Patent SG-11201907663X-A (SG)
Title: Method and device for constructing scoring model and evaluating user credit
Inventor: ZHAO XING
IPC: G06Q40/02
Filed: 2018-03-22
Abstract: I10Collecting sample data comprising a plurality of sample datasets 5120: For each characteristic variable, acquiring an interaction with each of one or more variables index of the characteristic variable other characteristic I Determining a clustering .5 . 30-. index of the characteristic the imeraction indices variable according to 5140: According to the clustering indices of the characteristic variable from at least variable variables, selecting a target characteristic one characteristic 5150 - According to the target characteristic variable and a value, dividing a plurality of of sample data subgroups corresponding characteristic sample datasets into a plurality S160 - Constructing a corresponding sub-scoring model for each data subgroups of the sample FIGURE 1 W O 20 18/ 183069 Al (12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (43) International Publication Date 04 October 2018 (04.10.2018) W I PO I PCT omit VIII °nolo OH mil noionomo oimIE (10) International Publication Number WO 2018/183069 Al (51) International Patent Classification: G06Q 40/02 (2012.01) (21) International Application Number: PCT/US2018/023692 (22) International Filing Date: 22 March 2018 (22.03.2018) (25) Filing Language: English (26) Publication Language: English (30) Priority Data: 201710188752.9 27 March 2017 (27.03.2017) CN (71) Applicant: ALIBABA GROUP HOLDING LIMITED [ /US]; Fourth Floor, One Capital Place, P.O. Box 847, George Town, Grand Cayman (KY). (72) Inventor: ZHAO, Xing; 5/F Building 3, 969 West Wen Yi Road, Yu Hang District, Hangzhou, 311121 (CN). (74) Agent: CHEN, Weiguo; Sheppard Mullin Richter & Hampton LLP, 379 Lytton Ave., Palo Alto, CA 94301 (US). (81) Designated States (unless otherwise indicated, for every kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, 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. (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). Published: — with international search report (Art. 21(3)) (54) Title: METHOD AND DEVICE FOR CONSTRUCTING SCORING MODEL AND EVALUATING USER CREDIT (57) : Systems and methods for constructing a scoring model and evaluating user credit. An example method for constructing a scoring model may comprise: collecting a plurality of sample datasets, each sample dataset comprising at least one characteristic variable and a corresponding charac- teristic value; for each characteristic variable, acquiring an interaction index of the characteristic variable with each of one or more other characteristic variables, and determining a clustering index of the characteristic variable according to the interaction indices; selecting a target characteristic variable from the at least one characteristic variable according to the clustering in- dices of the characteristic variables; dividing the plurality of sample datasets into a plurality of sample dataset subgroups according to the target charac- teristic variable and the corresponding characteristic value; and constructing a corresponding sub-scoring model for each of the sample dataset subgroups.