Best classification algorithms in peer-to-peer lending

A proper credit scoring technique is vital to the long-term success of all kinds of financial institutions, including peer-to-peer (P2P) lending platforms. The main contribution of our paper is the robust ranking of 10 different classification techniques based on a real-world P2P lending data set. Our data set comes from the Lending Club covering the 2009–2013 period, which contains 212,252 records and 23 different variables. Unlike other researchers, we use a data sample which contains the final loan resolution for all loans. We built our research using a 5-fold cross-validation method and 6 different classification performance measurements. Our results show that logistic regression, artificial neural networks, and linear discriminant analysis are the three best algorithms based on the Lending Club data. Conversely, we identify k-nearest neighbors and classification and regression tree as the two worst classification methods.     

Ownership discrimination and private firms financing in China

This study examines the financing/funding of private firms in China. Our results show that private firms are significantly less funded through formal financing channels such as bank loans than state-owned firms, and hence have to resort to alternative financing such as trade credit. Consistent with the theoretical expectation and literature, there is a substitution effect between trade credit and bank loans for private firms, but this effect is much weaker compared to that of state-owned firms. Moreover, while the univariate comparisons indicate that private firms obtain more notes payable than state-owned firms, the multivariate regression analyses show that the relation between bank loan and notes payable is positive and indifferent between private and state-owned firms.     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

严监管背景下农信社合规风险管理体系建设

2018年,银行业监管环境进一步趋严,不但强调对银行的监管,更提出了对监管人员职责的监管,这种严格的外部监管环境对农信社的合规风险管理带来了极大的挑战。农信社合规风险管理体系的建设和完善已势不容缓。论文提出了农信社合规风险管理体系建设要从战略定位、文化渗透、防线搭建、专业专职化、考核和追究六个维度入手,推进合规风险管理长效机制的建设。     

The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag

The credit risk contagion of Internet peer-to-peer (P2P) lending platforms is an important part of Internet financial risk management and supervision. This study analyzes the contagion path of credit risk in Internet P2P lending. Based on complex network theory and the theory of infectious disease dynamics, the characteristics of Internet P2P lending development are combined to construct a SEIR model of credit risk transmission among Internet P2P lending platforms with time lag, and the robustness of the model is analyzed and proven. The influence of platform correlations, the susceptible immune rate, the platform elimination rate, contagion latency, the saturation coefficient, and the susceptibility input rate on credit risk contagion behavior among Internet P2P lending platforms is analyzed, using the equilibrium point and threshold value. The impact of each variable is analyzed by simulation. Corresponding countermeasures and suggestions are proposed to prevent and control credit risk contagion among these platforms.     

Financial scandals: a historical overview

I examine the incidence of fraud from c.1720 to 2009 and relate it to the occurrence of significant financial scandals. Focusing on the UK, and US prior to Enron, and using a detailed dataset of significant events and news content, underpinned by examination of specific watershed scandals, the paper highlights the regulatory response to scandals and the implications for accounting and financial reporting. The evidence reveals the incidence of fraud and financial scandal to be historically contingent and skewed towards certain sectors, particularly banking and finance, facilitated by complex group structures and international capital mobility, and mediated by managerial incentives and ownership concentration. Financial reporting and auditing can mitigate fraud opportunities in all sectors and businesses without complex group structures, and the accounting profession achieved some success in this respect up to the mid-1970s. Since then, the profession has been increasingly challenged by, and to some degree implicated in, the development of interconnected and international business networks, which, combined with wider financial deregulation, has led to a resurgence of fraud and financial scandal not previously experienced since the mid-nineteenth century.     

加强会计诚信建设 提高会计信息质量

会计信息是国家的宏观经济管理部门、企业经济管理部门及其他方面进行决策的依据。会计信息真实客观与否，直接影响着企业经营管理、国家宏观调控、广大股东的投资决策，势必影响市场经济的有效健康发展。从根本上建立一套与市场经济相适应的会计信息质量保障体系势在必行，而整个体系的建立和健全是一个任重而道远的过程。在这个过程中，会计诚信也成了整个市场经济发展的职业道德规范，笔者就此谈谈几点看法。     

试论二元经济形态下的会计模式

本文分析了在知识经济兴起的环境下我国现行会计模式存在的缺陷,并根据知识经济发展的历程以及我国目前工业经济与知识经济并存的现状,提出了一种能适应两种经济形态的兼容性会计模式,最后指出了目前实施该模式尚存在的制约因素。     

高校财务实行内部会计控制的几点思考

分析了高校实施内部会计控制的背景和存在的主要问题,表述了对高校内部会计控制的方法和关键控制点,提出了解决目前高校内部会计控制存在问题的解决方法和主要对策.     

试析中小型民营家族制企业财务管理问题及对策

近几年来,民营经济在我国经济中的地位越来越突出。该文在分析家族制管理模式的利弊及其对企业财务管理影响的基础上,对中小型民营家族制企业财务管理存在的问题及改善对策进行了探讨。