Jou nal o Theo e ical and Applied In o ma ion Technology
31s May 2025. Vol.103. No.10
© Li le Lion Scien i ic
ISSN: 1992-8645 www.ja i .o g E-ISSN: 1817-3195
4149
BLOCKCHAIN TECHNOLOGY AND ITS IMPACT ON
FINANCIAL REPORTING IN THE DIGITAL ACCOUNTING
ERA
AHMAD ALNAIMAT MOHAMMAD1, OLEKSANDR CHUMAK2, MYKYTA ARTEMCHUK3,
ALONA KHMELIUK4, SVITLANA SKRYPNYK5
1PhD in Economic Sciences / Accoun ing, Analysis and Audi , Assis an P o esso , Depa men o
Accoun ing, Facul y o Business, Alzay oonah Uni e si y o Jo dan, Amman, Jo dan
2Doc o o Legal Sciences, P o esso o he Depa men o Na ional Secu i y, Ins i u e o Secu i y,
In e egional Academy o Pe sonnel Managemen , Kyi , Uk aine
3Candida e o Philosophical Sciences, Chie P oduc O ice , P om.ua, Kyi , Uk aine
4Candida e o Economics Sciences, Associa e P o esso , Depa men o Finance and Accoun ing, Dnip o
S a e Technical Uni e si y, Dnip o, Uk aine
5Doc o o Economic Sciences, Associa e P o esso , P o esso o he Depa men o En ep eneu ship,
Accoun ing and Finance, Facul y o Economics, Khe son S a e Ag a ian and Economic Uni e si y,
K opy ny skyi, Uk aine
E-mail: [email protected], 2da ynap [email protected], 3m.a [email protected],
[email protected], 5107s e [email protected]
ABSTRACT
The s udy is ele an , as blockchain echnologies ans o m inancial epo ing, inc easing i s anspa ency,
eliabili y, and da a p ocessing speed, educing cos s and minimizing isks, which equi es u he analysis.
Howe e , despi e nume ous s udies on blockchain applica ions, a knowledge gap exis s in unde s anding i s
comp ehensi e impac on inancial epo ing p ocesses and he de elopmen o in eg a ion models wi h o he
digi al echnologies. The aim o he s udy is o de e mine he impac o blockchain echnologies on he
p ocesses o p epa ing and submi ing inancial s a emen s, as well as de e mining he p ospec s o using
his echnology in accoun ing in he digi al age. The esea ch employed he ollowing me hods: con en
analysis o mode n blockchain sys ems, compa a i e analysis o inancial indica o s o companies ha use
blockchain, as well as economic and s a is ical modelling. The impac o blockchain echnologies was
assessed h ough quan i a i e analysis, including desc ip i e s a is ics, analysis o a iance (ANOVA),
co ela ion analysis (Pea son and Spea man coe icien s), eg ession analysis, clus e analysis and hypo hesis
es ing ( - es , Mann-Whi ney U- es ). The calcula ions we e pe o med using SPSS, S a a, and Py hon
so wa e (Pandas, S a smodels, Sciki -lea n). The esul s con i m ha he implemen a ion o blockchain
echnologies inc eases he e iciency o inancial epo ing, educing ope a ing cos s by 15–20% and educing
audi cos s by 25–30%. Sma con ac s minimize e o s by 18%, and he a e age p ocessing ime o
inancial ansac ions dec eased om 48 o 5 hou s. In he inancial sec o , cos s we e educed by 30%, and
ansac ion p ocessing ime by 85%. The academic no el y o he s udy lies in he comp ehensi e analysis o
he applica ion o blockchain echnologies o inc ease he anspa ency and eliabili y o inancial epo ing
in a global con ex , as well as he c ea ion o new knowledge h ough s a is ical analysis and p ac ical
assessmen o blockchain's e ec i eness. The p ospec s o u he esea ch include he de elopmen o
models o in eg a ing blockchain wi h o he digi al echnologies, such as a i icial in elligence (AI) and Big
Da a, as well as assessing he long- e m economic consequences o using blockchain in he inancial sec o .
Keywo ds: Blockchain, Financial Repo ing, Digi al Accoun ing, Sma Con ac s, T anspa ency,
In e na ional S anda ds, Au oma ion.
1. INTRODUCTION
Blockchain is ans o ming inancial
epo ing in he digi al age, p o iding anspa ency,
secu i y, and au oma ion o p ocesses. I s
implemen a ion educes he isks o aud, elimina es
he limi a ions o cen alized sys ems, and p o ides
ope a ional access o eliable da a. In he global
inancial en i onmen , blockchain p omo es he
in eg a ion o digi al pla o ms, con inuous audi ing
Jou nal o Theo e ical and Applied In o ma ion Technology
31s May 2025. Vol.103. No.10
© Li le Lion Scien i ic
ISSN: 1992-8645 www.ja i .o g E-ISSN: 1817-3195
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and compliance wi h in e na ional s anda ds. The
in e na ional aspec o i s applica ion is especially
ele an , as coun ies use di e en app oaches o
in eg a ing his echnology in o accoun ing sys ems.
Mapping p e ious s udies on blockchain's
impac on inancial epo ing e eals bo h p og ess
and limi a ions. Rawashdeh [1] emphasized b idging
he us gap h ough blockchain and sma con ac s,
while Siyue Qin [2] ocused on heo e ical
amewo ks wi hou p esen ing empi ical indings.
Fahdil e al. [3] discussed he ans o ma i e
po en ial o blockchain o audi ing bu did no
p o ide insigh s in o i s p ac ical implemen a ion.
Bellucci e al. [4] conduc ed a li e a u e e iew, bu
hei analysis was limi ed o a heo e ical
pe spec i e, lacking p ac ical alida ion. This s udy
aims o add ess hese gaps by p o iding a
comp ehensi e empi ical analysis o blockchain's
e ec i eness in inancial epo ing, including cos
educ ion, anspa ency imp o emen , and da a
accu acy enhancemen .
Howe e , despi e he inc easing adop ion o
blockchain echnology in inancial epo ing, he e
emains a signi ican knowledge gap ega ding i s
comp ehensi e impac on inancial epo ing
p ocesses and he de elopmen o in eg a ion models
wi h o he digi al echnologies. Mo eo e , he lack o
s anda dized amewo ks o implemen ing
blockchain in a ious inancial sys ems globally
complica es he p ocess o achie ing consis en and
eliable epo ing. The e o e, u he esea ch is
essen ial o b idge hese gaps and p o ide p ac ical
ecommenda ions o enhancing blockchain's
e ec i eness in inancial epo ing.
The aim o he esea ch is o in es iga e he
impac o blockchain echnology on he
ans o ma ion o inancial epo ing in he con ex
o digi al accoun ing and o de e mine he p ospec s
o i s use in an in e na ional con ex .
Empi ical objec i es:
1. S udy he main mechanisms o
implemen ing blockchain echnologies in inancial
epo ing and hei impac on he anspa ency and
eliabili y o da a.
2. Analyse he p ac ices o using blockchain
in mode n companies.
3. P o ide ecommenda ions on adap ing
accoun ing sys ems o he use o blockchain
solu ions o ensu ing compliance wi h in e na ional
s anda ds and inc ease he e iciency o business
p ocesses.
2. LITERATURE REVIEW
A li e a u e e iew demons a es bo h he
bene i s and limi a ions o blockchain echnology in
inancial epo ing. Rawashdeh [1] emphasizes
anspa ency h ough sma con ac s bu does no
add ess hei in eg a ion wi h digi al pla o ms, while
Siyue Qin [2] ocuses on au oma ion wi hou
p o iding empi ical e idence. Fahdil e al. [3]
examines he eliabili y o inancial da a, and
Bellucci e al. [4] examines con inuous audi ing, bu
bo h app oaches ail o add ess he egula o y
challenges analysed by Smi h and Cas onguay [5].
Amalia and P a olo [6] p opose new
concep s o accoun ing sys ems, bu igno e he la es
echnologies ha c i icize Dyball and See ham aju
[7], p o ing he e ec i eness o blockchain in
educing cos s, bu no add essing secu i y issues.
Fay ishenko e al. [8] and P okopenko e al. [9]
in es iga e blockchain in digi al ma ke ing and
banking, bu hei indings ha e limi ed applica ion.
Gai e al. [10] analyse global p ospec s wi hou he
in e disciplina y app oach used by Sheela e al. [11]
and wi hou empi ical suppo .
Sil a e al. [12] se an agenda o u he
esea ch, wi hou aking in o accoun he dynamics
o he egula o y en i onmen , which is emphasized
by Li and Juma'h [13]. Thies e al. [14] conside
economic bene i s, bu only om a echnical
pe spec i e, and Sha ma e al. [15] analyse
blockchain adop ion wi hou empi ical da a. Su yan i
e al. [16] in es iga e aud con ol wi hou
conside ing economic aspec s. S a opoulos e al.
[17] ocus on he ini ial s ages o implemen a ion,
c i icizing Ho i e al. [18] who in es iga e IT con ols
in p i a e blockchain bu do no conside in eg a ion
wi h en e p ise esou ce planning (ERP) sys ems.
Re iewing p e ious s udies on he opic
e eals a agmen ed app oach owa ds assessing
blockchain’s impac on inancial epo ing. While
some s udies ocus solely on au oma ion and da a
accu acy, o he s add ess anspa ency and cos
educ ion. Howe e , ew a emp s ha e been made o
in eg a e hese aspec s in o a comp ehensi e
amewo k ha would es ablish blockchain's o e all
e iciency. This esea ch aims o ill ha gap by
combining s a is ical analysis, in e disciplina y
in eg a ion, and empi ical e idence o c ea e a
holis ic model o e alua ing blockchain's impac .
The indings o his wo k di e in mo i a ion by
add essing he gaps iden i ied in p e ious s udies and
p o iding p ac ical ecommenda ions o imp o ing
blockchain implemen a ion in inancial sys ems.
O e all, he li e a u e suppo s he po en ial
o blockchain o enhance anspa ency, secu i y, and
Jou nal o Theo e ical and Applied In o ma ion Technology
31s May 2025. Vol.103. No.10
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ISSN: 1992-8645 www.ja i .o g E-ISSN: 1817-3195
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au oma ion o inancial epo ing, bu mos s udies
a e ei he heo e ical o limi ed in scope, indica ing
he need o u he empi ical and in e disciplina y
esea ch.
3. METHODOLOGY
3.1. Resea ch Design
The s udy consis ed o h ee s ages aimed a
analysing he impac o blockchain echnology on
inancial epo ing in digi al accoun ing.
The i s s age in ol ed a heo e ical
analysis o he li e a u e, in pa icula app oaches o
implemen ing blockchain echnologies in inancial
epo ing. Pa icula a en ion was paid o issues o
anspa ency, audi au oma ion, and he use o sma
con ac s.
The second s age o he s udy in ol ed
collec ing da a on he inancial indica o s o
companies ha had implemen ed blockchain in hei
accoun ing sys ems. The in o ma ion was ob ained
om open inancial epo s o companies ( epo s
unde he In e na ional Financial Repo ing
s anda ds (IFRS), Secu i ies and Exchange
Commission (SEC) Filings), academic esea ch, as
well as s a is ical pla o ms, in pa icula S a is a,
Bloombe g, Wo ld Bank Open Da a, and na ional
inancial epo ing egis e s. The analysis co e ed
he ollowing key inancial indica o s: ope a ing
expenses, ansac ion p ocessing speed, inancial
da a accu acy, changes in audi cos s, and he le el
o inancial anspa ency. The ep esen a i eness o
he sample was ensu ed by selec ing 50 companies
om i e key sec o s: inance, logis ics, ene gy,
echnology, and e ail. This app oach assessed he
speci ics o implemen ing blockchain solu ions in
di e en economic con ex s and hei impac on
inancial epo ing. The analysis co e ed he pe iod
o 5 yea s (2020–2024), which allowed us o assess
bo h he sho - e m and long- e m e ec s o
blockchain implemen a ion.
The hi d s age o he s udy was quan i a i e
analysis o assess he impac o blockchain
echnologies on companies’ inancial pe o mance.
Desc ip i e s a is ics we e used o assess he
dis ibu ion o inancial indica o s, ANOVA – o
compa e mean alues ac oss indus ies, and
co ela ion analysis (Pea son and Spea man
coe icien s) o de e mine he ela ionship be ween
digi aliza ion and inancial indica o s.
Reg ession analysis assessed he impac o
blockchain on educing audi cos s, epo ing
anspa ency, and ansac ion speed. Clus e analysis
o iden i ied ypical scena ios o he echnology’s
impac on business models in di e en indus ies.
The hypo hesis was es ed using he - es and Mann-
Whi ney U- es o assess di e ences be ween
companies ha implemen ed blockchain and he
con ol g oup (CG). The calcula ions we e
pe o med in SPSS, S a a, and Py hon (Pandas,
S a smodels, Sciki -lea n), which ensu ed he
accu acy o he analysis and ook in o accoun
indus y speci ics.
3.2. Me hods
The s udy employed h ee main me hods:
1. Con en analysis. The con en analysis
was used o s udy mode n blockchain sys ems and
hei unc ions in he con ex o inancial epo ing.
The analysis co e ed he assessmen o he
anspa ency o egis e s, he e ec i eness o sma
con ac s, and in eg a ion wi h au oma ed audi
sys ems. In pa icula , such sys ems as E he eum and
Hype ledge we e s udied, hei impac on he speed
o ansac ion p ocessing and da a secu i y.
2. Compa a i e analysis. A compa a i e
analysis o he inancial indica o s o companies was
ca ied ou in o de o de e mine he impac o
blockchain echnologies on economic esul s, aking
in o accoun indus y speci ics. The s udy used
inancial epo s o 50 companies om di e en
sec o s o he economy ( inance, logis ics, ene gy,
echnology, and e ail). The compa ison was ca ied
ou wi hin each indus y, which made i possible o
assess he e ec i eness o blockchain in speci ic
business con ex s wi hou di iding he sample in o
sepa a e independen g oups. The analysis used
a e age alues o audi cos s, ansac ion p ocessing
speed, and le el o compliance wi h in e na ional
s anda ds. The o mula 1 o calcula ing he
pe cen age impac o blockchain is:
ΔP = ( )
 100% (1)
whe e:
– ΔP – change in he indica o (%),
– Pblockchain –an indica o o companies
using blockchain,
– Pcon ol – an indica o o he CG
companies.
Fo example, companies ha implemen ed
blockchain educed audi cos s by 15%, while
ansac ion p ocessing speed inc eased by 20%.
1. Economic and s a is ical modelling. A
mul i a ia e eg ession was used o assess he impac
o blockchain on inancial epo ing. The dependen
a iable was da a accu acy (Y), and he independen
a iables we e he le el o au oma ion (X1), he
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31s May 2025. Vol.103. No.10
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4152
numbe o ansac ions (X2), and he le el o sys em
anspa ency (X3). The model has he o m (Fo mula
2):
Y=β0+β1X1+β2X2+β3X3+ε (2)
whe e:
– Y – da a accu acy,
– X1,X2, X3 – independen a iables,
– β0 – cons an ,
– β1,β2,β3 – eg ession coe icien s,
– ε – e o .
The esul s showed ha he
implemen a ion o blockchain explains up o 85%
o he changes in he accu acy o inancial da a.
3.3. Sample
Sampling was a key elemen among he
esea ch me hods aimed a analysing he impac o
blockchain echnologies on inancial epo ing. A
o al o 50 companies om he inancial, logis ics,
ene gy, echnology and e ail sec o s we e selec ed
o he pu pose o aking in o accoun he impo ance
o hese sec o s in digi al ans o ma ion. The
ini ially conside ed sample included 200 po en ial
companies iden i ied acco ding o global inno a ion
ankings (Wo ld Economic Fo um, OECD Digi al
Economy Ou look, McKinsey Blockchain Repo ),
public inancial epo ing (In e na ional Financial
Repo ing S anda ds, Financial S abili y Boa d) and
indus y analy ical e iews (Ga ne Blockchain
Ma ke Repo , PwC Global Fin ech Repo ).
S a i ied andom selec ion was based on he
ollowing c i e ia: annual e enue o companies
om $10 million o $500 million, numbe o
employees om 250 o 5,000 people,
implemen a ion o blockchain solu ions o a leas
wo yea s, ope a ional ac i i y o mo e han 50
housand ansac ions pe yea and he le el o
au oma ion o inancial p ocesses o a leas 60%.
P io i y was gi en o companies wi h public inancial
epo s o he las i e yea s, as well as hose whose
ac i i ies we e eco ded in in e na ional pla o ms
(Bloombe g, S a is a, Wo ld Bank Open Da a).
The sample co e ed he sec o s ha s and o
bene i he mos om blockchain adop ion:
– he inancial sec o , which is ac i ely
using blockchain in digi al paymen s, ansac ion
e i ica ion, and sma con ac s;
– logis ics, whe e blockchain is used o
ack supply chains, imp o e ansac ion accu acy,
and minimize aud;
– ene gy, which is in eg a ing he
echnology o au oma e se lemen s and ade
ansac ions;
– he echnology sec o , which is using
blockchain o da a p o ec ion, digi al iden i ica ion,
and inancial se lemen s;
– e ail, which is imp o ing in en o y
managemen , supply anspa ency, and consume
us .
The esea ch da a was ob ained om
co po a e annual epo s (IFRS Repo s, SEC
Filings), indus y analy ical publica ions (Ga ne
Blockchain Ma ke Repo , PwC Global Fin ech
Repo ), and in e na ional digi aliza ion ankings
(Wo ld Economic Fo um, Financial S abili y Boa d).
This app oach ensu ed he ep esen a i eness o he
sample, allowing o a comp ehensi e assessmen o
he eal impac o blockchain echnologies on
inancial epo ing in a ious sec o s o he economy.
The da a we e analysed in s ages: he
companies we e di ided by indus y, a e which a
sepa a e analysis o each g oup was ca ied ou . The
impac o blockchain was assessed by calcula ing
mean and median inancial indica o s o elimina e
dis o ions caused by di e en le els o company
inancing. The s udy also included a case s udy
app oach wi h a selec ion o e e ence companies o
a de ailed analysis o blockchain implemen a ion.
S a is ical assessmen o he signi icance o
di e ences be ween g oups was ca ied ou using
ANOVA. The co ela ions be ween he le el o
digi aliza ion and inancial indica o s we e assessed
using Pea son and Spea man coe icien s. The
calcula ions we e pe o med in SPSS, S a a, and
Py hon (Pandas, S a smodels, Sciki -lea n) o he
pu pose o assessing he impac o blockchain bo h
a he mac o le el (gene al ends) and a he mic o
le el (analysis o indi idual companies).
Table 1 con ains he cha ac e is ics o he
selec ed companies: indus y, du a ion o blockchain
implemen a ion, change in ope a ing cos s, and le el
o au oma ion. Du a ion o implemen a ion indica es
he numbe o yea s o using he echnology. Change
in ope a ing cos s (%) e lec s he educ ion
(nega i e alues) o inc ease in cos s a e
blockchain implemen a ion. The le el o au oma ion
is assessed quali a i ely (low, medium, high) and
shows he in eg a ion o blockchain in o inancial
and accoun ing p ocesses.
Table 1: Cha ac e is ics o he selec ed companies
Jou nal o Theo e ical and Applied In o ma ion Technology
31s May 2025. Vol.103. No.10
© Li le Lion Scien i ic
ISSN: 1992-8645 www.ja i .o g E-ISSN: 1817-3195
4153
G oup
Sec o
Blockchain
implemen a ion
Ope a ing cos s
(Change, %)
Au oma ion
le el
G oup
1
Finance 2
yea s
-15% High
G oup
2
Technology 2
yea s
-10% High
G oup
3
Re ail 2
yea s
-8% Medium
G oup
4
Ene gy 2
yea s
0% Low
G oup
5
Logis ics 2
yea s
5% Low
Sou ce: c ea ed by he au ho based on he
company da a and independen esea ch [19]-[24].
The da a p ocessing and analysis we e
ca ied ou using such ools as Mic oso Excel o
quan i a i e da a analysis (changes in cos s,
ansac ion speed), Tableau o isualiza ion o
changes in inancial indica o s, and Py hon o
mul i a ia e analysis. The use o a comp ehensi e
app oach o company selec ion and he use o
mode n analy ical ools ensu ed he
ep esen a i eness o he esul s, allowing o assess
he impac o blockchain on key aspec s o inancial
epo ing.
4. RESULTS
The implemen a ion o blockchain
echnology in inancial epo ing has inc eased he
accu acy, anspa ency, and speed o ansac ion
p ocessing, educing ope a ional cos s by 15–20%
h ough au oma ion and educed audi cos s. In he
inancial sec o , sma con ac s ha e educed
ansac ion e i ica ion cos s by 25%, speeding up
p ocesses. The echnology sec o has minimized
human e o s, which has imp o ed he e iciency o
inancial ansac ions. The a e age ansac ion
p ocessing ime has dec eased om se e al days o
minu es, especially in in e na ional paymen s.
Inc eased anspa ency o ansac ions has
s eng hened he us o egula o s, in es o s and
consume s. In e ail, blockchain has imp o ed
supply chain managemen , educing he isks o
aud and e o s in logis ics.
The analysis o he dynamics o inancial
indica o s o companies ha ha e implemen ed
blockchain echnologies demons a es signi ican
changes in cos s, da a accu acy, and ansac ion
p ocessing speed o 2020–2024.
Table 2 p esen s he dynamics o inancial
indica o s o companies ha ha e implemen ed
blockchain in 2020–2024. Ope a ing expenses (%
change) show hei educ ion due o he au oma ion
o inancial p ocesses. Da a accu acy (%
imp o emen ) e lec s he inc ease in he eliabili y
o inancial in o ma ion h ough decen alized
egis ies and sma con ac s. A e age ansac ion
ime (hou s) demons a es he accele a ion o
inancial ansac ions, which educes paymen delays
and inc eases e iciency.
Table 2: Dynamics o inancial indica o s in
companies ha ha e implemen ed blockchain
(2020–2024)
Yea
T ansac ion
Cos s (%
Change)
Da a Accu acy
(%
Imp o emen )
A e age
T ansac ion
Time (Hou s)
2020 -5 10 48
2021 -7 14 30
2022 -10 18 12
2023 -15 22 7
2024 -20 25 5
Sou ce: c ea ed by he au ho based on he
company da a and independen esea ch [19]-[24].
The s udy ound ha blockchain in eg a ion
educed ope a ing cos s by 15–20% h ough audi
au oma ion and s eamlined documen low. Sma
con ac s and au oma ed epo ing educed audi
cos s by 25–30%, and digi al egis e s educed
adminis a i e cos s. The e o s caused by manual
da a p ocessing dec eased by 18%, and he accu acy
o inancial in o ma ion inc eased by 20–25%
because o he a ailabili y o eal- ime ansac ions.
T ansac ion p ocessing imes dec eased om 48–72
hou s o 5–10 minu es, in e na ional ans e s – by
90%, and e ail o de p ocessing was accele a ed by
70%, he eby inc easing cus ome sa is ac ion.
Figu e 1 shows he educ ion in ansac ion
p ocessing imes o companies ha implemen ed
blockchain compa ed o adi ional sys ems. The
g aph shows a apid educ ion in ime be ween 2022
and 2024.

Jou nal o Theo e ical and Applied In o ma ion Technology
31s May 2025. Vol.103. No.10
© Li le Lion Scien i ic
ISSN: 1992-8645 www.ja i .o g E-ISSN: 1817-3195
4154
Figu e 1: Dynamics o ansac ion p ocessing ime (2020–2024)
Sou ce: c ea ed by he au ho based on he company da a and independen esea ch [19]-[24].
Figu e 1 shows ha ansac ion p ocessing
ime o companies ha implemen ed blockchain
dec eased om 48 o 5 hou s hanks o au oma ion
and sma con ac s o 2020-2024. In adi ional
sys ems, his igu e dec eased om only 72 o 62
hou s due o eliance on manual p ocedu es. This
con i ms he e ec i eness o blockchain in
op imizing inancial p ocesses. The echnology has
also educed audi cos s by 30% and accele a ed he
e i ica ion o annual epo s om 15 days o 48
hou s. In he banking sec o , i inc eased he le el o
inancial isk de ec ion, while i educed ope a ing
cos s by 22% and inc eased epo ing accu acy by
18% in he echnology sec o . In e ail, blockchain
educed deli e y e i ica ion ime by 40% and
educed logis ics e o s by 25%, s eng hening
consume us .
Table 3 shows he impac o blockchain
echnology on he inancial, echnology, logis ics,
ene gy and e ail sec o s. Cos educ ion (%) e lec s
he educ ion in ope a ing cos s h ough au oma ion
and op imiza ion o audi s. P ocessing ime educ ion
(%) demons a es he accele a ion o inancial
ansac ions hanks o sma con ac s and
decen alized ledge s. Accu acy imp o emen (%)
indica es he educ ion o epo ing e o s and he
imp o emen o inancial da a quali y due o
anspa ency and eal- ime access.
Table 3: Compa ison o he impac o blockchain on
key sec o s
Sec o
Cos educ ion
(%)
P ocessing
ime educ ion
(%)
Accu acy
imp o emen
(%)
Finance 30 85 25
Technology 22 78 18
Logis ics 27 60 22
Ene gy 18 55 15
Re ail 25 40 20
Sou ce: c ea ed by he au ho based on he
company da a and independen esea ch [19]-[24].
The inancial sec o bene i ed he mos
om blockchain, educing cos s by 30% and
ansac ion p ocessing ime by 85% h ough audi
au oma ion. In he echnology sec o , cos s dec eased
by 22% and epo ing accu acy inc eased by 18%
h ough eal- ime da a in eg a ion. In e ail,
blockchain accele a ed supply chain e i ica ion by
40% and inc eased da a accu acy by 20%, imp o ing
supply chain con ol. In logis ics, cos s ha e
dec eased by 27% and ansac ion p ocessing ime by
60%, con ibu ing o be e ma ke coo dina ion. In
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ene gy, cos s ha e dec eased by 18% and inancial
da a accu acy has inc eased by 15% h ough
epo ing au oma ion. O e all, blockchain p o ed i s
e ec i eness by educing cos s, accele a ing
inancial p ocesses, and inc easing accoun ing
accu acy, which s eng hens companies’
compe i i eness.
Figu e 2 shows he le el o educ ion in
ansac ion p ocessing ime ac oss indus ies due o
blockchain implemen a ion. The g aph shows he
g ea es bene i s in he inancial sec o , whe e
p ocessing ime dec eased om 15 days o 48 hou s.
Figu e 2: Reduc ion in ansac ion p ocessing ime by sec o
Sou ce: de eloped by he au ho based on he esea ch da a o 2020–2024
Figu e 2 shows he educ ion in ansac ion
p ocessing imes ac oss key indus ies in 2024. The
bigges impac is obse ed in he inancial sec o ,
whe e he a e age ime d opped om 15 days o 48
hou s due o au oma ion and sma con ac s. In
echnology, i dec eased by 78%, in logis ics – by
60%, in ene gy –by 55%, and in e ail, e i ica ion o
deli e ies has accele a ed by 40%. O e all,
blockchain has p o en i s e ec i
eness in accele a ing inancial p ocesses,
educing delays, and inc easing us be ween ma ke
pa icipan s.
Table 4 p esen s economic modelling o he
impac o blockchain on inancial epo ing ac oss
indus ies, es ima ing cos educ ions, inc eased
anspa ency, da a accu acy, and inancial
managemen e iciency. Cos educ ion (%) shows
he educ ion in ope a ing cos s h ough au oma ion
and audi op imiza ion. Accu acy imp o emen (%)
e lec s he educ ion in e o s and imp o ed
epo ing eliabili y. The educ ion in p ocessing
ime (%) demons a es he accele a ion o inancial
ansac ions and he op imiza ion o calcula ions.
The modelling e iciency (%) in eg a es hese
indica o s, assessing he o e all impac o blockchain
on he companies’ inancial ac i i ies.
Table 4: E ec s o economic modelling o he
implemen a ion o blockchain echnologies
Ca ego y
Finance
Technolog
y
Logis ics
Ene gy
Re ail
Cos educ ion (%) 36 28 30 26 25
Da a accu acy
imp o emen (%)
40 35 33 31 30
P ocessing ime
educ ion (%)
87 80 70 68 65
Modelling e iciency
(%)
92 85 82 80 78
Sou ce: c ea ed by he au ho based on he
company da a and independen esea ch [19]-[24].
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Finance Technology Logis ics Ene gy Re ail
P ocessing ime be o e implemen a ion (days)
P ocessing ime a e implemen a ion (days)
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The inancial sec o bene i ed he mos
om blockchain, educing cos s by 36% and
inc easing he accu acy o inancial da a by 40%,
which educed ope a ional isks and imp o ed he
quali y o epo ing. Audi cos s in he inancial
sec o dec eased om $500,000 o $320,000 pe yea
due o he au oma ion o audi s and he use o sma
con ac s. Logis ics educed ansac ion p ocessing
ime by 70%, accele a ing he coo dina ion o
deli e ies. In he ene gy sec o , blockchain inc eased
accoun ing accu acy by 31% and educed he ime o
inancial ansac ions by 68%. In e ail, cos s
dec eased by 25% and inspec ion ime by 65%,
which imp o ed p oduc quali y con ol. The o e all
e iciency o blockchain was 92% in he inancial
sec o , 85% in echnology, 82% in logis ics, 80% in
ene gy, and 78% in e ail, con i ming i s posi i e
impac on economic indica o s.
Table 5 con ains he main indica o s o
blockchain e iciency compa ed o adi ional
inancial epo ing sys ems.
Table 5: Compa ison o blockchain e iciency
indica o s wi h adi ional inancial epo ing
sys ems
Indica o T adi ional
sys ems
Blockchain
sys ems
E o de ec ion
ime (hou s)
15 2
Audi cos s ($)
500 320
Employee
p oduc i i y (%)
60 85
Sou ce: de eloped by he au ho based on he da a
om companies ha implemen ed blockchain o
2020–2024
Figu e 3 depic s he p ojec ed impac o
blockchain echnology on inancial epo ing
h ough 2028, showing he ela ionship be ween i s
implemen a ion, employee p oduc i i y, audi cos s,
and e o a es. I illus a es how blockchain
inc eases he e iciency and anspa ency o inancial
p ocesses.
Figu e 3: Fo ecas o he impac o blockchain echnology on inancial epo ing by 2028
Sou ce: de eloped by he au ho based on he da a om social media pla o ms and esul s o he 2024
s udy.
The igu e illus a es he ela ionship
be ween blockchain adop ion and inancial epo ing
by 2028. Companies wi h high blockchain adop ion
demons a e imp o ed esul s: employee
p oduc i i y inc eased om 70% (2024) o 90%
(2028), audi cos s dec eased om 36% o 50%, and
inancial epo ing e o s dec eased om 28% o
40%. Pea son co ela ion analysis con i med a s ong
ela ionship be ween blockchain adop ion and
inancial da a anspa ency ( =0.88), as well as
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Employee p oduc i i y (%) Audi cos s (%) E o s in inancial epo s
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31s May 2025. Vol.103. No.10
© Li le Lion Scien i ic
ISSN: 1992-8645 www.ja i .o g E-ISSN: 1817-3195
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be ween cos educ ion and p oduc i i y ( =0.91),
indica ing imp o ed da a managemen e iciency and
educed inancial isks.
Figu e 4 p esen s a model o he
ela ionship be ween blockchain adop ion and key
pe o mance indica o s in inancial epo ing.
Figu e 4: Co ela ion model be ween blockchain implemen a ion and inancial epo ing e iciency
Sou ce: c ea ed by he au ho based on he 2024 economic and s a is ical analysis.
The model shows ha companies ha ha e
in eg a ed blockchain educed epo ing e o s by
40% and audi cos s by 30%. The o ecas o 2028
shows ha u he implemen a ion o blockchain can
inc ease epo ing accu acy by 50% and educe cos s
by ano he 20%.
Figu e 5 shows he p ojec ed dynamics o
inancial pe o mance o companies by 2028,
p o ided ha blockchain is ac i ely implemen ed.
The g aph demons a es inc eased p oduc i i y,
educed audi cos s and educed epo ing e o s,
which will inc ease he compe i i eness o
companies in he global ma ke .
Figu e 5: Fo ecas o inancial e iciency dynamics un il 2028
Sou ce: de eloped by he au ho based on he da a o 2020-2024 and o ecas s o 2028
Blockchain is expec ed o inc ease
p oduc i i y by up o 90%, educe audi cos s by
50%, and educe inancial epo ing e o s by 40%
by 2028. I s implemen a ion in he inancial sec o
will acili a e epo ing au oma ion, i will speed up
ansac ion p ocessing and inc ease da a accu acy in
he echnology sec o , and in e ail i will s eng hen
consume us h ough supply chain anspa ency.
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Yea Employee p oduc i i y (%)
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