available at: https://kpmg.com (Accessed 05 May
2026).
16. Deloitte. (2025), "AI in audit: Transforming
risk assessment and assurance", available at: https:/
/deloitte.com (Accessed 05 May 2026).
17. European Commission. (2024), Sustainable
agriculture and ESG reporting standards, EC,
Brussels.
18. European Commission. (2024), Sustainable
agriculture and ESG reporting standards, EC,
Brussels.
19. Porter, M. E., & Heppelmann, J. E. (2023),
"How smart, connected products are transforming
competition", Harvard Business Review, vol. 101
(3), pp. 64—88.
Отримано редакцією журналу / Received: 08.05.26
Прорецензовано / Revised: 15.05.26
Дата публікації / Published: 21.05.26
|
| id | www_nayka_com_ua-article-10348 |
| institution | Agrosvit |
| keywords_txt_mv | keywords |
| language | Ukrainian |
| last_indexed | 2026-06-09T01:02:15Z |
| publishDate | 2026 |
| publisher | ДКС Центр |
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| resource_txt_mv | wwwnaykacomua/a4/38fa3fac0c56fe4675ebded1fd52dfa4.pdf |
| spelling | www_nayka_com_ua-article-103482026-06-08T08:39:19Z ACCOUNTING AND ANALYTICAL SUPPORT FOR THE AUDIT OF PRODUCTION AND EXPORT OF CROP PRODUCTS AT AN AGRIBUSINESS ENTERPRISES ОБЛІКОВО-АНАЛІТИЧНЕ ЗАБЕЗПЕЧЕННЯ АУДИТУ ВИРОБНИЦТВА ТА ЕКСПОРТУ ПРОДУКЦІЇ РОСЛИННИЦТВА ПІДПРИЄМСТВАМИ АГРОБІЗНЕСУ Копотієнко, Т. Ю. Шелестянка, Н. І. ДКС Центр 2026-05-21 Article Article application/pdf https://www.nayka.com.ua/index.php/agrosvit/article/view/10348 10.32702/2306-6792.2026.10.448 Журнал "Агросвіт"; № 10 (2026): АГРОСВІТ; 448-455 Agrosvit; No. 10 (2026): AGROSVIT; 448-455 2306-6792 10.32702/2306-6792.2026.10 uk https://www.nayka.com.ua/index.php/agrosvit/article/view/10348/10491 Авторське право (c) 2026 Журнал "Агросвіт" |
| spellingShingle | Копотієнко, Т. Ю. Шелестянка, Н. І. ОБЛІКОВО-АНАЛІТИЧНЕ ЗАБЕЗПЕЧЕННЯ АУДИТУ ВИРОБНИЦТВА ТА ЕКСПОРТУ ПРОДУКЦІЇ РОСЛИННИЦТВА ПІДПРИЄМСТВАМИ АГРОБІЗНЕСУ |
| title | ОБЛІКОВО-АНАЛІТИЧНЕ ЗАБЕЗПЕЧЕННЯ АУДИТУ ВИРОБНИЦТВА ТА ЕКСПОРТУ ПРОДУКЦІЇ РОСЛИННИЦТВА ПІДПРИЄМСТВАМИ АГРОБІЗНЕСУ |
| title_alt | ACCOUNTING AND ANALYTICAL SUPPORT FOR THE AUDIT OF PRODUCTION AND EXPORT OF CROP PRODUCTS AT AN AGRIBUSINESS ENTERPRISES |
| title_full | ОБЛІКОВО-АНАЛІТИЧНЕ ЗАБЕЗПЕЧЕННЯ АУДИТУ ВИРОБНИЦТВА ТА ЕКСПОРТУ ПРОДУКЦІЇ РОСЛИННИЦТВА ПІДПРИЄМСТВАМИ АГРОБІЗНЕСУ |
| title_fullStr | ОБЛІКОВО-АНАЛІТИЧНЕ ЗАБЕЗПЕЧЕННЯ АУДИТУ ВИРОБНИЦТВА ТА ЕКСПОРТУ ПРОДУКЦІЇ РОСЛИННИЦТВА ПІДПРИЄМСТВАМИ АГРОБІЗНЕСУ |
| title_full_unstemmed | ОБЛІКОВО-АНАЛІТИЧНЕ ЗАБЕЗПЕЧЕННЯ АУДИТУ ВИРОБНИЦТВА ТА ЕКСПОРТУ ПРОДУКЦІЇ РОСЛИННИЦТВА ПІДПРИЄМСТВАМИ АГРОБІЗНЕСУ |
| title_short | ОБЛІКОВО-АНАЛІТИЧНЕ ЗАБЕЗПЕЧЕННЯ АУДИТУ ВИРОБНИЦТВА ТА ЕКСПОРТУ ПРОДУКЦІЇ РОСЛИННИЦТВА ПІДПРИЄМСТВАМИ АГРОБІЗНЕСУ |
| title_sort | обліково-аналітичне забезпечення аудиту виробництва та експорту продукції рослинництва підприємствами агробізнесу |
| url | https://www.nayka.com.ua/index.php/agrosvit/article/view/10348 |
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