Dorothea Schäfer

Is Crowdfunding Different? Evidence on the Relation between Gender and Funding Success from a German Peer-to-Peer Lending Platform

Abstract According to the literature on traditional banking, lenders often discriminate against female borrowers. However, studies of peer-to-peer lending in the United States find that female borrowers have better chances of obtaining funds than do males. We provide evidence on the success of female borrowers at a large German peer-to-peer lending platform. Our results show that there is no effect of gender on the individual borrower’s chance to receive funds on this platform, ceteris paribus. Several robustness checks confirm this finding. Hence, female discrimination seems to be eased by the ‘wisdom of the lending crowd’.

Predicting Bankruptcy with Support Vector Machines

The purpose of this work is to introduce one of the most promising among recently developed statistical techniques – the support vector machine (SVM) – to corporate bankruptcy analysis. An SVM is implemented for analysing such predictors as financial ratios. A method of adapting it to default probability estimation is proposed. A survey of practically applied methods is given. This work shows that support vector machines are capable of extracting useful information from financial data, although extensive data sets are required in order to fully utilize their classification power.

Banking Competition, Good or Bad?: The Case of Promoting Micro and Small Enterprise Finance in Kazakhstan

Competition is claimed to be beneficial in development projects promoting micro and small enterprise finance although there are still doubts as to whether these loans can be developed into a profitable business. Our research sheds new light on the question of how many MSE banking units should optimally be created and supported in a certain region. We employ a unique data set from the European Bank for Reconstruction and Development for Kazakhstan, and investigate which strategy contributes more to the overall success of the programme: a strategy of setting up several competing banks or a strategy of establishing regional monopolies. ‘Competition is the most important principle on which our strategy is based. As in any other market, effective competition provides incentives for banks to offer market-based and demand-oriented financial services. Competition encourages the development of better products and services at lower cost.’ (Matthäus-Maier and von Pischke, 2004, p. 1).

Estimating Probabilities of Default with Support Vector Machines

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on Deutsche Bundesbank data. In particular we discuss the selection of variables and give a comparison with more traditional approaches such as discriminant analysis and the logit regression. The results demonstrate that the SVM has clear advantages over these methods for all variables tested.

Graphical data representation in bankruptcy analysis

Graphical data representation is an important tool for model selection in bankruptcy analysis since the problem is highly non-linear and its numerical representation is much less transparent. In classical rating models a convenient representation of ratings in a closed form is possible reducing the need for graphical tools. In contrast to that non-linear non-parametric models achieving better accuracy often rely on visualisation. We demonstrate an application of visualisation techniques at different stages of corporate default analysis based on Support Vector Machines (SVM). These stages are the selection of variables (predictors), probability of default (PD) estimation and the representation of PDs for two and higher dimensional models with colour coding. It is at this stage when the selection of a proper colour scheme becomes essential for a correct visualisation of PDs. The mapping of scores into PDs is done as a non-parametric regression with monotonisation. The SVM learns a non-parametric score function that is, in its turn, non-parametrically transformed into PDs. Since PDs cannot be represented in a closed form, some other ways of displaying them must be found. Graphical tools give this possibility.

Does Gender Affect Funding Success at the Peer-to-Peer Credit Markets? Evidence from the Largest German Lending Platform

Studies of peer-to-peer lending in the USA find that female borrowers have better chances of getting funds than males. Is differential treatment of borrowers of different sexes a common feature of peer-to-peer lendingmarkets or is it subject to specific businessmodels, ways of fixing loan contracts and even national financial systems? We aim at answering this question by providing evidence on loan procurement at the largest German peer-to-peer lending platform Smava.de. Our results show that gender does not affect individual borrowers chances of funding success on this platform, ceteris paribus. Hence, gender discrimination seems to be a platform-specific phenomenon rather than a common attribute of this innovative form of credit markets.

Financial Risk Aversion and Household Asset Diversification

This paper explores the relationship between risk attitude and asset diversification in household portfolios. We first examine the impact of manifested risk aversion on the total number of distinct assets held in a portfolio (naive diversification). The second part of the paper focuses on a more sophisticated strategy of diversification and asks whether financial theory is compatible with observed diversification patterns. Based on the German Socioeconomic Panel which provides unique measures of individual propensity for taking risk, the results of the regression analysis show that, along with some socioeconomic characteristics, the propensity for taking investment risk is an important predictor of a households diversification strategy. However, some of our findings are strongly at odds with what the concept of mean-variance utility suggests.

Financial Transaction Tax Contributes to More Sustainability in Financial Markets

We argue that a financial transaction tax complements financial market regulation. With the tax, governments have an additional instrument at hand to influence trading activity. FTT aims to reduce regulatory arbitrage, flash trading, overactive portfolio management, excessive leverage and speculative transactions of financial institutions. The focus clearly addresses these classes of activities that have contributed to the financial crisis. However, if contrary to expectations harmful transactions will not be curbed, FFT generates at least large tax revenues that can contribute to cover the costs of the financial crisis. The trend towards centralized clearing and depositaries makes tax evasion more difficult than it was in the past. Tax avoidance is, of course, never completely avoidable. Therefore the effect of the tax should be monitored closely so that governments can react quickly if tax loopholes and taxinduced geographical relocation plans of financial institutions come to light.

The Default Risk of Firms Examined with Smooth Support Vector Machines

In the era of Basel II a powerful tool for bankruptcy prognosis is vital for banks. The tool must be precise but also easily adaptable to the banks objections regarding the relation of false acceptances (Type I error) and false rejections (Type II error). We explore the suitabil- ity of Smooth Support Vector Machines (SSVM), and investigate how important factors such as selection of appropriate accounting ratios (predictors), length of training period and structure of the training sample in°uence the precision of prediction. Furthermore we show that oversampling can be employed to gear the tradeo® between error types. Finally, we illustrate graphically how di®erent variants of SSVM can be used jointly to support the decision task of loan o±cers.

Entrepreneurship, Windfall Gains and Financial Constraints: The Case of Germany

In this paper we investigate the link between entrepreneurship and financial constraints. We develop a dynamic partial equilibrium model of an individual utility maximization that predicts that the person is more likely to start her business when financial constraints are eased. We test this hypothesis using German Socio-Economic Panel data covering the periods 2000 - 2002 and measure release from financial constraints by windfall gains. The estimates confirm that the individual has higher propensity to start her business when she gets windfall gains. Furthermore, there are stronger effects for persons that have sufficient, but not very high levels of income and abilities.