scholarly journals Peer-to-Peer Lending – A (Financial Stability) Risk Perspective

2018 ◽  
Vol 69 (1) ◽  
pp. 1-25 ◽  
Author(s):  
Benjamin Käfer
Keyword(s):  
Default Risk ◽  
Financial Stability ◽  
Liquidity Risk ◽  
Peer To Peer ◽  
Soft Information ◽  
Final Conclusion ◽  
Survey Article ◽  
P2p Lending ◽  
Over Time

AbstractThe aim of this survey article is to discuss P2P lending, a subcategory of crowdfunding, from a (financial stability) risk perspective. The discussion focuses on a number of dimensions such as the role of soft information, herding, platform default risk, liquidity risk, and the institutionalization of P2P markets. Overall, we conclude that P2P lending is more risky than traditional banking. However, it is important to recognize that a constant conclusion would be misleading. P2P platforms have evolved and changed their appearance markedly over time, which implies that although our final conclusion of increased riskiness through P2P markets remains valid over time, it is based on different arguments at different points in time.

scholarly journals Fintech Based Peer-too-peer (P2P) Lending : A Perspective of MSMEs In the New Normal Era of Pandemic Covid-19

2021 ◽  
Vol 5 (1) ◽  
pp. 26-46
Author(s):  
Tuti Zakiyah
Keyword(s):  
Sampling Method ◽  
Peer To Peer ◽  
Survey Method ◽  
Data Collection Tool ◽  
New Normal ◽  
Central Java ◽  
Inner Model ◽  
P2p Lending ◽  
R Value

The purpose of this research is to find out the role of Fintech Peer to Peer (P2P) lending based on the perception in the new normal era of Covid-19 as a financial inclusion for the recovery of the MSME financial sector. The population of this research is MSMEs in Central Java and East Java Provinces. The survey method was carried out by collecting data using a questionnaire as a data collection tool. In addition, researchers also use purposive sampling method to determine the sample. The analysis hypothesis is used the outer model and EViews 10 for the evaluation of the inner model. The results of this study are that peer to peer  lending together has a significant effect on the interests of MSME actors in East Java in The New Normal Era of the Covid-19, this is also supported by the Adjevtive R value which shows the number 87%.

Competition and Distortion: A Theory of Information Bias on the Peer-to-Peer Lending Market

2021 ◽  
Author(s):  
Zhenhua Wu ◽  
Lin Hu ◽  
Zhijie Lin ◽  
Yong Tan
Keyword(s):  
Peer To Peer ◽  
Policy Implications ◽  
Relevant Research ◽  
Market Incentives ◽  
Information Bias ◽  
Information Reporting ◽  
P2p Lending ◽  
Optimal Information ◽  
Threat Of Entry

Despite the popular emergence of peer-to-peer (P2P) lending platforms, relevant research investigating the role of these platforms on P2P markets still lags. In this paper, we present a model to study the market incentives of P2P lending platforms' optimal information-reporting strategies when the following exist: (i) uncertainty on the return of loans and (ii) competition from entrants. We focus on the information bias of platforms driven by demand-side actors—investors’ optimism/pessimism about risk—while we keep the platforms being rational. We characterize platforms' equilibrium reporting strategies under different market conditions. Surprisingly, we find that when uncertainty is significant, and the threat of entry is strong but not detrimental, the platform has incentives to bias information toward investors' biased beliefs. This result demonstrates a case where competition and uncertainty may jointly lead to information bias. However, a properly designed uncertainty-resolution mechanism could reduce the incentive. Our findings contribute to the literature on the P2P lending market by analyzing platform decisions and offer policy implications for regulating P2P lending market.

scholarly journals PENGARUH FINANCIAL TECHNOLOGY (FINTECH) TERHADAP STABILITAS SISTEM KEUANGAN DI INDONESIA

2021 ◽  
pp. 921
Author(s):  
Birgitta Dian Saraswati ◽  
Ni Made Tisnawati
Keyword(s):  
Exchange Rates ◽  
Interest Rates ◽  
Financial Stability ◽  
Financial System ◽  
System Stability ◽  
Series Data ◽  
Macroeconomic Variables ◽  
P2p Lending

Financial stability is very important in the economy because financial stability will ensure smooth financial transactions in the economy.This study aims to analyze the effect of P2P lending fintech, payment fintech and macroeconomic variables (inflation, interest rates and exchange rates) on financial stability in Indonesia.This study uses time series data with the period 2018.1-2021.4. Using the Vector Error Correction Model, this research shows that Fintech P2P Lending, Fintech Payments and macroeconomic variables (inflation, interest rates and exchange rates) affect the financial stability in Indonesia only in the long term.Fintech P2P lending in the long term will lead to financial system instability, while Fintech payments in the long term have a positive effect on financial system stability in Indonesia. This has policy implications where through the role of the Financial Services Authority it is necessary to regulate and supervise P2P lending fintech. In addition, considering that payment fintech has a positive impact on financial system stability in Indonesia, through the role of Bank Indonesia, it is necessary to design policies to increase the use of non-cash payment instruments.

scholarly journals Penerapan Konsep Utilitarianisme Untuk Mewujudkan Perlindungan Konsumen Yang Berkeadilan Kajian Peraturan Otoritas Jasa Keuangan Nomor: 1/POJK.07/2013 Tentang Perlindungan Konsumen Sektor Jasa Keuangan

2019 ◽  
Vol 19 (1) ◽  
pp. 15
Author(s):  
Dwi Edi Wibowo
Keyword(s):  
Consumer Protection ◽  
Financial Services ◽  
Peer To Peer ◽  
Financial Industry ◽  
Fast Process ◽  
Bank Institution ◽  
P2p Lending ◽  
Peer Lending ◽  
Financial Technology

Abstrak Peranan internet dalam teknologi informasi telah digunakan untuk mengembangkan industri keuangan  (financial industry)  melalui modifikasi dan efisiensi layanan jasa keuangan yaitu dikenal dengan istilah Financial Technology atau Fintech. Fintech jenis pinjam-miminjam uang berbasis teknologi atau peer to peer lending (P2P-lending) merupakan jenis Fintech yang tumbuh pesat di Indonesia, kelebihan pinjam meminjam uang melalui layanan P2P-lending lainnya adalah syarat yang sangat mudah dan proses yang cepat dibandingkan meminjam uang melalui Lembaga Bank. Namun kemudahan transaksi yang ditawarkan oleh layanan P2P- lending justru memperlemah posisi dari konsumen. Permasalahan Bagaimanakah Penerapan Konsep Utilitarianisme Untuk Mewujudkan Perlindungan Konsumen Fintech. (Financial Technology) Yang Berkeadilan, Tujuan  untuk mengetahui bagaimanakah penerapan konsep utilitarianisme untuk mewujudkan perlindungan kosnumen fintech ( finansial technology yang berkeadilan . Kata kunci : utilitarianisme, perlindungan konsumen, berkeadilan Abstrak The role of the internet in information technology has been used to develop the financial industry through the modification and efficiency of financial services, known as Financial Technology or Fintech. Fintech borrows money based on technology or peer to peer lending (P2P-lending) is a fast-growing type of Fintech in Indonesia, the advantages of lending and borrowing via other P2P-lending services are very easy conditions and a fast process compared to borrowing money through Bank Institution. But the ease of transactions offered by P2P-lending services actually weakens the position of consumers. Problems How to Implement the Utilitarianism Concept to Realize Fintech Consumer Protection. (Financial Technology) that is just, the aim is to find out how the application of the concept of utilitarianism is to realize the protection of fintech consumers (equitable technology finance. Keywords: utilitarianism, consumer protection, justice 

scholarly journals Penanganan TerhadaP Financial Technology Peer-To-Peer lending Ilegal MelaluI OTOrITas Jasa Keuangan (studi Pada OJK Jakarta Pusat)

2020 ◽  
Vol 8 (2) ◽  
pp. 252
Author(s):  
Alifia Salvasani ◽  
Munawar Kholil
Keyword(s):  
Peer To Peer ◽  
Payment System ◽  
Primary Data ◽  
Cyber Crime ◽  
Data Types ◽  
Literature Study ◽  
P2p Lending ◽  
Peer Lending ◽  
Financial Technology

<p>abstract<br />This article aims to examine the role of Otoritas Jasa Keuangan (OJK) in handling illegal peer-to-peer  (P2P)  financial  technology  (fintech)  in  Indonesia.  This  role  includes  the handling carried out by the FSA to minimize the number of illegal fintech in Indonesia, both through supervision and arrangements related to illegal fintech. This type of empirical legal research, is descriptive, with primary data types. Literature study and interview data collection techniques, qualitative analysis techniques. Factors causing the rise of illegal fintech are normative and non-normative factors. Then the role of the OJK in making efforts to handle illegal P2P lending includes establishing Satgas Waspada Investasi, listing registered P2P lending and licensed on the official OJK website, socializing to the public about the characteristics of illegal P2P lending that must be avoided and data of illegal P2P lending in Indonesia, closing illegal P2P lending, blocking applications and illegal P2P lending websites on a regular basis, conducting selective checks on P2P lending companies that  propose opening  new  accounts,  applying  special  rules  for  P2P  lending  companies related to the fintech payment system , and submit information reports to the Criminal Investigation Police regarding cyber crime.<br />Keywords: Otoritas Jasa Keuangan; Illegal Fintech; Peer-to-Peer</p><p>abstrak<br />Artikel  ini  bertujuan  untuk  mengkaji  peranan  Otoritas  Jasa  Keuangan  (OJK)  dalam menangani  financial technology (fintech) peer-to-peer (P2P) lending ilegal di Indonesia. Peranan tersebut  meliputi penanganan yang dilakukan OJK untuk meminimalisir jumlah fintech  ilegal  di  Indonesia,  baik  melalui  pengawasan  maupun  pengaturan  terkait  fintech ilegal. Jenis penelitian hukum empiris, bersifat deskriptif, dengan jenis data primer. Teknik pengumpulan data studi kepustakaan dan wawancara, teknik analisis kualitatif. Faktor penyebab tumbuh maraknya fintech ilegal adalah adanya faktor normatif dan non-normatif. Kemudian peranan OJK dalam melakukan upaya penanganan P2P lending ilegal antara lain dengan membentuk Satgas Waspada Investasi, mencantumkan daftar P2P lending yang terdaftar dan berizin di website resmi OJK, mensosialisasikan kepada masyarakat terkait ciri-ciri P2P lending ilegal yang harus dihindari dan data P2P lending ilegal di Indonesia, melakukan penutupan terhadap P2P lending ilegal, pemblokiran aplikasi dan website P2P lending ilegal secara  rutin, melakukan  pemeriksaan  secara selektif bagi perusahaan  P2P lending yang mengajukan pembukaan rekening baru, memberlakukan aturan khusus bagi perusahaan  P2P  lending  terkait  fintech  payment  system,  dan  menyampaikan  laporan informasi kepada Bareskrim Polri terkait tindakan cyber crime.<br />Kata Kunci: Otoritas Jasa Keuangan; Fintech Ilegal; Peer-to-Peer Lending</p>

scholarly journals The Role of Peer to Peer Lending in Increasing Funding for Micro, Small, and Medium Enterprises

2020 ◽  
Vol 76 ◽  
pp. 01031
Author(s):  
Nanik Linawati ◽  
Moeljadi Moeljadi ◽  
Djumahir Djumahir ◽  
Siti Aisjah
Keyword(s):  
Literature Review ◽  
Financial Aid ◽  
Small And Medium Enterprises ◽  
Peer To Peer ◽  
Alternative Funding ◽  
P2p Lending ◽  
Peer Lending ◽  
Medium Enterprises

This study aims to describe the potential of MSMEs in Indonesia and the role of technology in the industrial era 4.0, especially in alternative funding in the form of Peer to Peer (P2P) Lending in providing funding solutions for MSMEs. This study uses a literature review including academic studies on MSME financing in Indonesia by using the results of previous studies and surveys on Indonesian MSME. The development of P2P Lending is the solution for MSMEs with no access to financial aid from banks.

scholarly journals Fintech Application in Banking Operations - Application of Machine Learning in Mitigating Bank Derivatives Counterparty Risks

2019 ◽  
Vol 4 (3) ◽  
pp. 1
Author(s):  
Tianshu Li
Keyword(s):  
Machine Learning ◽  
Gender Discrimination ◽  
Bp Neural Network ◽  
Default Risk ◽  
Soft Information ◽  
Financial Decisions ◽  
P2p Lending ◽  
Different Characteristics ◽  
Psychological Bias ◽  
Machine Learning Models

We all know that human has many psychological biases, including overconfidence, gender discrimination and so on. Although some genuine lenders may outperformance others, machine learnings have been utilized to solve this human psychological bias in many areas. By using machine learnings methods, people can make better financial decisions. This proposal tries to examine the effectiveness of several different machine learning models on predicting the ex-pose default risk, including BP neural network, decision tree, KNN, and random forest. I focus on loans on one electronic P2P lending platform, called “Paipaidai” in which lenders select and supply private loans to borrowers with different characteristics. I use machine learnings methods to predict the default risk and thus provides better ways for investors to select high-quality borrower. I will also further test how different machine learnings methods perform when there is soft information contained by using Prosper platform.

scholarly journals THE ROLE OF INSURANCE IN ANTICIPATING THE RISK OF DEFAULT IN PEER TO PEER (P2P) LENDING SCHEME

2021 ◽  
Vol 2 (2) ◽  
pp. 112
Author(s):  
Ida Ayu Rhadana Satvikarani ◽  
Mas Rahmah ◽  
Dian Purnama Anugerah
Keyword(s):  
Peer To Peer ◽  
P2p Lending

scholarly journals A DBM-Based Ensemble Method for Improving Default Risk Prediction of Peer-to-Peer (P2P) Lending

2021 ◽  
Vol 11 (3) ◽  
pp. 85-92
Author(s):  
Shan Gao ◽  
◽  
Xuefeng Wang
Keyword(s):  
Risk Prediction ◽  
Default Risk ◽  
Influencing Factor ◽  
Real Data ◽  
Peer To Peer ◽  
Ensemble Method ◽  
Real World Data ◽  
The Real ◽  
Healthy Development ◽  
P2p Lending

With the peer-to-peer lending (P2P) business growing up, the most important influencing factor for the healthy development of this industry is the default risk of borrowers. Because the behavior between lenders and borrowers is real time, naturally large amounts of transaction data are being generated all the time. However, it is difficult to extract useful representative features and choose an appropriate model to predict the default risk of the borrowing behavior. In this paper, we proposed a (Deep Boltzmann Machines) DBM-based ensemble method for the default risk prediction in p2p lending, which is based on the real data generated by Lending Club company. Experimental results on the real world data indicate that our model is more effective and powerful with a 0.9093 explanation power.

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