SG11201810762WA - Dynamic self-learning system for automatically creating new rules for detecting organizational fraud - Google Patents

Abstract

INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property C.--.` 1111111011111111101 1111111111111111111111111111111111111111111111111111111111111110111111 Organization International Bureau (10) International Publication Number 03 (43) International Publication Date ......P' WO 2017/210519 Al 07 December 2017 (07.12.2017) WIP0 I PCT (51) International Patent Classification: (72) Inventor: SAMPATH, Vijay; 30 Wall Street, 8th Floor, G06Q 99/00 (2006.01) New York, NY 10005 (US). (21) International Application Number: (74) Agent: CITTONE, Henry, J.; Cittone & Chinta LLP, 11 PCT/US2017/035614 Broadway, Suite 615, New York, NY 10004 (US). (22) International Filing Date: (81) Designated States (unless otherwise indicated, for every 02 June 2017 (02.06.2017) kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, (25) Filing Language: English CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, (26) Publication Language: English DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JP, KE, KG, KH, KN, KP, KR, (30) Priority Data: KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, 62/344,932 02 June 2016 (02.06.2016) US MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, (71) Applicant: SURVEILLENS, INC. [US/US]; 30 Wall PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, Street, 8th Floor, New York, NY 10005 (US). SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (54) Title: DYNAMIC SELF-LEARNING SYSTEM FOR AUTOMATICALLY CREATING NEW RULES FOR DETECTING OR- GANIZATIONAL FRAUD FIG. 1 RAW DATA THROUGH APACHE STORM BUSINESS INTELLIGENCE + DATA VISUALIZATION —10 • — — • m. 1 — co olc, 1 CLOUDERA \" 1 \"\" RULES ...{ ENGINE IMPALA ALGORITHMS INTEGRATION 1 t a --0- FOR PATTERN DETECTION TO RULES ENGINE —_,— _[ ANALYST WORKBENCH GENERIC AND CUSTOMIZED REPORTS DATA MINING EMAIL EXCHANGE SERVER 1-1 CN (57) : A fraud 1-1 in fraudulent transactions 0 positives by scoring ll This iterative process recalibrates the parameters underlying the scores over time. These parameters are fed into an algorithmic model. .. .. detection system that applies scoring models to process transactions by scoring them is provided. Those transactions which are flagged by this first process are then further them via a second model. Those meeting a predetermined threshold score are then sidelined and sidelines potential processed to reduce false for further review. el --.... Those transactions sidelined after undergoing the aforementioned models are then autonomously processed by a similarity matching IN algorithm. In such cases, where a transaction has been manually cleared as a false positive previously, similar transactions are given 1-1 © the benefit of the prior clearance. Less benefit is accorded to similar transactions with the passage of time. The fraud detection system ei predicts the probability of high risk fraudulent transactions. Models are created using supervised machine learning. C [Continued on next page] WO 2017/210519 Al MIDEDIMOMOIDEIRMEM00110101MHOMOMOVOIMIE (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG). Declarations under Rule 4.17: — of inventorship (Rule 4.17(iv)) Published: — with international search report (Art. 21(3))