Asymmetric effects of housing wealth on college enrolment

We investigate the impact of housing wealth, credit availability and financial distress on college enrolment decisions. We find that housing wealth is negatively related to enrolment in public schools and positively related to enrolment in private schools. This evidence suggests that, on average, students substituted away from private schools towards public institutions during the recent financial crisis.     

The provision of long-term credit and firm growth in developing countries

Do small and young firms benefit from an increase in the provision of long-term loans? By combining firm-level data from 62 countries (over the period 2006–2016) with a new database on short-term and long-term credit provided to the private sector, this article shows a higher provision of long-term credit does not stimulate growth of small and young firms. On the contrary, an increase in the availability of short-term credit spurs firm growth. The main explanation of this (counter-intuitive) result is the differential impact of short-term and long-term credit provision on small and young firms’ access to credit. Young and small firms are able to take advantage of an increase of short-term loans, which allow them to switch from informal finance to bank loans. However, a higher level of long-term credit does not alleviate credit constraints faced by opaque firms because these funds are allocated towards transparent borrowers.     

Will FinTech make regional banks superfluous for small firm finance? Observations from soft information-based lending in Germany

Regional banks have a competitive advantage in that short distances to clients enable the use of soft information for superior lending decisions. If the ambition of FinTech start-ups to create superior screening and monitoring technologies materialises, this advantage would be diminished and regional banks would become superfluous for small firm finance. To explore this claim, the paper in hand analyses qualitative empirical data about the lending processes and rating system use of regional German savings banks. In essence, the results from participant observation and interviews clarify the importance of “real” soft information for critical lending decisions. The context specificity and limited verifiability of “real” soft information hamper it from being hardened through the use of rating systems and other bank-ICT. Though FinTech's scoring technologies may overcome the first limitation, it appears likely that in the course of scoring development “real” soft information will be systematically crowded out due to the manipulation problem. The paper expects improved access to finance for SMEs if FinTech solutions overcome both limitations of “real” soft information use, or if peer-to-peer lending and regional banks coexist. Deteriorated access to finance is expected if FinTech companies displace the relationship banking of regional banks due to enhanced competition, without preserving the advantages of “real” soft information with superior screening and monitoring technologies. The paper concludes with recommendations on how to prevent deteriorated access to finance for small firms by promoting fair competition and FinTech innovations.     

The angel investment decision: insights from Australian business angels

While much has been written about the investment criteria of business angels, few studies explore why these particular criteria are important to them. The Australian context has a diverse range of actors along with complex jurisdictional arrangements, making for an interesting background for investigation of the angel finance phenomenon. We examine 12 business angels in the rapidly changing Australian context and use nine corroborating participants to validate responses and identify four key drivers – personal experience, trust, the need to contribute and realistic expectations – that influence business angels during the initial investment process.     

互联网视角下供应链金融的新发展

在这个网络社会愈发深化的时代,通过互联网科技完善和发展线上供应链金融成为必要的发展方向。本文首先梳理了传统供应链金融的基本模式,发现了其存在的不足;然后重点介绍了当前三种主要的线上供应链金融模式,总结了线上供应链金融的优势;最后,提出相关政策建议,认为金融机构应该不断升级线上供应链金融产品,逐步完善供应链金融线上操作系统,监管机构需要出台更加严格的监管规则对线上供应链金融进行有效监管。     

Dynamic response of bank-intermediated trade finance to a global liquidity shock

This paper investigates the bank-level responses of a bank-intermediated instrument of trade finance to a negative global liquidity shock in Korea. Using a factor-augmented vector autoregression approach, the results show that there exists significant heterogeneity in bank-level trade-finance responses to a global liquidity shock. In addition, we find that the source of the heterogeneity is the bank-level foreign currency liquidity condition; banks with a better foreign currency liquidity condition may dampen the negative impact of a global liquidity shock on trade-finance.     

External funding of major capital projects in the UK Higher Education sector: issues of demand,supply and market timing?

The aim of this paper is to consider the sources of finance used to support major capital expenditure in the UK Higher Education sector and to reflect on any differences between traditional corporate finance theory and practice in the UK university sector. Utilising both HESA data returns and published annual accounts, an in-depth analysis using a logit structure is carried out on data from the top 63 UK universities over the period 2014–2017, to establish the range of funding sources adopted for major capital projects, all set within the context of the UK macro environment and a period of low interest rates. The research also carries out a survey of funders to understand the decision criteria used by lenders active in the Higher Education sector and a survey of university finance directors to determine the use of the funds, the reasons behind past lending decisions and to ascertain likely future demand for finance to fund major capital projects.     

国有企业如何做好投资项目财务风险管理

作为国有企业经营管理的重要组成部分,财务风险管理对于投资项目经济效益的保障具有积极作用。论文在阐述国有企业投资项目财务风险管理必要性的基础上,就现阶段财务风险管理的问题展开分析,并指出国有企业投资项目财务风险管理的策略。期望能进一步提升财务风险管理质量,确保投资项目资金运行的安全性,进而促进国有企业的进一步发展。     

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.