Overview
AI inobatsira mabhanga kuona chikamu chidiki chekutengeserana chinovanza mari yematsotsi pakati pemabhiriyoni ezviri pamutemo. Izvo zvine basa nekuti legacy-yakavakirwa masisitimu inosimudzira yakawandisa isina mhosva kutengeserana, kutambisa nguva yevaongorori uye kurega kubira chaiko kuchipfuura.
AI muAnti-Money Laundering inoshandisa AI munharaunda-yakananga nharaunda umo mirau, mashandiro, uye kushivirira njodzi zvinogadzirisa zvakanyanya sarudzo dzekugadzira.
Deep Dive
Anti-money laundering (AML) ndiyo nzira iyo mabhanga anoona nayo mari yakasungirirwa kumhosva dzakadai sekutengesa zvinodhaka, hutsotsi, uye hugandanga. Masisitimu echinyakare anoshandisa mirau yakatarwa - semuenzaniso, mureza chero dhipoziti yemari inodarika zviuru gumi zvemadhora - izvo zvinoburitsa huwandu hukuru hwema alarm enhema (kazhinji 90-95% yechenjedzo dzakafa magumo). AI inoshandura maitiro nekudzidza maitiro akajairwa anotaridzika kune wega mutengi uye kuona kutsauka. Mamodheru ekudzidza emuchina anowana kutengeserana nenjodzi, nepo magirafu ekuongorora mepu yakavanzika network yeakaundi inofambisa mari munzira dzakabatana. Kugadziriswa kwemutauro wechisikigo kunoongorora nhau uye rondedzero yezvirango panguva ye 'Ziva Mutengi Wako'. Chinangwa ndechekuita mashoma emanyepo, kuferefeta nekukurumidza, uye kubata zvirongwa zvakaomarara - senge 'smurfing' (kupatsanura mari yakawanda kuita madiki madiki ekuchinjisa) - izvo zvikumbaridzo zviri nyore zvinopotsa zvachose.
Technical Insight
Maitiro maviri anotonga. Mamodheru anotariswa (miti inokwidziridzwa-gradient, neural nets) dzidza kubva kune dzakapfuura dzakasimbiswa-makesi ekugezesa kuhwina matransaction matsva. Asi hutsotsi hwakanyorwa hahuwanzo, saka kutariswa kusingatarisirwi kusingatarisirwi uye graph neural network zvine basa zvakare: vanotevedzera maakaundi semanodhi uye anotamiswa semapendero, achiburitsa mhete, manyurusi network, uye mapatani ekuisa hapana mutemo weakaundi imwe chete waigona kuona. Entity resolution inobatanidza aliases uye makambani egomba mhiri kwedata silos saka tsotsi rimwe haribatwe sevatengi gumi vasina hukama.
Kubata AI muAnti-Mari Kubira
AI inobatsira mabhanga kuona chikamu chidiki chekutengeserana chinovanza mari yematsotsi pakati pemabhiriyoni ezviri pamutemo. Izvo zvine basa nekuti legacy-yakavakirwa masisitimu inosimudzira yakawandisa isina mhosva kutengeserana, kutambisa nguva yevaongorori uye kurega kubira chaiko kuchipfuura. AI muAnti-Money Laundering inoshandisa AI munharaunda-yakananga nharaunda umo mirau, mashandiro, uye kushivirira njodzi zvinogadzirisa zvakanyanya sarudzo dzekugadzira. Kuvaka kunzwisisa kwakadzama, bata AI muAnti-Money Laundering semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodikanwa, kujekesa fungidziro, uye patsanura zvinogona kuitwa nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa AI muAnti-Money Laundering inonanisa kugona kwehunyanzvi nedomendi mutemo, kutarisika, uye kumberi kwekuita sarudzo. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Mamiriro eindasitiri anosarudza kana mazano eAI achirarama nekusangana neicho chaicho. Panguva imwecheteyo, Regulatory zvinodiwa zvinogona kusashanda neimwe nzira yakasimba prototypes. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Mamiriro eindasitiri anosarudza kana mazano eAI achirarama nekusangana neicho chaicho.
Mamiriro eindasitiri anosarudza kana mazano eAI achirarama nekusangana neicho chaicho. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Zvisungo zveDomain zvinopesvedzera mwero wezvikanganiso zvinogamuchirika uye mamodheru etarisiro.
Zvisungo zveDomain zvinopesvedzera mwero wezvikanganiso zvinogamuchirika uye mamodheru etarisiro. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Kuendesa kwakabudirira kunonanisa kugona kwehunyanzvi nekumberi kwekufambiswa kwebasa.
Kuendesa kwakabudirira kunonanisa kugona kwehunyanzvi nekumberi kwekufambiswa kwebasa. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
HSBC yakabatana ne Google Cloud kutumira AI iyo inonzi yakawana 2-4x zvimwe zviitiko zvekufungira apo vachicheka chenjedzo dzenhema, vachiongorora mazana emamiriyoni ekutengeserana pamwedzi.
Mabhangi anoshandisa graph analytics kufumura 'mule network' apo munhu mumwechete anotora akawanda maakaundi kuisa uye kutamisa mari dzakabiwa.
NLP-inotungamirwa zita rekuongorora rinotarisa vatengi vachipesana nezvirango zvepasirese uye zvematongerwo enyika-zvakafumurwa-munhu runyorwa, kubata kusiyanisa zviperengo uye aliases mumaarufabheti.
Kudzidza kwemuchina njodzi-yakawanda waya kutamiswa munguva chaiyo saka kuchinjisa $9,800 (kungori pasi pechikumbaridzo chekuzivisa) kunodzokororwa mumaakaundi mazhinji kunokonzeresa chenjedzo.
Maitiro Ekuita
AI muAnti-Mari Kubira mukuita
HSBC yakabatana ne Google Cloud kutumira AI iyo inonzi yakawana 2-4x zvimwe zviitiko zvekufungira apo vachicheka chenjedzo dzenhema, vachiongorora mazana emamiriyoni ekutengeserana pamwedzi.
HSBC yakabatana neGoogle Cloud kuendesa AI inonzi yakawana 2-4x zvimwe zviitiko zvinofungirwa uku ichicheka chenjedzo dzenhema, kuongorora mazana emamiriyoni ekutengeserana pamwedzi Matimu anowanzo kuwana mibairo iri nani kana achitsanangura mabindu emhando kumberi, chengetedza nzira yekukwira kwemunhu kune zvese zviri zviviri mutengo wemhosho, uye kuronda zviitiko zvechigadzirwa.
AI muAnti-Mari Kubira mukuita
Mabhangi anoshandisa graph analytics kufumura 'mule network' apo munhu mumwechete anotora akawanda maakaundi kuisa uye kutamisa mari dzakabiwa.
Mabhangi anoshandisa graph analytics kufumura 'manyurusi network' apo munhu mumwe anotora akawanda maakaundi kuti aise uye kutamisa mari dzakabiwa Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye kukanganisa mutengo nekufamba kwenguva.
AI muAnti-Mari Kubira mukuita
NLP-inotungamirwa zita rekuongorora rinotarisa vatengi vachipesana nezvirango zvepasirese uye zvematongerwo enyika-zvakafumurwa-munhu runyorwa, kubata kusiyanisa zviperengo uye aliases mumaarufabheti.
NLP-inotyairwa zita rekuongorora rinotarisa vatengi vachipesana nezvirango zvepasi rose uye nezvematongerwo-zvakafumurwa-munhu runyorwa, kubata kusiyanisa zviperengo uye zviperengo mumaarufabheti Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
AI muAnti-Mari Kubira mukuita
Kudzidza kwemuchina njodzi-yakawanda waya kutamiswa munguva chaiyo saka kuchinjisa $9,800 (kungori pasi pechikumbaridzo chekuzivisa) kunodzokororwa mumaakaundi mazhinji kunokonzeresa chenjedzo.
Kudzidza kwemuchina njodzi-inopa waya kutamiswa munguva chaiyo saka kuchinjisa $9,800 (ingori pasi pechikumbaridzo chekuzivisa) kudzokororwa mumaakaundi mazhinji kunokonzeresa yambiro yekunyepedzera Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura hunhu kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa nemitengo yekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
Regulatory zvinodiwa zvinogona kukanganisa zvimwe zvakasimba prototypes.
Nhoroondo yenhoroondo inogona kubatanidza kurerekera kunokuvadza nharaunda dzakati.
Nhaka masisitimu anogona kugadzira mabhodhoro ekubatanidza uye mitengo yakavanzika.
Implementation Roadmap
Batanidza domain nyanzvi kubva pakugadzirisa dambudziko kusvika pakuongorora.
Batanidza domain nyanzvi kubva pakugadzirisa dambudziko kusvika pakuongorora. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Dhizaina nzira dzekuongorora uye zvinyorwa zvisati zvatanga.
Dhizaina nzira dzekuongorora uye zvinyorwa zvisati zvatanga. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Gadzirisa zvisungo zvekuteedzera uye kuchengetedza nekukurumidza.
Gadzirisa zvisungo zvekuteedzera uye kuchengetedza nekukurumidza. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Buritsa muzvikamu zvine kujeka kumira uye kudzoreredza maitiro.
Buritsa muzvikamu zvine kujeka kumira uye kudzoreredza maitiro. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.