140 2023, olume 26, issue 2, pp. 140–157, DOI: 10.15240/ ul/001/2023-2-009
Finance
S a egic managemen , scena io analysis
and compe i i e ad an age analysis:
New oppo uni ies o an i-money launde ing
sys em e o m
Se hiy Lyeono 1, Yu ii Bilan2, Olha Kuzmenko3,
Olena K ukhmal4, László Vasa5
1 Sumy S a e Uni e si y, Educa ion and Resea ch Ins i u e o Business, Economics and Managemen , Economic
Cybe ne ics Depa men , Uk aine, ORCID: 0000-0001-5639-3008, [email p o ec ed];
2 Alexande Dubcek Uni e si y o T encin, Facul y o Social and Economic Rela ions, Slo akia, ORCID: 0000-0003-
0268-009X, y[email p o ec ed];
3 Sumy S a e Uni e si y, Educa ion and Resea ch Ins i u e o Business, Economics and Managemen , Economic
Cybe ne ics Depa men , Uk aine, ORCID: 0000-0001-8520-2266, [email p o ec ed];
4 Sumy S a e Uni e si y, Educa ion and Resea ch Ins i u e o Business, Economics and Managemen , Depa men o Fi -
nancial Technologies and En ep eneu ship, Uk aine, ORCID: 0000-0001-9118-1713, [email p o ec ed];
5 Széchenyi Is án Uni e si y, Facul y o Economics, Hunga y, ORCID: 0000-0002-3805-0244, [email p o ec ed]
(co esponding au ho ).
Abs ac : The a icle iden i ies and ma hema ically subs an ia es ec o s o e o ming he inancial
moni o ing sys em based on he syne gis ic app oach in he c oss-coun y con ex by de eloping
scena ios by selec ing in e nal and ex e nal ac o s ha s imula e money launde ing. The key
ex e nal and in e nal ac o s o he money launde ing p ocess in ensi ica ion a e indica ed.
Compe i i e ad an ages o he an i-money launde ing p ocesses, he achie emen o which is
possible in e ms o key ex e nal and in e nal ac o s o ac i a ion o money launde ing p ocess
a e o med. The ela ionship be ween he key in e nal and ex e nal ac o s o money launde ing
in ensi ica ion and compe i i e ad an ages by building a bina y cha ac e is ic ma ix is o med.
The syne gy e ec made by he mu ual in luence o simul aneously ac ing in e nal and ex e nal
ac o s – a quan i a i e ea u e o he u he s a egy o he inancial moni o ing sys em e o ming
in e ms o c oss-coun y analysis is calcula ed. An economic-ma hema ical model o e alua ing
and in e p e ing s a egy o imp o ing he inancial moni o ing sys em in e ms o c oss-coun y
con ex based on in ege op imiza ion is de eloped. In he a icle, he e is calcula ion o he numbe
o compe i i e ad an ages ecei ed by each obse ed coun y, wi hou conside ing he possible
syne gy e ec o mu ual in luence o simul aneously ac ing in e nal and ex e nal ac o s on each
o he . Mo eo e , he e is quan i a i e assessmen o he syne gy e ec made by he eme gence o
addi ional compe i i e ad an ages due o a ce ain combina ion o simul aneous in luence made
by ex e nal and in e nal ac o s o he money launde ing in ensi ica ion. The “ideal” si ua ion o
he possibili y o gaining all possible compe i i e ad an ages in e o ming he inancial moni o ing
sys em in e ms o c oss-coun y con ex by o e coming in e nal and ex e nal ac o s s imula ing
he money launde ing is s udied. The esul s o he c oss-coun y analysis o m a basis o
he u he o maliza ion o he limi s o quan i a i e e alua ion o he de eloped s a egies
h ough a uni o m dis ibu ion.
Keywo ds: Economic g ow h, sus ainable g ow h, economic de elopmen , e o ming scena ios,
compe i i e ad an ages, in e nal ac o s, ex e nal ac o s, inancial moni o ing, syne gy e ec .
JEL Classi ica ion: G28, С10, С44, С49.
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2023, olume 26, issue 2, pp. 140–157, DOI: 10.15240/ ul/001/2023-2-009
Finance
APA S yle Ci a ion: Lyeono , S., Bilan, Y., Kuzmenko, O., K ukhmal, O., & Vasa, L.
(2023). S a egic managemen , scena io analysis and compe i i e ad an age analysis: New
oppo uni ies o an i-money launde ing sys em e o m. E&M Economics and Managemen ,
26(2), 140–157. h ps://doi.o g/10.15240/ ul/001/2023-2-009
In oduc ion
The de elopmen o economic ela ions, he
eme gence o new inancial ins umen s, scien-
i ic and echnological p og ess a e among
hose ac o s ha inc ease he isk o a ac ing
cash lows o he shadow economy, c ea e con-
di ions o hei launde ing, and in some cases,
ind oppo uni ies o co up ion and o ganized
c ime. A he same ime, he de elopmen o
he inancial moni o ing sys em c ea es com-
pe i i e ad an ages o de eloping he na ional
economy and i s sus ainable g ow h.
1. Theo e ical backg ound
Gi en he scien i ic li e a u e, one should no e
ha he gene al heo e ical and p ac ical is-
sues o an i-money launde ing and he impac
o he inancial moni o ing sys em a e s udied
in he wo ks o many scien is s. Resea ches
in his a ea ha e di e en di ec ions and e eal
a ious aspec s o he opic.
Le chenko e al. (2019) in es iga e he isk
o money launde ing in de eloping and ansi-
ion economies and he impac o he inancial
moni o ing sys em on economic de elopmen .
Le chenko e al. (2018) summa ize he a gu-
men s and coun e a gumen s in he scien i ic
discussion on he main ools o he na ional eco-
nomy de-shadowing, as well as o e heo e ical
and me hodological p inciples o c ea e he de-
shadowing s a egy o he na ional economy.
Lyulyo e al. (2021) iden i y d i e s o he
shadow economy in coun ies and subs an ia e
he empi ical ela ionship wi h he le el o in es -
men , economic g ow h, social and physi cal
heal h o he popula ion. Acco ding o Gine icius
e al. (2020a), Gine icius e al. (2020b), Shpak
e al. (2021) and Simo ic (2021), he highe
he le el o na ional economic de elopmen ,
he lowe he size o he shadow economy.
The long- un analysis e ealed ha shadow
economies nega i ely a ec ed o eign di ec
in es men in lows (Baya e al., 2020; Bilan
e al., 2020; Boyko e al., 2014).
I ano a and Ko dos (2017) analyse he com-
pe i i e ad an ages caused by he educ ion o
he shadow economy and he s eng hening o
he an i-money launde ing policy. Tiu inyk and
Mazu enko (2021) also s udy he coun y’s
compe i i e ad an ages and de e mine he le -
el o inancial moni o ing as an impo an ac o
in de ining he a ou able business en i on-
men , he le el o p o ec ion o ci izens’ igh s,
ma e ial well-being o he popula ion.
The ela ionship be ween ac o s o mac-
oeconomic s abili y and s a e egula ion e ec-
i eness was s udied by Roszko-Wój owicz and
G zelak (2020). Bouche a a e al. (2020) anal-
yse he ole and ools o mac op uden ial policy.
An impo an a ea o esea ch is he s udy o
he e ec i eness o he di e en ac o s p o id-
ing mac oeconomic s abili y (Kobushko e al.,
2021; Kohno a e al., 2019; Kosch & Sza ucki,
2020; Oliinyk e al., 2019; Pe oye e al., 2020;
Thai e al., 2021; Tkachenko e al., 2019;
S adomska e al., 2019).
An impo an a ea o esea ch is o assess
he ole o he inancial moni o ing sys em o
economic g ow h and s eng hen o he com-
pe i i e ad an ages o he coun y (Ba yk e al.,
2020; B ychko e al., 2021; Glo a e al., 2020;
K y ych & Goncha enko, 2020; Pakhnenko
e al., 2021). Be na delli e al. (2021) analyse
he empo al s abili y o he ela ionship be-
ween ins i u ions and economic g ow h and eal
economic con e gence. Muj aba e al. (2018)
analyse he ela ionship be ween wo impo an
indices o business ac i i y, namely: he deg ee
o en ep eneu ial ac i i y egula ion by he cen-
al sys em and he co up ion in he coun y.
Legenzo a e al. (2019) use ne wo k analysis o
assess he links o he global banking sys em.
Coun y-speci ic ac o s o mac oeconomic s a-
bili y we e s udied by Telizhenko e al. (2019),
Saeed and Shanan (2020), Piplica (2021),
Plas un e al. (2018), Mie zejewska and Dziu -
ski (2019), and Uddin e al. (2021).
One should no e ha The Financial Ac ion
Task Fo ce (FATF) (2021) ca ies ou he e alu-
a ion o he an i-money launde ing sys em in
he coun y. The FATF me hodology does no
e lec he ocus on he an i-money launde ing
esul s. Pol (2018) examines he FATF ap-
p oach and no es he misuse o ou come
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142 2023, olume 26, issue 2, pp. 140–157, DOI: 10.15240/ ul/001/2023-2-009
Finance
labels o ou pu s, as well as he me hodo-
logy o assessing he an i-money launde ing
egime’s e ec i eness.
On he o he hand, he posi i e impac o
an e ec i e an i-money launde ing sys em con-
ibu es o o e coming he shadow economy
and is mani es ed in he imp o emen o
he coun y’s mac oeconomics (Al-Tkhayneh
e al., 2019; Juznik, 2021; Kuzne so a e al.,
2018; Sysoye a & Kleinschmid , 2017; Vasily-
e a e al., 2016). Compe i i e ad an ages a e
o e coming co up ion, imp o ing he in es men
clima e, inc easing economic ac i i y, en su ing
and imp o ing he legal en i onmen , en su ing
sus ainable social de elopmen , inc easing he
s abili y o he inancial sec o and o he s (Bo-
onos e al., 2020; Chig in & Pimonenko, 2014;
Chukwu & Kasz elnik, 2021; Vasilye a e al.,
2020; Yelniko a & Ba haq, 2020). S udying
app oaches o assessing he e ec i eness o
he an i-money launde ing sys em a e ep esen
by many schola s a ound he wo ld (And ade
& Lou ei o, 2020; Ja ošo á & Noskie ičo á,
2019; Kozmenko e al., 2013; Mus a a e al.,
2019; Pe ushenko e al., 2018; Ya o enko e al.,
2021). The scien is s’ wo ldwide expe ience
o s udying he e ec i eness o complica ed
sys ems was s udied o build a model ha akes
in o accoun he in luence o a ious ac o s
(Kasych & Vochozka, 2017; Kobushko e al.,
2020; Koibichuk e al., 2021; Schwab & Zahidi,
2021; Shipko e al., 2020; Sk ynnyk & Vasilye a,
2020a; Sk ynnyk & Vasilye a, 2020b; No iko ,
2021; Synia ska e al., 2019).
Al hough many schola s a ound he wo ld
a e s udying app oaches o assessing he e -
ec i eness o he an i-money launde ing sys-
em, an i- e o is inancing and he p oli e a ion
o mass des uc ion weapons, his ques ion
emains open in e ms o he impac made
by he sys em e ec i eness on he coun y’s
economic and social de elopmen , he pos-
sibili y o ob aining posi i e consequences
o he economy and socie y. We belie e ha
he s udy o ec o s o he inancial moni o ing
sys em e o m in e ms o c oss-coun y con ex
needs special a en ion. Assessmen o he im-
pac made by he sys em’s e ec i eness on
he coun y’s economic and social de elopmen
allows o de e mining he deg ee o pe ec ion
o he sys em and he need o i s e o m, which
has p ac ical implica ions o p ac i ione s.
Thus, he hypo hesis is ha he e is a ela-
ionship be ween key in e nal, ex e nal ac o s
o he in ensi ica ion o an i-money launde ing
based on FATF assessmen and compe i-
i e ad an ages and, in consequence o his,
economic and ma hema ical models ega ding
he in e p e a ion o s a egies o e o ming
he inancial moni o ing sys em in e ms o
c oss-coun y con ex may be de eloped.
This a icle aims o iden i y and ma h-
ema ically subs an ia e ec o s o e o ming
he inancial moni o ing sys em based on
he syne gis ic app oach in he c oss-coun y
con ex by de eloping scena ios by selec ing
in e nal and ex e nal ac o s ha s imula e
money launde ing.
2. Resea ch me hodology
Modelling o he compe i i e s a egies
In ege modelling o compe i i e s a egies
as a me hodological g ound o o ming a basis
o e o ming he inancial moni o ing sys em
in e ms o c oss-coun y analysis using a syn-
e gy app oach by o e coming in e nal and
ex e nal ac o s o money launde ing in ol es
he ollowing s ages:
1 S age. Iden i ica ion o he key ex e nal and
in e nal ac o s o he money launde ing p o-
cess in ensi ica ion. The indica o s o echnical
compliance o he inancial moni o ing sys em
in he coun y wi h he FATF ecommenda ions
a e aken. Acco ding o he FATF me hodology,
ac o s a e uni ed in o:
 G oup AML/CFT Policies and coo dina ion:
R1 – Assessing isks and applying a isk-
based app oach; R2 – Na ional coope a ion
and coo dina ion;
 G oup Money launde ing and con isca ion:
R3 – Money launde ing o ence; R4 – Con-
isca ion and p o isional measu es;
 G oup Te o is inancing and inancing o
p oli e a ion: R5 – Te o is inancing o -
ence; R6 – Ta ge ed inancial sanc ions
ela ed o e o ism & e o is inancing;
R7 – Ta ge ed inancial sanc ions ela ed o
p oli e a ion; R8 – Non-p o i o ganisa ions;
 G oup P e en i e measu es: R9 – Financial
ins i u ion sec ecy laws; R10 – Cus ome
due diligence; R11 – Reco d keep-
ing; R12 – Poli ically exposed pe sons;
R13 – Co esponden banking; R14 – Mon-
ey o alue ans e se ices; R15 – New
echnologies; R16 – Wi e ans e s;
R17 – Reliance on hi d pa ies; R18 – In-
e nal con ols and o eign b anches and
subsidia ies; R19 – Highe - isk coun ies;
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R20 – Repo ing o suspicious ansac-
ions; R21 – Tipping-o and con iden iali y;
R22 – DNFBPs: Cus ome due diligence;
R23 – DNFBPs: O he measu es;
 G oup T anspa ency and bene icial owne -
ship o legal pe sons and a angemen s:
R24 – T anspa ency and bene icial owne ship
o legal pe sons; R25 – T anspa ency and
bene icial owne ship o legal a angemen s;
 G oup Powe s and esponsibili ies o com-
pe en au ho i ies and o he ins i u ional
measu es: R26 – Regula ion and supe i-
sion o inancial ins i u ions; R27 – Pow-
e s o supe iso s; R28 – Regula ion and
supe ision o DNFBPs; R29 – Financial
in elligence uni s; R30 – Responsibili ies o
law en o cemen and in es iga i e au ho i-
ies; R31 – Powe s o law en o cemen and
in es iga i e au ho i ies; R32 – Cash cou i-
e s; R33 – S a is ics; R34 – Guidance and
eedback; R35 – Sanc ions;
 G oup In e na ional coope a ion: R36 – In-
e na ional ins umen s; R37 – Mu ual legal
assis ance; R38 – Mu ual legal assis ance:
eezing and con isca ion; R39 – Ex adi-
ion; R40 – O he o ms o in e na ional co-
ope a ion.
2 S age. Fo ma ion o compe i i e ad an-
ages o he an i-money launde ing p o-
cesses, he achie emen o which is possible
in e ms o key ex e nal and in e nal ac o s
o ac i a ion o money launde ing p ocess:
KP1 – O e coming co up ion, KP2 – Imp o ing
in es men clima e, KP3 – Inc easing economic
ac i i y – ensu ing and imp o ing he legal en-
i onmen , KP5 – Ensu ing sus ainable social
de elopmen , KP6 – Inc easing he s abili y o
he inancial sec o , he sou ces o in o ma ion
in e ms o which a e espec i ely: Co up ion
Pe cep ions Index (T anspa ency In e na ional,
2021), A Global Fo eign Di ec In es men
Coun y A ac i eness Index (Riadh, 2020),
Ease o Doing Business Index (Wo ld Bank,
2021), Wo ld Jus ice P ojec Rule o Law Index
(Wo ld Jus ice P ojec , 2021), Economic Well-
being Index (Kowalski & Vei , 2020).
3 S age. I is p oposed o o m a sample o
42 coun ies based on coun ies ha a e as-
sessed by all he abo e c i e ia. The lis o
coun ies includes: I aly, Denma k, Uni ed
Kingdom, Spain, Sweden, Belgium, China,
Canada, he USA, Singapo e, Ko ea, Uni ed
A ab Emi a es, Uk aine, New Zeland, Aus alia,
Bo swana, Bu kina-Faso, Cambodia, he Czech
Republic, Dominican Republic, E hiopia, Fin-
land, G eece, Hondu as, Hunga y, Jo dan, Mad-
agasca , Mali, Mau i ania, Mau i ius, Mexico,
Mo occo, Nica agua, No way, Pakis an, Pe u,
Philippines,Russian Fede a ion, Tunisia, Tu -
key, Uganda, and U uguay.
4 S age. Fo malizing he ela ionship be ween
key in e nal and ex e nal ac o s o money
launde ing p ocess ac i a ion and compe i i-
e ad an ages by building a ma ix o bina y
cha ac e is ics (Tab. 1).
A epo on p og ess in add essing he
echnical compliance de iciencies iden i ied
in he FATF assessmen o hei measu es o
comba money launde ing and e o is inanc-
ing was analysed, and weaknesses ha do no
allow o achie e ce ain compe i i e ad an-
ages we e iden i ied o build a ma ix o bina y
cha ac e is ics o each coun y.
Elemen s in he ma ix o bina y cha ac e -
is ics o in e nal and ex e nal ac o s o ac i a e
he money launde ing p ocess, p o iding com-
pe i i e ad an ages, p esen ed in Tab. 1, a e
o malized in he o m o he ollowing o mula:
aij =
[
1, i i- ac o p o ides j-compe i i e ad an age
0, i i- ac o does no p o ide j-compe i i e ad an age (1)
whe e: aij – bina y indica o , which co esponds o he in e sec ion o he i- ac o (in e nal o ex e -
nal) ega ding ac i a ion o he money launde ing p ocess and he j-compe i i e ad an age.
(2)
whe e: Sgj – he sum o bina y indica o s in e ms o in e nal and ex e nal ac o s o ac i a e he mon-
ey launde ing p ocess in e ms o g-g oup; Ng – he numbe o ex e nal o in e nal ac o s in ensi y-
ing he money launde ing p ocess in e ms o g-g oup; Ngs – o dinal numbe o he indica o in o al,
which begins he sequen ial calcula ion o he g-g oup indica o s.
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144 2023, olume 26, issue 2, pp. 140–157, DOI: 10.15240/ ul/001/2023-2-009
Finance
5 S age. De elopmen o economic and ma he-
ma ical models ega ding comple e e alua ion
and in e p e a ion o s a egies o e o ming
he inancial moni o ing sys em in e ms o
c oss-coun y con ex based on in ege op imi-
za ion. The syne gy e ec o mu ual in luence
made by simul aneously ac ing in e nal and
ex e nal ac o s is calcula ed o implemen his
s age. These a e quan i a i e ea u es o u -
he s a egy o e o m he inancial moni o ing
sys em in e ms o c oss-coun y analysis, and
s a egy o maliza ion: apid, mode a ely as ,
slow and neu al adap abili y o ex e nal ac o s.
Quan i ying he s a egy o e o m he inan-
cial moni o ing sys em in e ms o c oss-coun y
analysis, he e is a need o some in e media e
calcula ions – s eps o summa ize he bina y
indica o s p esen ed in Tab. 1.
S ep 5.1: Calcula ion o he numbe o com-
pe i i e ad an ages ecei ed by each obse ed
Fac o s in ensi ying he money
launde ing p ocess
Compe i i e ad an ages
KP1 KP2 KP3 KP4 KP5 KP6
AML/CFT Policies and coo dina ion
R1 a11 a12 a13 a14 a15 a16
R2 a21 a22 a23 a24 a25 a26
To al Sg11 Sg12 Sg13 Sg14 Sg15 Sg16
Money launde ing and con isca ion
R3 a31 a32 a33 a34 a35 a36
R4 a41 a42 a43 a44 a45 a46
To al Sg21 Sg22 Sg23 Sg24 Sg25 Sg26
Te o is inancing and inancing
o p oli e a ion
R5 a51 a52 a53 a54 a55 a56
…………………
R8 a81 a82 a83 a84 a85 a86
To al Sg31 Sg32 Sg33 Sg34 Sg35 Sg36
P e en i e measu es
R9 a91 a92 a93 a94 a95 a96
…………………
R23 a231 a232 a233 a234 a235 a236
To al Sg41 Sg42 Sg43 Sg44 Sg45 Sg46
T anspa ency and bene icial
owne ship o legal pe sons
and a angemen s
R24 a241 a242 a243 a244 a245 a246
R25 a251 a252 a253 a254 a255 a256
To al Sg51 Sg52 Sg53 Sg54 Sg55 Sg56
Powe s and esponsibili ies
o compe en au ho i ies and o he
ins i u ional measu es
R26 a261 a262 a263 a264 a265 a266
…………………
R35 a351 a352 a353 a354 a355 a356
To al Sg61 Sg62 Sg63 Sg64 Sg65 Sg66
In e na ional coope a ion
R36 a361 a362 a363 a364 a365 a366
…………………
R40 a401 a402 a403 a404 a405 a406
To al Sg71 Sg72 Sg73 Sg74 Sg75 Sg76
To al S1S2S3S4S5S6
Sou ce: own
Tab. 1: Ma ix o bina y cha ac e is ics o in e nal and ex e nal ac o s o money
launde ing p ocess ac i a ion, p o iding compe i i e ad an ages
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coun y, wi hou conside ing he possible syne -
gy e ec o mu ual in luence o simul aneously
ac ing in e nal and ex e nal ac o s on each
o he as a se :
S ep 5.2: Quan i a i e assessmen o he syn-
e gy e ec made by he eme gence o addi-
ional compe i i e ad an ages due o a ce ain
combina ion o simul aneous in luence made by
ex e nal and in e nal ac o s o he money laun-
de ing in ensi ica ion. A syne gy e ec occu s i
he sum o bina y indica o s wi hin each com-
pe i i e ad an age wi hou conside -
ing he syne gy e ec is a leas le el 2; and we
calcula e he addi ional e ec when
exceeding le el 1. We use a ma hema ical a io
ha con ains a combina ion o in ege and a max-
imum o wo unc ions o eco d a quan i a i e
assessmen o he syne gy e ec o addi ional
compe i i e ad an ages due o a combina ion
o simul aneous in luence o bo h ex e nal and
in e nal ac o s o money launde ing ac i a ion:
(4)
S ep 5.3: Quan i a i e assessmen o he syn-
e gy e ec ega ding he eme gence o ad-
di ional compe i i e ad an ages by exceeding
he sum o bina y indica o s wi hin each com-
pe i i e ad an age o h esholds
10, 20 and 30:
S ep 5.4: The las s ep o o m he ela ion-
ship be ween key in e nal and ex e nal ac o s
o in ensi ica ion o money launde ing and
compe i i e ad an ages by building he ma ix
o bina y cha ac e is ics as an in eg a ed ab-
solu e quan i a i e assessmen o scena ios
o e o ming he inancial moni o ing sys em
in e ms o c oss-coun y analysis (SR) p o-
ides o an addi i e con olu ion o he abo e
componen s [Fo mulas (1–5)] by o ming
he ollowing ma hema ics:
6 S age. A s udy o he “ideal” si ua ion o
he possibili y o gain all possible compe i i e
ad an ages wi hin he inancial moni o ing sys-
em e o ming in e ms o c oss-coun y con ex
by o e coming in e nal and ex e nal ac o s
s imula ing he money launde ing p ocess. This
s age is implemen ed by o ming he maximum
possible si ua ion, cha ac e ized by he uni
(3)
whe e: Zj – bina y indica o , acqui ing a single alue, i i is possible o ob ain he j-compe i i e
ad an age by o e coming he ex e nal o in e nal ac o o money launde ing in ensi ica ion, and
ze o le el o he wise.
(5)
(6)
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Finance
le els o bina y alues in e ms o compliance
o all conside ed in e nal and ex e nal ac o s
o all po en ial compe i i e ad an ages (Tab. 2).
Thus, gi en he “ideal” si ua ion, he ele-
men s o Fo mula (6) acqui e he ollowing
alues: – he las line o Tab. 2;
will ha e indi idual alues;
ake ze o alues in e ms o
all six compe i i e ad an ages;
– quan i ica ion o
he syne gy e ec o addi ional compe i i e
ad an ages due o exceeding he h es-
hold le el 2 o each g oup o in e nal
Fac o s in ensi ying he money
launde ing p ocess
Compe i i e ad an ages
KP1 KP2 KP3 KP4 KP5 KP6
AML/CFT Policies and coo dina ion
R1 111101
R2 111111
To al 222212
Money launde ing and con isca ion
R3 100110
R4 110110
To al 210220
Te o is inancing and inancing
o p oli e a ion
R5 100110
… ………………
R8 111010
To al 411340
P e en i e measu es
R9 011111
… ………………
R23 111111
To al 9 12 10 9 14 14
T anspa ency and bene icial
owne ship o legal pe sons
and a angemen s
R24 101111
R25 101111
To al 202222
Powe s and esponsibili ies
o compe en au ho i ies and o he
ins i u ional measu es
R26 000111
… ………………
R35 100101
To al 722987
In e na ional coope a ion
R36 111111
… ………………
R40 100110
To al 511551
To al 31 19 18 32 36 26
Sou ce: own
Tab. 2:
De e mining he “ideal” si ua ion o he possibili y o gain all po en ial
compe i i ead an ageswi hin he inancialmoni o ingsys em e o ming
in e ms o c oss-coun y con ex by o e coming in e nal and ex e nal ac o s
s imula ing he money launde ing p ocess
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Finance
and ex e nal ac o s sepa a ely and
a e: 5 ( o KP1), 1 ( o KP2), 2 ( o KP3 and KP6),
4 ( o KP4 and KP5); quan i a i e assessmen
o he syne gy e ec o he addi ional compe i-
i e ad an ages by exceeding he sum o bina y
indica o s wi hin each compe i i e ad an age
o h esholds a he le els
10, 20 and 30:
akes a uni alue only o KP4 and KP5,
and
akes a uni alue
only o h ee compe i i e ad an ages KP1,
KP4, KP5.
Thus, conside ing hese quan i a i e alues
in Fo mula (6) in he case o an “ideal” si ua ion,
he in eg a ed absolu e quan i a i e assessmen
o scena ios o e o m he inancial moni o ing
sys em in e ms o c oss-coun y analysis (SR)
akes he alue o 197 uni s.
7 S age. Calcula ion o in eg a ed ela i e
quan i a i e assessmen (VSR) o scena ios o
e o m he inancial moni o ing sys em in e ms
o c oss-coun y analysis by o malizing he e-
la ionship o key in e nal and ex e nal ac o s
o he in ensi ica ion o he money launde -
ing p ocess and compe i i e ad an ages. I is
necessa y o weigh he absolu e es ima e
[Fo mula (6)] on he alue SR o he “ideal”
si ua ion, i.e., 197 uni s:
(7)
8 S age. Quali a i e in e p e a ion o he ela-
i e quan i a i e assessmen o s a egies o
e o m he inancial moni o ing sys em: apid,
mode a ely as , slow and neu al adap abili y
o ex e nal ac o s.
The “ideal” si ua ion o gaining all possible
compe i i e ad an ages wi hin e o ming he i-
nancial moni o ing sys em in e ms o c oss-
coun y con ex by o e coming in e nal and
ex e nal ac o s s imula ing he money launde -
ing p ocess is s udied. The implemen a ion o
his s age in ol es he o maliza ion o he max-
imum possible si ua ion, cha ac e ized by
he uni le els o bina y alues in e ms o com-
pliance o all conside ed in e nal and ex e nal
ac o s o all po en ial compe i i e ad an ages.
The s a egy o apid adap abili y demon-
s a es he coun y’s acquisi ion o ce ain com-
pe i i e ad an ages while achie ing compliance
o in e nal and ex e nal ac o s o in ensi ying
he money launde ing p ocess wi h speci ic
FATF ecommenda ions. The s a egy o neu-
al adap abili y indica es he inconsis ency o
he echnical ea u es in he moni o ing sys em
wi h he FATF ecommenda ions and demon-
s a es he lack o compe i i e ad an age. S a -
egies o mode a ely as and slow adap abili y
a e in e media e. We use a uni o m dis ibu ion
o he possible ange o alues om ze o o one
o de e mine he lowe and uppe limi s o s a -
egies o e o ming he inancial moni o ing sys-
em in e ms o c oss-coun y con ex (Tab. 3).
Implemen ing he in ege modelling o com-
pe i i e s a egies as a me hodological g ound
o o m a basis o e o ming he inancial moni-
o ing sys em in e ms o c oss-coun y analysis
using syne gy app oach by o e coming in e nal
and ex e nal ac o s o money launde ing, we
conside he ma ix o inpu bina y alues on
he example o I aly (Tab. 4).
S a egy Lowe limi o possible
alues
Uppe limi o possible
alues
Neu al adap abili y o ex e nal ac o s 0.00 0.25
Slow adap abili y o ex e nal ac o s 0.25 0.50
Mode a ely apid adap abili y o ex e nal ac o s 0.50 0.75
Rapid adap abili y o ex e nal ac o s 0.75 1.00
Sou ce: own
Tab. 3: Quali a i e in e p e a ion o he ela i e quan i a i e assessmen o s a egies
o  e o ming he inancialmoni o ingsys emin e mso c oss-coun y con ex
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148 2023, olume 26, issue 2, pp. 140–157, DOI: 10.15240/ ul/001/2023-2-009
Finance
Fac o s in ensi ying he money
launde ing p ocess
Compe i i e ad an ages
KP1 KP2 KP3 KP4 KP5 KP6
R1 111101
R2 111000
R3 100110
R4 110110
R5 100100
R6 100110
R7 000010
R8 001010
R9 011111
R10 100111
R11 111011
R12 010010
R13 011000
R14 011010
R15 011011
R16 011011
R17 011111
R18 100001
R19 011000
R20 100111
R21 111010
R22 110111
R23 111110
R24 101111
R25 101111
R26 000111
R27 000111
R28 000111
R29 100111
R30 100110
R31 100110
R32 100111
R33 111001
R34 111110
R35 100101
Tab. 4: Ma ix o bina y cha ac e is ics o in e nal and ex e nal ac o s o ac i a ing
he money launde ing p ocess, p o iding compe i i e ad an ages o I aly – Pa 1
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