Fintech Lending Research Articles

Evolutionary-based ensemble feature selection technique for dynamic application-specific credit risk optimization in FinTech lending

Evolutionary-based ensemble feature selection technique for dynamic application-specific credit risk optimization in FinTech lending

Financial Literacy Program in Introducing Online Loan Applications to University Students

The Covid-19 pandemic in 2021 impacted the increasing diversity of basic needs in society and accelerated digitalization, which has now become a lifestyle. Easy access to digital platforms for shopping, education, investment, payments, and loans has made wise financial management essential. According to data from the Financial Services Authority (OJK), the total distribution of online loans from Fintech Lending in Indonesia reached IDR 225.55 trillion in 2022, an increase of 44.6% from the previous year. Fintech simplifies loan access through peer-to-peer (P2P) lending products that are fast and without complicated requirements, attracting the interest of young generations. Therefore, financial literacy is crucial for Sampoerna University students to address the low level of financial understanding amid the proliferation of online loan applications. Knowledge of risk management is needed so that students can make wise and responsible financial decisions and manage their finances effectively.

Social Penetration Analysis in Self-Disclosure of Online Loan Application Users to Their Partners

Abstract: This study aims to analyze the disclosure of online loan users to their partners through social penetration theory. Information technology-based money lending services are one of the innovations in the financial sector, utilizing technology to facilitate lending transactions without meeting in person. This transaction mechanism is carried out through a system provided by the Fintech Lending Organizer, either through an application or a website. Several problems arise because of the characteristics of online loans that often terrorize and intimidate people close to them without asking permission. This study is descriptive, using data collection techniques on ten pairs of online loan informants with their partners. Data analysis was carried out using interactive techniques involving interactions between data collection, data reduction, data presentation, and conclusions. Based on the social penetration analysis, five pairs of informants decided to separate/divorce, while five pairs did not divorce. The five pairs of informants who did not divorce were at stages 3 (affective exchange) and 4 (stable exchange). The five pairs who divorced were at stage 2 (exploration of affective exchange), which decreased the development of their relationship to deterioration. Couples who eventually divorce receive negative Feedback from their partners in the form of anger, annoyance, and regret. The perpetrators decide to get involved in online loans without discussing it with their partners but also have no desire to discuss it. The perpetrators' mindset, household economic problems, characteristics of online loans, and skills in communicating issues to their partners color the couple's interactions towards the end of the relationship. On the other hand, supportive Feedback, personality, and gender of the partner are factors that influence self-disclosure.

Determinant Factors of Profitability in Fintech Lending Companies in Indonesia from 2019 to 2022 Using Principal Component Analysis (PCA)

This reserach examines factors influencing the profitability of Fintech lending companies in Indonesia. A purposive sampling method was employed to select 45 companies annually. The data for this research are cross-sectional, comprising the years 2019, 2020, 2021, and 2022. The methods in this research are Principal Component Analysis (PCA) and multiple linear regression. Findings reveal that current ratio, cash ratio, working capital turnover, debt to assets ratio, short-term debt ratio, equity multiplier, total assets turnover, fixed assets turnover, tangible assets ratio, and effective tax rate significant determinants of profitability for Fintech lending companies in Indonesia. This reserach can help Fintech lending companies improve their profitability.

How the Economic Policy Uncertainty (EPU) impacts FinTech: The implication of P2P lending markets

This study investigates the impact of state-level Economic Policy Uncertainty (EPU) on FinTech lending marketplace. Leveraging two large-scale Peer-to-Peer (P2P) datasets of LendingClub and Prosper from 2010 to 2019 alongside the news-based EPU index, we unveil a causal relationship between the EPU and both the interest rates and loan amounts. Economically, a one-standard-deviation increase in EPU causes 4.49 and 8.90 basis points change in P2P loan rates, and 1.56% and 1.28% variation in loan amounts, for LendingClub and Prosper, respectively. Furthermore, the national-sourced EPU has a relatively stronger effect on LendingClub, while the state-sourced EPU imposes more impacts on Prosper.

Navigating regulatory sandbox initiatives for innovation diffusion in fintech lending: A systematic review

Navigating regulatory sandbox initiatives for innovation diffusion in fintech lending: A systematic review

Bridging the gap? A theoretical analysis of the net effect of FinTech entry on access to credit

FinTech lenders offer an opportunity to enhance credit access but may also disrupt traditional banking. This study proposes a theoretical framework for analyzing the net impact of FinTech’s entry on access to credit in credit markets dominated by conventional banks. When a FinTech lender enters the market, competition intensifies, which reduces the bank’s gain in serving certain customer segments. While FinTech lending can help serve some unattended niches, it may cause the bank to abandon others, leading to an ambiguous or even negative impact on access to credit.

ANALYZE THE INFLUENCE OF THE TECHNOLOGY ACCEPTANCE MODEL (TAM) ON THE USE OF FINTECH LENDING

This study endeavors to explore the impact of perceived usefulness and perceived ease of use on the intention to use fintech lending applications in Indonesia. The independent variables under scrutiny are perceived usefulness and perceived ease of use, while the dependent variable is the adoption of fintech lending applications. Employing a quantitative approach, this research employs a descriptive methodology. Primary data collected from 182 respondents serves as the basis for analysis. Sampling in this study is conducted using a non-probability technique, specifically the purposive sampling method. Questionnaires are distributed based on specific criteria, targeting individuals who have utilized fintech lending applications and reside in Indonesia. The findings, derived from multiple regression analysis, reveal a significant positive correlation between perceived usefulness, perceived ease of use, and the adoption of fintech lending applications in Indonesia. The research concludes that users use fintech lending technology when they find it easy to access loan funds quickly and when the application features do not ask for various types of information and documents.

Identifying Simultaneous Equation Modelling for the Digital Competitiveness Index (IDSD) and Foreign Direct Investment (FDI) in their Influence on Economic Digitalization

Technological advances are causing rapid and comprehensive changes, especially in the digital economy sector. The strength of a society's digital competitiveness is an important asset to support the growth of the national digital economy and attract foreign direct investment. This study aims to identify the simultaneous relationship between the Digital Competitiveness Index (IDSD) and Foreign Direct Investment (FDI). The method used is Two Stage Least Squares (2SLS) to overcome endogeneity problems in existing regression models, using STATA 17 software for calculations. The data analyzed are panel data from 34 provinces in Indonesia for 4 years (2020, 2021, 2022, and 2023). The analysis shows that in the FDI model, IDSD, GRDP growth rate, and non-oil and gas exports have a significant effect on FDI. However, in the IDSD model, FDI has no significant effect on IDSD, while fintech lending and ICT capability of the community have a significant effect on IDSD. Based on the results, there is no simultaneous relationship between FDI and IDSD.

Kepatuhan Syariah Pada Fintech Lending Syariah: Analisis Akad dan Implementasinya

Islamic fintech lending has emerged in response to the need for financial products that comply with Islamic law. In the context of Muslim communities, fintech lending is assessed not only in terms of efficiency and convenience but also for its adherence to Sharia principles. This research is of a normative-empirical type with a content analysis approach. The results of this study indicate that Islamic fintech is a financial innovation that combines technology with Islamic Sharia principles. Parties involved need to understand the contracts used according to their needs, such as sales (al-al-bayʿ), muḍārabah, mushārakah, wakālah bil ujrah, and qardh, the permissibility of which is explained in the Qur'an and rational evidence. In Indonesia, Islamic fintech activities refer to DSN-MUI Fatwa Number 117/DSN-MUI/II/2018. With Islamic values and strict government regulations, economic operations can be conducted in a beneficial, just manner, avoiding riba (usury), maysir (gambling), and gharar (uncertainty).

ISLAMIC FINTECH LENDING DETERMINANTS USING ISLAMIC FINANCIAL LITERACY AS A MODERATION VARIABLE

This study aims to determine the financial literacy of MSME actors in Morotai Island Regency as well as their erceptions in utilizing islamic fintech lending as an alternative business funding. Moderated Regression Analysis (MRA) with SPSS version 25 is the analysis approach used. 108 MSME units in six randomly chosen sub-districts received questionnaires with slovin technique, which was applied with a 0.05 margin of error and predetermined criteria. The study's findings demonstrate that the usage of islamic fintech lending is highly influenced by the perceived usefulness and ease of use of fintech. In addition, this study discovered that the impact of perceived usefulness and perceived ease of use on the frequency with which MSMEs use islamic fintech lending is not moderated by islamic financial literacy. The study's practical contribution is the realization that islamic financial literacy apart cannot be as a criteria for evaluating how MSME utilize islamic fintech lending to obtain funding for company expansion. Further research is necessary on digital literacy, which refers to MSME actors' ability in utilizing technology and digital platforms to obtain fintech funding. In addition, it's essential to focus on external factors like the availability of Islamic financial technology funding education and training for MSME.

Who gets the money? A qualitative analysis of fintech lending and credit scoring through the adoption of AI and alternative data

Credit scoring plays an important role in determining the accessibility of credit in the financial sector. This in turn has a significant impact on how economic opportunities are distributed. Our study examines the use of AI and alternative data in fintech lending through the lens of Information Asymmetry Theory. By employing a qualitative research design using the Gioia method, we extract, analyze, and synthesize insights from a diverse group of 26 experts in fintech lending, artificial intelligence, machine learning, data science, and academia. Our results reveal several important findings: the enhancement of predictive proficiency and risk management, the decrease in default rates, the extension of credit access by including previously ‘unbanked populations’, the introduction of real-time creditworthiness assessment and new business models for entrepreneurs, the enhancement of credit market efficiencies and positive effects on the stability of financial markets. In addition, our study highlights the necessity for rigorous and critical ethical considerations of important challenges such as the question of consent, algorithmic transparency, data quality, data misuse, representativeness, traceability, responsibility, bias and discrimination. The reasonable goal of a more fair, resilient, sustainable and accessible credit system will require a joint effort to balance leveraging technological innovations with respecting peoples' right to privacy.

Cyber Crime Countermeasures Policies Carried Out Within the Scope of Illegal Online Loans

Fintech Lending or online loans provide convenience for everyone who will borrow funds only with internet media or applications. However, with this convenience, illegal online loans have emerged which cause cyber crime in the scope of illegal online loans such as intimidation collection, extortion, fraud and even death threats and sexual harassment. This study analyzes both repressive and preventive countermeasures policies in tackling cyber crime in illegal online lending. This research uses juridical normative methods with primary materials of laws and regulations. Repressive efforts in law enforcement in cyber crimes in online loans carried out by the National Police, Prosecutors, Judges, and community agencies are influenced by legal factors, law enforcement factors, facilities or facilities factors. Preventive efforts in tackling these crimes by direct education to the community through socialization, seminars, discussions and dialogues.

Revitalization of the role of mosques and local wisdom in facing the rising of fintech lending in urban society

Revitalization of the role of mosques and local wisdom in facing the rising of fintech lending in urban society

Indonesian Millennial’s Financial Behaviour: The Role of Financial Literacy in Intention to Use Fintech Lending

The significance of financial behaviour among millennials, particularly concerning fintech lending, is important. Fintech lending is a complex subject that is increasingly being studied. However, it also provides a solution for quick and easy funds. This study proposes to notice the financial behaviour of millennials by looking at their financial literacy and how it affects their plan to use fintech lending. The study practices a quantitative research approach and gathered data from 359 respondents through purposive random sampling. Structural equation modelling was used to test the hypotheses. The study found that the variables of the theory of planned behaviour do not directly affect the intention to use fintech, on the other hand, financial literacy has a significant influence. The consequences of this study are useful for investors, financial institutions, and government officials since it emphasises the necessity of knowing millennials' financial behaviours. These behaviours can impact their product choices, as seen in their susceptibility to the FOMO syndrome

Can we trust machine learning to predict the credit risk of small businesses?

With the emergence of Fintech lending, small firms can benefit from new channels of financing. In this setting, the creditworthiness and the decision to extend credit are often based on standardized and advanced machine-learning techniques that employ limited information. This paper investigates the ability of machine learning to correctly predict credit risk ratings for small firms. By employing a unique proprietary dataset on invoice lending activities, this paper shows that machine learning techniques overperform traditional techniques, such as probit, when the set of information available to lenders is limited. This paper contributes to the understanding of the reliability of advanced credit scoring techniques in the lending process to small businesses, making it a special interesting case for the Fintech environment.

The impact of fintech lending on credit access for U.S. small businesses

Small business lending (SBL) plays an important role in funding productive investment and fostering local economic growth. Recently, nonbank lenders have gained market share in the SBL market in the United States, especially relative to community banks. Among nonbanks, fintech lenders have become particularly active, leveraging alternative data and complex modeling for their own internal credit scoring. We use proprietary loan-level data from two fintech SBL platforms (Funding Circle and LendingClub) to explore the characteristics of loans originated pre-pandemic (20162019). Our results show that these fintech SBL platforms lent relatively more in zip codes with higher unemployment rates and higher business bankruptcy filings. Moreover, fintech platforms’ internal credit scores were able to predict future loan performance more accurately than traditional credit scores, particularly in areas with high unemployment. Using Y-14 M loan-level bank data, we compare fintech SBL with traditional bank business cards in terms of credit access and interest rates. Overall, while not all fintech firms follow the same approach, we find that fintech lenders could help close the credit gap, allowing small businesses that were less likely to receive credit through traditional lenders to access credit and potentially at lower cost.

Banking competition in Indonesia: does Fintech lending matters?

PurposeThis paper aims to examine how the rise of financial technology (Fintech) lending affects bank competition. Moreover, this study also identifies the structure of Indonesian commercial banking sector and the different behaviour of competition among bank groups (based on their size, type and ownership) and the joint impact of COVID-19 due to the rise of Fintech lending.Design/methodology/approachUsing an unbalanced panel data set of 118 commercial banks in Indonesia over the period 2018–2022, both static panel and 2SLS/IV data analysis were used and found that random effect model is the best model.FindingsThe results show that the Indonesian commercial banking sector can be considered as monopolistic competition. Moreover, using the Lerner index reveals that the entry of the Fintech lenders increases bank competition. Furthermore, there were different responses to the impact of Fintech lending on bank competition among state-owned banks, private banks, regional development banks and foreign banks. Greater efficiency and stability lead to greater market power. In the meantime, higher level of asset growth, capitalisation and cost-to-income ratio increase the competition. Lastly, higher bank credit growth and lower inflation boost overall bank competitiveness.Practical implicationsThis study highlights some policy recommendations for commercial banks to be aware of the coming of Fintech lenders because they have started to increase the market competition. The government should create a more collaborative ecosystem between banks and Fintech lending to anticipate unhealthy competition.Originality/valueThis study will contribute to the literature by expanding the determinants of bank competition by considering the rise of Fintech lending in the market.

ANALYSIS OF RELATIONSHIP BETWEEN THE USAGE OF ONLINE LOAN SERVICES AND THE WELL-BEING OF INDONESIAN USING CHI-SQUARE TEST

Online fintech lending offers convenience by providing flexibility for both lenders and borrowers. It led to a significant increase in users. Despite this encouraging growth, it comes with risks, such as the emergence of illegal loan companies. The controversial positive and negative aspects of online loans have sparked the researchers' interest in understanding how the Indonesian public perceives the existence of online loans and whether there is a relationship between the use of online loans and the well-being of users. The data were collected through the questionnaire using Google Form and then distributed to respondents who meet the specified sample criteria, namely Indonesian, aged 17 years old or above, and still able to think rationally. The total study sample are 191 respondents, with the total male is 90 and the total female is 101. Since the results of the data gathered were in the form of categorical data, so the Chi-square test is utilized in this study. With the calculated chi-square less than the chi-square table, it showed that there is no correlation between the frequency of using online loan services and the well-being of the Indonesian people, whether based on age, level of education, or type of job. Hence, it can be concluded that the usage of online loan services is not influences the well-being of Indonesian. It is also known that public perceptions of online loans vary and cannot be generalized. However, those less prosperous, tend to agree with and appreciate the online loan services’ existence compared to those who are prosperous.

Application of Artificial Intelligence and Machine Learning in Robotic Systems for Nuclear Micro Reactor Development and Manufacturing

Artificial intelligence and machine learning algorithms and methods are the forthcoming instances in developing advanced nuclear reactor technology, mainly micro-nuclear reactor development.