EP 3596685 A1 20200122 - DETECTION BY MACHINE LEARNING OF ANOMALIES IN A SET OF BANKING TRANSACTIONS BY OPTIMIZATION OF THE AVERAGE PRECISION
Title (en)
DETECTION BY MACHINE LEARNING OF ANOMALIES IN A SET OF BANKING TRANSACTIONS BY OPTIMIZATION OF THE AVERAGE PRECISION
Title (de)
ERKENNUNG VON ANOMALIEN IN EINER REIHE VON BANKGESCHÄFTEN DURCH MASCHINENLERNEN MITTELS OPTIMIERUNG DER DURCHSCHNITTLICHEN GENAUIGKEIT
Title (fr)
DÉTECTION PAR APPRENTISSAGE AUTOMATIQUE D'ANOMALIES DANS UN ENSEMBLE DE TRANSACTIONS BANCAIRES PAR OPTIMISATION DE LA PRÉCISION MOYENNE
Publication
Application
Priority
- FR 1752142 A 20170316
- FR 2018050544 W 20180309
Abstract (en)
[origin: WO2018167404A1] The invention relates to a method for detecting anomalies in a set of payment transactions, consisting of: - establishing (E3) a meta-model formed from a set of models, each trained on a training set in order to determine a risk for each transaction of being anomalous, the meta-model being established by the "gradient boosting" technique so as to optimize a differentiable function expressing the average precision of the meta-model; - submitting (E4) said set to the meta-model so as to determine risks for each transaction of said set, and - determining a subset of transactions corresponding to a risk that is greater than a determined threshold in order to provide a predetermined number of transactions in said subset.
IPC 8 full level
G06Q 20/40 (2012.01)
CPC (source: EP)
G06Q 20/4016 (2013.01)
Citation (search report)
See references of WO 2018167404A1
Designated contracting state (EPC)
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR
Designated extension state (EPC)
BA ME
DOCDB simple family (publication)
WO 2018167404 A1 20180920; CN 110678890 A 20200110; EP 3596685 A1 20200122; FR 3064095 A1 20180921; FR 3064095 B1 20190614
DOCDB simple family (application)
FR 2018050544 W 20180309; CN 201880024752 A 20180309; EP 18712980 A 20180309; FR 1752142 A 20170316