Two regressions were used to analyse the composition of the interest rate on the primary market and the discount rate on the unregulated secondary market of the Estonian peer-to-peer lending platform Bondora. Furthermore, it was investigated how different dummy variables affect the pricing behaviour on the primary market, and if Bondora fulfills the classic peer-to-peer promises.
What drives pricing behavior in peer-to-peer loan primary and secondary markets? To answer this question, datasets from the P2P platform Bondora are examined. For the pricing behavior on the primary market, the effects of different variables on the interest rate set by the platform on Bondora are tested. The pricing behavior on the secondary market, on the other hand, is investigated regarding the discount rate. It can be used to examine which factors of a loan lead to its shares being sold at a premium or discount to the fundamental value. The regressions revealed that the expected loss has the strongest influence on the interest rate in the primary market. The effect of the expected loss on the interest rate was positive. However, gender also plays an important role in determining the price of a loan, it was found that women pay a significantly smaller interest rate than men. In general, a large part of the variance of the interest rate can be determined with the presented models. In contrast, pricing behavior in the secondary market is not as easy to predict, probably due to irrationality and cognitive limitations. Although all variables in the secondary market regression were significant, the adjusted R2 was very small at 1%. The days since the borrower defaulted had the largest impact on the price in terms of amount. Curiously, more days in default even meant that the loan share was more likely to be sold at a premium.
Table of Contents
1 Introduction
1.1 Motivation
1.2 Literature Review
1.3 Bondora Overview
1.4 Lending on Bondora
1.5 Does Bondora fulfil the classic P2P promises?
2 Main Findings
2.1 The Datasets
2.2 Dummy Regressions
2.3 Primary Market Regression
2.4 Secondary Market Regression
3 Closing Section
3.1 Conclusion
3.2 Limitation
Research Objective and Core Topics
This thesis examines the driving factors of pricing behavior within the peer-to-peer (P2P) lending platform Bondora, specifically analyzing mechanisms in both its primary and secondary markets through regression analysis of borrower and loan characteristics.
- Primary market interest rate determinants
- Secondary market discount rate factors
- Impact of borrower demographics and employment status
- Evaluation of classic P2P platform promises
- Analysis of irrational trading and mispricing patterns
Excerpt from the Book
1.3 Bondora Overview
This chapter gives an insight into the Bondora P2P platform and classifies it in terms of characteristics and processes. Bondora Capital OÜ was founded on March 11th, 2008, and was firstly available for investors in 2009 (Bondora Blog, 2018, March 12th). The company is headquartered in Tallinn, the capital of Estonia, and issued loans amounting to € 615,2 million, according to its statement (Bondora Statistics). Bondora issues loans to borrowers from Estonia, Spain, Finland, and Slovakia only, but lenders from all over the world can lend money to the borrowers on Bondora, through the platform. The parent company of Bondora Capital OÜ, Bondora AS, is regulated by two authorities, namely the Estonian Financial Supervisory Authority for all loans originating from European countries since 21.03.2016 and the Finish Financial Supervisory Authority for loans originating from Finland (Bondora Support [1]).
To borrow money, an applicant sends a loan application, in which personal data, like contact details, socio-demographic data, employment details, income details, and outstanding debts are revealed. Bondora then evaluates, if the loan application fits the company´s lending policy regarding restrictions on age, income, and over-indebtedness of the applicant. If the policy check is positive, the borrower’s credit score is calculated, and a credit offer is made (Bondora Support [2]). Since 2020 the process of customer identification and fraud detection is sourced out to the company Onfindo (Bondora Support [3]). Bondora collects and verifies the applicant´s data simultaneously or immediately after the external identification of the customer and the fraud check. Furthermore, behavioral data from third-party data providers, social networks, and server protocols are considered. All previously collected data is included in the Bondora-Rating. The expected loss after the recovery procedure, within one year, is used to create an expected lifetime cash flow curve. Data collected in periods of an economic downturn are weighted stronger to reflect loan performance in an adverse economic environment (Bondora Support [4]). The interest rate is based on this expected lifetime cash flow. A loan may have a default risk of 10%, which would result in a D-rating. But if it is expected that a lot of money can be recovered during the recovery process, the loan may get a C-Rating (Bondora Rating [5]).
Summary of Chapters
1 Introduction: Provides the motivation for P2P lending, a literature review on relevant research, an overview of the Bondora platform, and an examination of whether Bondora fulfills classic P2P promises.
2 Main Findings: Describes the primary and secondary market datasets, conducts dummy regressions on borrower characteristics, and provides in-depth regression analyses for both markets.
3 Closing Section: Summarizes the study’s findings regarding price determinants and acknowledges limitations encountered during the analysis.
Keywords
P2P lending, Bondora, interest rate, secondary market, discount rate, regression analysis, default risk, pricing behavior, expected loss, financial technology, borrower characteristics, information asymmetry, asset mispricing, loan fulfillment, credit scoring.
Frequently Asked Questions
What is the core focus of this research?
The work investigates the factors that drive pricing behavior for loans on the P2P platform Bondora, distinguishing between original loan issuance in the primary market and trading in the secondary market.
What are the primary fields of study included?
The research covers P2P lending mechanisms, financial regression modeling, loan pricing factors, and the socio-economic determinants of creditworthiness.
What is the central research question?
The study seeks to identify which specific variables dictate interest rate settings on the primary market and discount rate variations on the secondary market for P2P loans.
Which scientific methodology is applied?
The author employs quantitative empirical analysis, specifically performing various regression models (including dummy regressions and z-standardized coefficients) on two large datasets retrieved from Bondora.
What topics are discussed in the main section?
The main section analyzes borrower demographics (gender, education, employment) in relation to interest rates, performs regression analysis on primary and secondary market behavior, and tests for normal distribution of model residuals.
Which keywords best describe this research?
Key terms include P2P lending, Bondora, regression analysis, interest rates, discount rates, pricing behavior, and default risk.
How does Bondora's rating system influence pricing?
Bondora's platform sets interest rates based on an internal rating system, which is heavily influenced by calculated expected loss and predicted recovery success rates rather than direct lender-borrower negotiation.
What conclusions are reached regarding the secondary market?
The study concludes that secondary market pricing is often influenced by irrationality and cognitive limitations, as the regression model explains only a small fraction (1%) of the variance in discount rates.
- Quote paper
- Tillmann Klapper (Author), 2022, What Drives Pricing Behavior in Peer-to-Peer Loan Primary and Secondary Markets?, Munich, GRIN Verlag, https://www.grin.com/document/1458846
