Alternative data in fnance and business:emerging applications and theory analysis(review)  

作　　者：Yunchuan Sun Lu Liu Ying Xu Xiaoping Zeng Yufeng Shi Haifeng Hu Jie Jiang Ajith Abraham 

机构地区：[1]International Institute of BigData in Finance,Business School,Beijing Normal University,Beijing 100875,China [2]Institute for FinancialStudies,Shandong University,Jinan 250100,China [3]Business School,Beijing NormalUniversity,Beijing 100875,China [4]Machine Intelligence ResearchLabs(MIR Labs),ScientifcNetwork for Innovationand Research Excellence Auburn,Auburn,Washington 98071,USA

出　　处：《Financial Innovation》2024年第1期32-63,共32页金融创新(英文)

基　　金：sponsored by the National Natural Science Foundation of China(72371032);the National Key Research and Development Program of China(2023YFC3305401).

摘　　要：In the financial sector,alternatives to traditional datasets,such as financial statements and Securities and Exchange Commission filings,can provide additional ways to describe the running status of businesses.Nontraditional data sources include individual behaviors,business processes,and various sensors.In recent years,alternative data have been leveraged by businesses and investors to adjust credit scores,mitigate financial fraud,and optimize investment portfolios because they can be used to conduct more in-depth,comprehensive,and timely evaluations of enterprises.Adopting alternative data in developing models for finance and business scenarios has become increasingly popular in academia.In this article,we first identify the advantages of alternative data compared with traditional data,such as having multiple sources,heterogeneity,flexibility,objectivity,and constant evolution.We then provide an overall investigation of emerging studies to outline the various types,emerging applications,and effects of alternative data in finance and business by reviewing over 100 papers published from 2015 to 2023.The investigation is implemented according to application scenarios,including business return prediction,business risk management,credit evaluation,investment risk prediction,and stock prediction.We discuss the roles of alternative data from the perspective of finance theory to argue that alternative data have the potential to serve as a bridge toward achieving high efficiency in financial markets.The challenges and future trends of alternative data in finance and business are also discussed.

关 键 词：Alternative data Behavioral data Commercial data Credit evaluation Enterprise management Finance innovation INVESTMENT Market efciency Priceprediction Risk evaluation Sensing data 

分 类 号：F22[经济管理—国民经济]