中圖分類號： TP38
文獻標識碼： A
DOI： 10.20044/j.csdg.2097-1788.2022.03.002
引用格式： 文凱，馬寅，王鵬，等. 基于光量子計算的信用評分特征篩選研究報告[J].網絡安全與數據治理，2022，41(3)：13-18.

Research report on feature screening of credit scoring based on photonic quantum computing

Abstract： With the progress of science and technology, quantum computing has broken through the traditional bottleneck of computing power and is playing an increasingly important role in various fields. In the financial field, the credit scoring scenario is the top priority of the loan industry. Feature selection can build simpler and easier-to-understand models, improve data mining performance, prepare concise and understandable data to extract effective features and reduce data dimensions, and provide effective loan reference information for the financial industry. This paper mainly discusses the application of quantum computing in the credit scoring scenario, improves the financial data preprocessing method, and creatively uses quantum computer to solve the QUBO model of feature selection. Compared with one-hot encoding, the WOE strategy used in this paper can directly analyze the features, and the screening results can be directly compared. Compared with the traditional feature selection strategy based on correlation, the feature selection strategy based on quantum computing is little difference. Moreover, due to the inherent advantages of quantum computer, this strategy is faster and more promising.

Key words : quantum computing；feature selection；correlation；credit evaluation