电子学报2023，Vol.51Issue(10)：2801-2811,11.DOI:10.12263/DZXB.20220812
基于实时动态图联合学习框架的金融交易风控技术
Real-Time Dynamic Graph Unified Learning Framework for Financial Transaction Risk Management
摘要
Abstract
In recent years,with the continuous escalation of demand in the intelligent financial platforms,the perfor-mance requirements for these relevant application algorithms in financial scenarios have also risen.At present,two genera-tions of frameworks about financial role representation learning have been widely used in the industry.The first-generation framework introduced the unique historical sequence of financial roles,and used the sequence model to learn the historical behavior of the role.The second-generation framework put more emphasis on the interaction between roles,built a real-time dynamic graph system through capital flow,and directly obtained the required real-time features through graph calcula-tion according to predefined business rules,and added them to the follow-up discriminant models.Compared with the first generation,it introduced more interactive information,resulting in a good performance improvement.However,the second-generation framework still has great limitations in terms of timeliness,generalization,and ease of use.In order to solve these problems,we design the third-generation framework which directly builds feature from the original real-time capital flow graph through the dynamic graph learning algorithm,avoiding many problems in the second generation.This paper mainly carries on the innovative design in temporal modeling and frame design.In terms of temporal modeling,we design the C2GAT to flexibly capture high-order structured temporal information on dynamic graphs.In terms of framework mod-eling,we design a real-time dynamic graph framework-RULF,which can better capture and characterize the specific pat-terns existing in capital behavior in real time financial scenarios.We explicitly separate multi-role joint behavior and single-role independent behavior in financial scenarios,and jointly learn multiple subgraph modules to obtain accurate user repre-sentation and performance improvement.A typical interactive financial scenario will be used as a credit cashback example in this article to introduce our design ideas and implementation details in actual business scenarios.关键词
时序建模/实时动态图/图学习/注意力机制/深度学习/系统框架Key words
time encoding/real time dynamic graph/graph learning/attention mechanism/deep learning/system framework分类
信息技术与安全科学引用本文复制引用
周俊,曹月恬,胡斌斌,张志强,陈超超..基于实时动态图联合学习框架的金融交易风控技术[J].电子学报,2023,51(10):2801-2811,11.基金项目
国家自然科学基金(No.72192823,No.62172362)National Natural Science Foundation of China(No.72192823,No.62172362) （No.72192823,No.62172362）
