Consumer marketplace lending in Australia: Credit scores and loan funding success

2019 ◽  
Vol 45 (4) ◽  
pp. 607-623
Author(s):  
Andrew Grant ◽  
Luke Deer
Keyword(s):  
Decision Tree ◽  
Decision Process ◽  
Jel Classification ◽  
Third Party ◽  
Credit Score ◽  
Second Stage ◽  
Funding Success ◽  
Credit Scores ◽  
Unique Dataset

This article examines borrower acceptance in consumer marketplace lending using a unique dataset from the largest platform in Australia, Society One. Applications are initially filtered through an automated decision tree based on a third-party Veda (Equifax) credit score. At the second stage of assessment, loan applications are underwritten by the platform before being offered to sophisticated investors for purchase. The platform accepts around 11% of completed applications, with around 55% declined by an automated decision process and the remaining 34% by the manual underwriting process. More than 80% of purchased loans were made to borrowers with credit scores classed as ‘Good’, ‘Very Good’ or ‘Excellent’ (the threshold for ‘Good’ being a score of 622). However, underwriters decline around two-thirds of these higher credit score applicants, showing the importance of the underwriting process to the platform’s growth. JEL Classification: G21, G23, D14, D45, D82

scholarly journals Financial Education versus Costly Counseling: How to Dissuade Borrowers from Choosing Risky Mortgages?

2020 ◽  
Vol 12 (1) ◽  
pp. 1-32
Author(s):  
Sumit Agarwal ◽  
Gene Amromin ◽  
Itzhak Ben-David ◽  
Souphala Chomsisengphet ◽  
Douglas D. Evanoff
Keyword(s):  
High Risk ◽  
Consumer Choice ◽  
Financial Education ◽  
Third Party ◽  
Credit Score ◽  
Contract Choice ◽  
Credit Scores

This paper explores the effects of mandatory third-party review of mortgage contracts on consumer choice. The study is based on a legislative pilot carried out in Illinois in 2006, under which mortgage counseling was triggered by applicant credit scores or by their choice of “risky mortgages.” Low-credit score applicants for whom counselor review was mandatory did not materially alter their contract choice. Conversely, higher credit score applicants who could avoid counseling by choosing nonrisky mortgages did so, decreasing their propensity for high-risk contracts between 10 and 40 percent. In the event, one of the key goals of the legislation—curtailment of high-risk mortgage products—was only achieved among the population that was not counseled. (JEL D14, D18, G21, R21)

COMMENTARY: Beyond the Black Box Revisited: Algorithmic Trading and TCA Analysis Using Excel

2018 ◽  
Keyword(s):  
Decision Process ◽  
Investment Decision ◽  
Black Box ◽  
Third Party ◽  
Algorithmic Trading ◽  
Impact Model ◽  
Market Impact ◽  
Proprietary Information ◽  
Analysis Techniques ◽  
Trading Decisions

In this paper we revisit techniques from “Creating Dynamic Pre-Trade Models: Beyond the Black Box” (Kissell, 2011) which was awarded The Journal of Trading’s Best Paper of the Year Award in 2011. We provide investors a pre-trade of pre-trade modeling technique that can be used to decipher broker and vendor models, and to calibrate a customized investor specific market impact model. We also provide a suite of Excel TCA Add-In functions that can incorporate investor specific market impact parameters and allow investors to perform TCA analysis on their own desktops within Excel, and with the added level of security and comfort that their investment decision process will not be reverse engineered because they do not need to upload or transmit any of their proprietary information and valuable trade information to a third-party website or API for analysis. Techniques in this paper enable investors to create their own customized TCA analyses within Excel to assist with both trading decisions and portfolio analysis and optimization.

scholarly journals Using Credit Scores to Predict and Analyze Areas of Gentrification and Urban Development in Toronto, Canada - a Geo-Spatial Approach

2021 ◽  
Author(s):  
Nicholas Pulsone ◽  
Brian Ceh
Keyword(s):  
Spatial Analysis ◽  
Urban Development ◽  
Well Being ◽  
Development Zone ◽  
Credit Score ◽  
Spatial Approach ◽  
Credit Scores ◽  
The City ◽  
Analytical Frameworks ◽  
Regent Park

This study examines the use of financial well-being indicators such as credit scores to identify gentrification. This study is a response to the redevelopment of neighbourhoods in the City of Toronto through gentrification. This study also explores both theoretical and analytical frameworks outlined in literature to identify correlations between financial wellbeing indicators and gentrification. Comparing the observations in this study to areas experience gentrification such as Regent Park revealed large implications that gentrification is largely associated with financial wellbeing. The study also found that the average credit scores in the City of Toronto seem to be increasing. The analysis determined that the credit score changes reflected the development in the Regent Park development zone. Key words: Gentrification, credit scores, spatial analysis, urban development

Using I-D maps to Represent the Adoption of Internet Applications by Local Cricket Clubs

2011 ◽  
pp. 80-94 ◽  
Author(s):  
Scott Bingley ◽  
Steven Burgess
Keyword(s):  
Decision Process ◽  
Third Party ◽  
The Internet ◽  
Internet Applications ◽  
Visual Aid ◽  
Use Of The Internet ◽  
The Uk ◽  
Use Of Internet ◽  
Online Statistics ◽  
Different Levels

This chapter describes the development of a visual aid to depict the manner in which Internet applications are being diffused through local sporting associations. Rogers’ (2003) Innovation-Decision process stages, specifically the knowledge, persuasion, adoption and confirmation stages, are used as the theoretical basis for the aid. The chapter discusses the Innovation-Decision process as an important component of Rogers’ (2003) Innovation Diffusion approach. It then outlines the particular problem at hand, determining how best to represent different sporting (cricket) associations and their adoption and use of Internet applications across the innovation-decision process stages. Different data visualisation approaches to representing the data (such as line graphs and bar charts) are discussed, with the introduction of an aid (labelled I-D maps) used to represent the adoption of different Internet applications by cricket associations in New Zealand, Australia and the UK. The Internet applications considered are email, club websites, association and/or third party websites and the use of the Internet to record online statistics. The use of I-D maps provides instant interpretation of the different levels of adoption of Internet applications by different cricket associations.

scholarly journals Blockchain-Based ICOs: Pure Hype or the Dawn of a New Era of Startup Financing?

2018 ◽  
Vol 11 (4) ◽  
pp. 80 ◽  
Author(s):  
Lennart Ante ◽  
Philipp Sandner ◽  
Ingo Fiedler
Keyword(s):  
Social Media ◽  
Human Capital ◽  
Venture Capital ◽  
Business Model ◽  
Model Quality ◽  
New Era ◽  
Relative Ease ◽  
Funding Success ◽  
Rapid Pace ◽  
Unique Dataset

This study explores the determinants of initial coin offering (ICO) success, where success is defined as the amount of capital a project could raise. ICOs are a tool for startups in the blockchain ecosystem to raise early capital with relative ease. The market for ICOs has grown at a rapid pace since its start in 2013. We analyze a unique dataset of 278 projects that finished their ICOs by August 2017 to assess determinants of funding success that we derive from the crowdfunding and venture capital literature. Our results show that ICOs exhibit similarities to classical crowdfunding and venture capital markets. Specifically, we identify resemblances in determinants of funding success regarding human capital characteristics, business model quality, project elaboration, and social media activity.

scholarly journals Entry Barriers and Nonprofit Founding Rates: An Examination of the Milwaukee Voucher School Population

2017 ◽  
Vol 8 (1) ◽  
pp. 71-90 ◽  
Author(s):  
Fredrik O. Andersson ◽  
Michael Ford
Keyword(s):  
Third Party ◽  
Entry Barriers ◽  
Barriers To Entry ◽  
Approval Process ◽  
Success Rates ◽  
Institutional Barriers ◽  
School Population ◽  
Voucher Schools ◽  
Entrepreneurial Efforts ◽  
Unique Dataset

AbstractIn this study we examine how formal barriers to entry correlate with levels and changes in the founding rate of new voucher schools in Milwaukee. Drawing from a unique dataset covering founding attempts and successful foundlings of voucher schools since the early 1990s we show how formal institutions regulating entrepreneurial efforts have an impact on both attempts and success rates. For example, our analysis indicates that the removal of the non-sectarian school requirement led to an increase in entrepreneurial attempts. Likewise, we find that erecting of institutional barriers in the form of a formal third party approval process, proved to have an impactful effect on the founding success rate of new voucher schools. Our research also illuminate how a majority of entrepreneurial attempts, about 70 percent in the case of the new voucher schools in Milwaukee, fail somewhere between the stage of entrepreneur intent and actual establishment of the organization.

scholarly journals Identification of Information Leakage and Guilt Agent by using MAC-IP Binding and Recursive Partitioning Algorithm to Modulate the Uncertainty in the Organization’s Network

2019 ◽  
Vol 9 (1) ◽  
pp. 4091-4096
Keyword(s):  
Decision Tree ◽  
Recursive Partitioning ◽  
Information Leakage ◽  
Third Party ◽  
Sensitive Information ◽  
Sensitive Data ◽  
The Third ◽  
Partitioning Algorithm ◽  
The Third Party ◽  
Modern Era

In this modern era, all organizations depend on internet and data so, maintaining of all data is done by the third party in large organizations. But in this present on-developing world, one have to share the data inside or outside the organization which incorporates the sensitive data of the venture moreover. Data of the organization have sensitive data which should not share with any others but unfortunately, that data was there in the third party hands so; we need to protect the data and also have to identify the guilt agent. For this, we propose a model that would evaluate and correctly identifies guilt agents, for which a recursive partitioning has been created which is a decision tree that spills data in to the sub partitions and does the easiest way to get alert and at least one specialist or it can autonomously accumulate by some different means. The main intention of the model is to secure sensitive information by recognizing the leakage and distinguish the guilt agent.

scholarly journals Blockchain-Based ICOs: Pure Hype or the Dawn of a New Era of Startup Financing?

2018 ◽  
Author(s):  
Lennart Ante ◽  
Philipp Sandner ◽  
Ingo Fiedler ◽  
Andranik Tumasjan ◽  
Isabell Welpe
Keyword(s):  
Social Media ◽  
Human Capital ◽  
Venture Capital ◽  
Business Model ◽  
Model Quality ◽  
New Era ◽  
Relative Ease ◽  
Funding Success ◽  
Rapid Pace ◽  
Unique Dataset

This study explores the determinants of ICO success, where success is defined as the amount of capital a project was able to raise. ICOs are a tool for startups in the blockchain ecosystem to raise early capital with relative ease. The market for ICOs has grown at a rapid pace since its start in 2013. We analyze a unique dataset of 278 projects that finished their ICOs by August 2017 to assess determinants of funding success that we derive from the crowdfunding and venture capital literature. Our results show that ICOs exhibit similarities to classical crowdfunding and venture capital markets. Specifically, we identify resemblances in determinants of funding success regarding human capital characteristics, business model quality, project elaboration and social media activity.

scholarly journals Determining the Credit Score and Credit Rating of Firms using the Combination of KMV-Merton Model and Financial Ratios

2021 ◽  
Vol 6 (3) ◽  
pp. 105-112
Author(s):  
Norliza Muhamad Yusof ◽  
Iman Qamalia Alias ◽  
Ainee Jahirah Md Kassim ◽  
Farah Liyana Natasha Mohd Zaidi
Keyword(s):  
Credit Risk ◽  
Credit Rating ◽  
Credit Ratings ◽  
Credit Scoring ◽  
Financial Ratios ◽  
Credit Score ◽  
Merton Model ◽  
Medium Level ◽  
Credit Scores ◽  
Risk Managers

Credit risk management has become a must in this era due to the increase in the number of businesses defaulting. Building upon the legacy of Kealhofer, McQuown, and Vasicek (KMV), a mathematical model is introduced based on Merton model called KMV-Merton model to predict the credit risk of firms. The KMV-Merton model is commonly used in previous default studies but is said to be lacking in necessary detail. Hence, this study aims to combine the KMV-Merton model with the financial ratios to determine the firms’ credit scores and ratings. Based on the sample data of four firms, the KMV-Merton model is used to estimate the default probabilities. The data is also used to estimate the firms’ liquidity, solvency, indebtedness, return on asset (ROA), and interest coverage. According to the weightages established in this analysis, scores were assigned based on those estimates to calculate the total credit score. The firms were then given a rating based on their respective credit score. The credit ratings are compared to the real credit ratings rated by Malaysian Rating Corporation Berhad (MARC). According to the comparison, three of the four companies have credit scores that are comparable to MARC’s. Two A-rated firms and one D-rated firm have the same ratings. The other receives a C instead of a B. This shows that the credit scoring technique used can grade the low and the high credit risk firms, but not strictly for a firm with a medium level of credit risk. Although research on credit scoring have been done previously, the combination of KMV-Merton model and financial ratios in one credit scoring model based on the calculated weightages gives new branch to the current studies. In practice, this study aids risk managers, bankers, and investors in making wise decisions through a smooth and persuasive process of monitoring firms’ credit risk.

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