7/23/2019 Financial Fraud Detection Model: Based on Random Forest

1/11

Mjtfrjatmkjad Okurjad kn F`kjkim`s ajl Nmjaj`f3 ^kd. 7, Jk. 73 8516MPPJ 1=1>-=71R F-MPPJ 1=1>-=782

Uuhdmsbfl hy @ajalmaj @fjtfr kn P`mfj`f ajl Flu`atmkj

172

Nmjaj`mad Nraul Lftf`tmkj Iklfd? Hasfl kj Xajlki Nkrfst

@bfjgwfm Dmu1, ]mxmajg @baj1, Pyfl Basjamj Adai Cazim1& Bak Nu1

1P`bkkd kn F`kjkim`s ajl Iajagfifjt, Pkutbwfst Omaktkjg Vjmvfrsmty, @bfjglu, Pm`buaj, @bmja

@krrfspkjlfj`f? Bak Nu, P`bkkd kn F`kjkim`s ajl Iajagfifjt, Pkutbwfst Omaktkjg Vjmvfrsmty, @bfjglu,Pm`buaj, @bmja. \fd? 2>-582-27>5-52=6. F-iamd? baknu18E18>.`ki

Xf`fmvfl? Aprmd 2, 8516 A``fptfl? Aprmd 88, 8516 Kjdmjf Uuhdmsbfl? Oujf 86, 8516

lkm?15.660=/mofn.v7j7p172 VXD? bttp?//lx.lkm.krg/15.660=/mofn.v7j7p172

Ahstra`t

Husmjfsss a``fdfratfl gdkhadmzatmkj bas wfacfjfl rfgudatkry `apa`mty kn tbf daw ajl s`bkdars bavf hffj paml

attfjtmkj tk nraul lftf`tmkj mj rf`fjt yfars. Mj tbms stuly, wf mjtrklu`fl Xajlki Nkrfst (XN) nkr nmjaj`mad nraul

tf`bjmquf lftf`tmkj ajl lftamdfl nfaturfs sfdf`tmkj, varmahdfs mipkrtaj`f ifasurfifjt, partmad `krrfdatmkj

ajadysms ajl Iudtmlmifjsmkjad ajadysms. \bf rfsudts sbkw tbat a `kihmjatmkj kn fmgbt varmahdfs bas tbf bmgbfsta``ura`y. \bf ratmk kn lfht tk fqumty (LFQV\]) ms tbf ikst mipkrtajt varmahdf mj tbf iklfd. Ikrfkvfr, wf

appdmfl nkur statmstm` iftbklkdkgmfs, mj`dulmjg paraiftrm` ajl jkj-paraiftrm` iklfds tk `kjstru`t lftf`tmkj

iklfds ajl `kj`dulfl tbat Xajlki Nkrfst bas tbf bmgbfst a``ura`y ajl tbf jkj-paraiftrm` iklfds bavf bmgbfr

a``ura`y tbaj jkj-paraiftrm` iklfds. Bkwfvfr, Xajlki Nkrfst `aj miprkvf tbf lftf`tmkj fnnm`mfj`y

smgjmnm`ajtdy ajl bavf aj mipkrtajt pra`tm`ad mipdm`atmkj.

Cfywkrls? nmjaj`mad nraul lftf`tmkj, rajlki nkrfst, ratmk kn lfht tk fqumty, partmad `krrfdatmkj ajadysms, statmstm`

iftbklkdkgmfs, paraiftrm` iklfds

1. Mjtrklu`tmkj

Mj tklays gdkhadmzfl iarcft, tbf smzf kn tbf nmri ms dargfr lay hy lay, ajl ikrf arfjas arf fvkdvfl ajl mj tbf

`kjtfxt nrauludfjt hfbavmkr kn fjtfrprmsf dfals tk bugf dkssfs ajl hrmjgs sfrmkus laiagf tk tbf mjvfstkrs

`kjnmlfj`f ajl tbf pfkpdf pay ikrf attfjtmkj tk tbf tkpm` ajl hrajl `kipajmfs arf nk`usmjg tk targft tbf prm`mjg

mj tbf rmgbt iajjfr (f.g., Hrfmiaj, 85513 Dmaw & Wmfjfr, 85583 Ptrkhd ft ad., 855=3 Najg ft ad., 85183 Bajsfj

1==>3 Cmrcks ft ad., 85573 Adai Cazim, 8516a, h). Bkwfvfr, rfpkrts kn nrauludfjt hfbavmkr lftf`tmkj wfrf

lmnnm`udt nkr stann supfrvmsmkj. Cmrcks ft ad. (8557) nkujl tbat tbfrf arf tbrff iamj rfaskjs. Nmrst, tbfrf ms da`c kn

cjkwdflgf ahkut nmjaj`mad nraul, adtbkugb iajy prmkr rfsfar`bfs kj tbf nmjaj`mad nraul wfrf mjvfstmgatfl tk

skif `kj`dusmkjs, hut tbfy wfrf nar away nrki tbf pra`tm`f. Pf`kjl, ikst aulmtkrs da`c fxpfrmfj`fs, wbm`b

iacfs tbfi lmnnm`udt tk lftf`t tbf rkkts mj nmjaj`mad nraul. Nmjaddy, `krpkratf fxf`utmvfs lfdmhfratfdy lf`fmvf ajl

tbfy usf skpbmstm`atfl tkkds tk addkw aulmtkrs jkt tk cjkw wbfrf tk hfgmj. \bfrfnkrf, bkw tk bfdp tbf gkvfrjifjt

ajl aulmtkrs tk miprkvf tbf ahmdmty tk lftf`t nraul ms `ru`mad prkhdfi ajl tbms papfr try tk ifft tbms lfiajl wmtb

mj lfptb ajadytm`ad tkkds ajl tf`bjmqufs. Wf lfikjstratfl iklfds tk iacf a `kipajmkj wmtb Xajlki Nkrfst

tf`bjmqufs ajl kiparfl tbf fnnm`mfj`y hftwffj a paraiftfr ajl jkj-paraiftrm` iklfds.

1.1 Iklfds mj Xajlki Nkrfst

Mlfjtmnm`atmkj kn nmjaj`mad nraul ms a `baddfjgmjg tasc. A dargf juihfr kn s`bkdars bavf fstahdmsbfl rf`kgjmtmkjiklfd tk lftf`t mt nrki lmnnfrfjt ajgdfs, usmjg lmnnfrfjt iftbkls, su`b as lfnmjf hy Bajsfj (1==>) ajl Cmrcks ft

ad. (8557). Bajsfj (1==>) appdmfl a gfjfradmzfl quadmtatmvf rfspkjsf iklfd (FGH8) tk mlfjtmny iajagfifjt

nraul. \bfy usfl lata nrki tbf mjtfrjatmkjad a``kujtmjg nmri tk nmt tbf iklfd ajl mt sbkwfl a gkkl prflm`tmvf

ahmdmty. \bfy Nkujl tbat tbf iklfd `aj skdvf asyiiftrm` frrkrs `kst nrki tbf \ypf MM ajl M frrkrs, mt `aj

fnnf`tmvfdy prfvfjt tbf dkss nrki dawsumt nrki iacmjg tbf \ypf MM frrkr. Cmrcks ft ad. (8557) usfl a lata imjmjg

iftbkl tk fstahdmsb tbrff nrauludfjt mlfjtmnm`atmkj iklfd, cjkwj as Lf`msmkj \rff (L\), Jfurad Jftwkrcs (JJ)

ajl Hayfsmaj Jftwkrc (HHJ) ajl tbrkugb \fj-nkdl `rkss-vadmlatmkj. \bf rfsudts sbkw tbat Hayfsmaj jftwkrc

(HHJ) bas tbf bmgbfst a``ura`y. Xavmsajcar ft ad. (8511) usfl iudtm-dayfr nfflha`c jfurad jftwkrcs, suppkrt

vf`tkr ia`bmjfs, prkhahmdmstm` jfurad jftwkrcs ajl ktbfr nkur iftbkls tk humdl iklfds. \bf rfsudts sbkwfl tbat

prkhahmdmstm` jfurad jftwkrc (UJJ) pfrnkriaj`f was kutstajlmjg. Najjmjg ajl @kggfr (1==2) `kjstru`tfl

iklfd wmtb tbf jfurad jftwkrc ajl tbf mjlfpfjlfjt varmahdfs mj`dulfl tbf nmjaj`mad ratmks ajl quadmtatmvf

varmahdfs. \bfy adsk usfl skif ktbfr tralmtmkjad statmstm`ad iftbkls tk humdl iklfds tk iacf a `kiparmskj wmtb

7/23/2019 Financial Fraud Detection Model: Based on Random Forest

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www.``sfjft.krg/mofn Mjtfrjatmkjad Okurjad kn F`kjkim`s ajl Nmjaj`f kd. 7, Jk. 73 8516

17=

jfurad jftwkrcs. \bfy `kj`dulfl tbat jfurad jftwkrcs bavf a bmgbfr a``ura`y tbaj tbf tralmtmkjad statmstm`ad

iftbkls.

1.8 Iklfd Lfvfdkpifjts

Puiifrs ajl Pwffjfy (1==2) fstahdmsbfl a Dkgmstm` iklfd tk vadmlatf tbf rfdatmkjsbmp hftwffj mjtfrjad

trajsa`tmkjs ajl nraul. \bfy nkujl tbat iajagfrs wkudl lf`rfasf tbf `kipajys stk`c bkdlmjgs hy nrfqufjt

tralmjg wbfj tbfrf ms a nraul.Ahhktt ajl Uarcfr (8555) fxai wbftbfr tbf prfsfj`f kn aj mjlfpfjlfjt aulmt `kiimttff fnnf`tmvfdy rflu`fs tbf

pkssmhmdmty kn `krpkratf nraul tbrkugb a rfgrfssmkj. \bf rfgrfssmkj rfsudts sbkw wbfj tbf mjlfpfjlfjt aulmt

`kiimttff ajl `krpkratf ajjuad ifftmjgs bfdl at dfast ikrf tbaj twm`f, tbf `kipajy bavf rfpkrtfl tk rflu`f

nmjaj`mad rfpkrtmjg frrkrs. @bfj ft ad. (855>) stulmfl tbf rfdatmkjsbmp hftwffj `krpkratf gkvfrjaj`f ajl

kwjfrsbmp stru`turf `krpkratf nmjaj`mad nraul wmtb tbf saipdf kn @bmjfsf dmstfl `kipajmfs. \bf rfsudts sbkw tbat

`krpkratf kwjfrsbmp stru`turf ajl hkarl kn gkvfrjaj`f `bara`tfrmstm`s arf mipkrtajt mjlm`atkrs nkr nraul

mjtfrprftatmkj. \bfy adsk nkujl tbat tbf ratmk kn mjlfpfjlfjt lmrf`tkrs, hkarl ifftmjg nrfqufj`y ajl tbf tfri kn

knnm`f kn tbf bamrpfrskj rfdatfl tk nraul.

Mj tbms papfr, hasfl kj prmkr stulmfs, wf mjtrklu`fl ajl ajadyzfl tbf appdm`atmkj kn rajlki nkrfst mj nmjaj`mad

nraul. Wf `kjstru`t ajl tfst tbf iklfd wmtb lata nrki dmstfl `kipajmfs nrki @bmja. Ifajwbmdf, wf `kjstru`t

skif iklfds tk iacf a `kipajmkj wmtb Xajlki Nkrfst. Wf `kiparfl tbf fnnm`mfj`y hftwffj a paraiftfr

iklfds ajl jkj-paraiftrm` iklfds. \bf stuly nkddkw tbf stru`turf as, mjtrklu`tmkj tk tbf rfsfar`b iftbkl mjPf`tmkj 8 mj`dulmjg rajlki nkrfsts, nfaturf sfdf`tmkj ajl mjtrklu`tmkj kn lata. \bf fipmrm`ad ajadysms, mj`dulmjg

nmttmjg, tfstmjg kn rajlki nkrfsts, ajl ktbfr iklfds ajl prfsfjtfl mj Pf`tmkj 0 ajl Pf`tmkj

7/23/2019 Financial Fraud Detection Model: Based on Random Forest

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125

\bf prk`fss bfdps tk `bkksf tbf ikst kutstajlmjg pfrnkriaj`f iklfd kn Hrfmiaj (8551).

8.1.8 Haddparc Iatrmx kn Lata

Urkxmimty hftwffj ajy twk pkmjts ms lfnmjf as tbf ratmk kn tbf juihfr kn k``urrfj`fs kn tbf twk lata kj tbf saif

fjl kn tbf `dassmnm`atmkj trff jklf. Fstahdmsb a J J-lmifjsmkjad prkxmimty iatrmx (J ms tbf juihfr kn lata

pkmjts) ajl fa`b fdfifjt kn tbf iatrmx rfprfsfjts tbf rajlki nkrfst fa`b trff mj twk `krrfspkjlmjg lata pkmjts

nadd kj tbf saif fjl jklf ratmk. A``krlmjg tk tbf fxpfrmfj`f, lmssmimdar lata pkmjts gatbfrfl at tbf fjl kn tbfprkhahmdmty kn a hraj`b ms jkt smgjmnm`ajtdy bmgbfr tbaj tbf prkhahmdmty kn prkxmimty lata pkmjts gatbfrfl.

Bkwfvfr, tbf `kiputatmkj kn tbf prkxmimty kn tbf iatrmx ms rfdatmvfdy vfry dargf. \bf prkxmimty `aj hf appdmfl tk

mjput tbf imssmjg vadufs, lftf`t tbf smjgudar vadufs, iacf partmad pdkt, `dustfrmjg ajadysms, lmifjsmkj rflu`tmkj

ajl vmsuadmzatmkj. Mj tbms stuly, wf mjtrklu`f tbf partmad pdkt ajl lmifjsmkj rflu`tmkj.

Uartmad pdkt `aj prfsfjt bkw a varmahdf nrki tbf hda`c hkx (P^I, XN, L\, JJ\, `dassmnm`atmkj ajl rfgrfssmkj

iklfd mipa`t tbf prflm`tmkj mj a vmsuad way. (_bajg ft ad., 851

7/23/2019 Financial Fraud Detection Model: Based on Random Forest

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121

Puiifrs ajl Pwffjfy (1==2) nkujl tbat tbf `krpkratf lfht dfvfd ms aj mipkrtajt mjlm`atkr tk rf`kgjmzf tbf

`krpkratf nmjaj`mad nraul. \bfrfnkrf, tbms papfr usfs grkss prknmt ajl FHM\ (\UFHM\), FHM\ ajl kpfratmjg

mj`kif ratmk (FHM\PAD), `asb ndkw mjtfrfst `kvfragf ratmk (JK@NMF), mjtfrfst `kvfragf ratmk (\MJFAX),

dkjg-tfri lfht tk `apmtadmzatmkj ratmk (D\L@AU), wkrcmjg `apmtad ajl hkrrkwmjg ratmk (WK@AUD) tk ifasurf a

`krpkratf skdvfj`y. Xavmsajcar ft ad. (8511)3 Oaifs (8550) ajl @kbfj ft ad. (8556< 5.087 5.5

FHM\PAD -5.=65 5.2 5.52= 5.176 .277 5.555

XKA -5.12< 5.862 5.560 5.5>2 .552 5.551

JUXK\A -5.816 5.885 5.500 5.5>< .586 5.555

JUXK@A -5.>0> 5.088 5.561 5.102 .55> 5.555

JUXNAP -5.216 8.501 5.1>2 5.01 5.555

XKF -5.61 5.555

DK\@AG -5.82> 5.6 5.526 5.11< .551 5.555

IAJFRU 5.552 1.51= 5.11> 5.105 .5.56= 8=>.>>7 20.76 7.=50 11.87= .6 5.555

A@XFPAD 5.551 1.=10 5. 1.=0< 5.080 5.8=5 .7=2 5.555

@VXAP\ 5.567 2.8>1 1.16< 5.2=1 .555 5.555

NAPMJ@ 5.502 08 .8=1 5.555

NAPP\V 5.111 =.862 8.>< 5.555

LND -5.60= 6.828 1.< 5.71> .707 5.555

WKX@AU -1.78> 5.=00 5.1>> 5.6= 5.117 5.180 .015 5.555

WK@AUD -1.78= 80.755 8.0

7/23/2019 Financial Fraud Detection Model: Based on Random Forest

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7/23/2019 Financial Fraud Detection Model: Based on Random Forest

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Mj krlfr tk miprkvf tbf a``ura`y, wf wmdd nmjl tbf hfst paraiftfr tk kptmimzf iklfd humdt ajl tbf rfsudt arf

sbkwj mj Nmgurf 8. \bf nmgurf sbkws tbat tbf hfst paraiftfr kn itry ms 0 ajl tbfrf ms jk mipa`t wbfj tbf trff

juihfr ms ikrf tbaj 655. Wf wmdd sft tbfsf twk paraiftfr at 0 ajl 655, agamj tk tfst tbf iklfd hy nmvf-nkdl tfst

ajl wf gft a 18% frrkr ratf. @kjsfqufjtdy, tbf kptmimzatmkj kn paraiftfrs bas aj khvmkus mipa`t kj tbf rfsudts.

0.8 LA``ura`y Iftbkl Ifasurfifjt

Ifasurfifjt iftbkls hasfl kj rajlki nkrfsts, mj`dulmjg Lf`fasf A``ura`y ajl Lf`fasf Gmjm `kfnnm`mfjt arfusfl tk ifasurf tbf mipkrtaj`f kn tbf varmahdfs mj tbf iklfd. Wbmdf LA``ura`y iftbkl kn ifasurmjg tbf

mipkrtaj`f kn fa`b varmahdf kj tbf lfpfjlfjt varmahdf Nraul ajl Jnraul nkddkws twk cmjls kn `kipajmfs. \bf

rfsudts arf sbkwj mj \ahdf 0. Xfsudts sbkw tbat tbf ifasurfl iaxmiui prflm`tmkj a``ura`y ajl Gmjm `kfnnm`mfjt

kn

7/23/2019 Financial Fraud Detection Model: Based on Random Forest

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www.``sfjft.krg/mofn Mjtfrjatmkjad Okurjad kn F`kjkim`s ajl Nmjaj`f kd. 7, Jk. 73 8516

128 >>. 5.5507UF 5.06@VXAP\ 5.60WKX@AU1

pp

9 + +

7/23/2019 Financial Fraud Detection Model: Based on Random Forest

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www.``sfjft.krg/mofn Mjtfrjatmkjad Okurjad kn F`kjkim`s ajl Nmjaj`f kd. 7, Jk. 73 8516

12>

P^I 21.22 72.10 25.12

XN 26.1> =5.71 22.55

Nrki, \ahdf > sbkwmjg as Dkgmstm` iklfd rf`kgjmzfs tbf kvfradd su``fss ratf was 0%, rfspf`tmvfdy. L\ iklfd `aj su``fssnuddy mlfjtmnmfl >>.2.10% ajl >0.>8%, nkr Jnraul rf`kgjmtmkj su``fss ratf ms bmgbfr tbaj Nraul,

`kiimttmjg \ypf M frrkr tbaj tk `kiimt a \ypf MM frrkr bavf a bmgbfr pkssmhmdmty. P^I iklfd mlfjtmnm`atmkj kn

21.22% ajl 72.10% kn Jnraul saipdf kn Nraul saipdf tfst sft, tbf kvfradd su``fss ratf rfa`bfl 25.2 pfr`fjt, tbf

rfsudts kn tbf tfst ms rfdatmvfdy gkkl. XN iklfds arf iklfds tk mlfjtmny tbf ikst fnnm`mfjt iklfds, tbf kvfradd

su``fss ratf kn 22 pfr`fjt rf`kgjmtmkj, wbm`b tbf Jnraul rf`kgjmtmkj su``fss ratf rfa`bfl 26% kn Nraul

rf`kgjmtmkj su``fss rfa`bfl =5.71%. Ukssmhmdmty kn `kiimttmjg \ypf MM frrkr ms dkwfr tbaj tbf dmcfdmbkkl kn

`kiimttmjg \ypf M frrkr. \bms ms nkr aulmt nmris ajl gkvfrjifjt lfpartifjts ms vfry mipkrtajt. Mn a jkriad

`kipajy imsoulgfl as bavmjg a nraul, tbfj tk bms rfputatmkj, `rflmhmdmty a lfvastatmjg hdkw, tbfj tbf jfxt tbfy

wmdd na`f bugf laiagfs, ajl rajlki nkrfsts tk skif fxtfjt addfvmatfl su`b `rmsfs. \bf ahmdmty tk mlfjtmny tbf

strkjgfst rajlki nkrfst ajl fxtrapkdatmkj ahmdmty ms tbf hfst, wf `aj sff tbat tbf mjtrklu`tmkj kn rajlki nkrfsts

kvfradd nmjaj`mad rf`kgjmtmkj nrki tbf pfrspf`tmvf kn rf`kgjmtmkj ratf `aj miprkvf tbf rf`kgjmtmkj kn nmjaj`madnraul. Wf adsk nkujl tbat rf`kgjmtmkj ratf paraiftfr iklfd, wbm`b arf Dkgmstm` ajl CJJ tk hf smgjmnm`ajtdy

dkwfr tbaj tbf jkj-paraiftrm` iklfds tbat, arf L\, P^I ajl XN, wbm`b mlfjtmny tbf dkwfst fnnm`mfj`y Dkgmstm`

iklfd.

>.

7/23/2019 Financial Fraud Detection Model: Based on Random Forest

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127

Jkj-paraiftrm` iklfd P^I ajl XN rfa`b 25.12% ajl 22%. Pk wf cjkw nrki tbf rfsudts tbat paraiftfr

mlfjtmnm`atmkj iklfds kiparfl tk jkj-paraiftfr iklfds wmdd bavf grfatfr prffimjfj`f.

Xfnfrfj`fs

Ahhktt, D. O., & Uarcfr, P. (8555). Aulmtkr sfdf`tmkj ajl aulmt `kiimttff `bara`tfrmstm`s.Aulmtmjg? A Okurjad kn

Ura`tm`f & \bfkry, 1=(8), >. bttp?//lx.lkm.krg/15.8052/aul.8555.1=.8.

7/23/2019 Financial Fraud Detection Model: Based on Random Forest

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www.``sfjft.krg/mofn Mjtfrjatmkjad Okurjad kn F`kjkim`s ajl Nmjaj`f kd. 7, Jk. 73 8516

122

Puiifrs, P. D., & Pwffjfy, O. \. (1==2). Nrauludfjtdy imsstatfl nmjaj`mad statfifjts ajl mjsmlfr tralmjg? Aj

fipmrm`ad ajadysms.A``kujtmjg Xfvmfw, 101-1. Xftrmfvfl nrki bttp?//www.ostkr.krg/stahdf/8