Financial Entities Research Articles

Entrepreneurial Innovation and Economic Development: Historical and Modern Perspectives

Entrepreneurship, a cornerstone of economic development and innovation, involves identifying and exploiting opportunities through new ventures. This paper delves into the evolution of entrepreneurship, its components, processes, and various forms, while also discussing strategies for entrepreneurial success. From historical perspectives provided by Cantillon, Say, and Schumpeter to modern concepts such as social and biosphere entrepreneurship, the paper offers a holistic view. It also highlights the importance of an enabling ecosystem comprising government support, educational institutions, and financial entities, emphasizing the need for effective risk management and strategic planning.

IPerFEX-2023: Indonesian personal financial entity extraction using indoBERT-BiGRU-CRF model

There is minimal research focusing on applications of Indonesian named entity recognition (NER) in a specific domain. This study proposes an Indonesian personal financial entity extraction task that can be utilized in a financial assistant chatbot system to interpret user’s financial situation for personalization. Due to the simplicity that a chatbot has, it can promote financial management practices to youth as early as possible in their career. However, the challenge in financial NER is numerical entity extraction that relies heavily on contextual information and suffers the out-of-vocabulary (OOV) problem. Therefore, to extract 15 personal financial entities in daily Indonesian discussions (expense-type, expense-amount, income-type, income-amount, asset-type, asset-amount, saving-type, saving-amount, liability-type, liability-amount, family, time, financial-goal, age, and occupation), this research proposes a dataset, IPerFEX-2023, trained using the Bidirectional Gated Recurrent Unit BiGRU and Conditional Random Field (CRF) with Indonesian Bidirectional Encoder Representations from Transformers (IndoBERT) pre-trained model for feature embeddings (IndoBERT-BiGRU-CRF). It is compared with the corresponding Bidirectional Long Short-Term Memory (BiLSTM) (IndoBERT-BiLSTM-CRF) as baseline. Not only the IndoBERT-BiGRU-CRF model achieves the best performance with a 0.73 F1-score, but it is also 14% faster on average compared to the corresponding baseline model due to its simpler unit structure. This paper also discusses future directions covering model enhancement strategy based on the error analysis result and complementary tasks needed to complete personalization

Risk Assessment of Banks and Financial Institutions in China

In the aftermath of the COVID-19 pandemic, economic development has emerged as a paramount concern globally. Governments, including that of China, have implemented various policies to reignite growth. However, this pursuit of rapid expansion brings with it inherent risks. This study conducts a comprehensive analysis of the risks facing China's domestic banks and financial institutions. It systematically identifies the factors contributing to their vulnerabilities, highlighting the complexities of the economic landscape. The research reveals that external economic conditions, lingering effects of the pandemic, and internal factors such as banks' understanding gaps collectively drive these risks. By illuminating these dynamics, the study aims to enhance understanding of the challenges confronting financial entities. It seeks to provide valuable insights for the comprehensive evaluation of China's domestic financial landscape in the future. Understanding these risks is crucial for policymakers, regulators, and stakeholders in crafting effective strategies to navigate the evolving economic environment. Ultimately, this analysis contributes to a more informed approach towards bolstering the resilience of China's banking and financial sectors amidst ongoing uncertainties.

Australia’s Thin Capitalization Regime: Financial Entities and Authorized Deposit-Taking Institutions (ADIs) are Put on Notice

Australia’s Thin Capitalization Regime: Financial Entities and Authorized Deposit-Taking Institutions (ADIs) are Put on Notice

Understanding and predicting lapses in mortgage life insurance using a machine learning approach

Mortgage Life Insurance (MLI) offers lucrative opportunities for insurers. However, customer retention has proven to be a daunting challenge, particularly following the regulatory changes of 2009 in Europe. New market entrants strategically employing low-premium tactics have reshaped the competitive landscape, leading established insurers and banks to grapple with retaining their MLI clientele. Consequently, increasing policy lapses hold critical implications for these financial entities. Responding to this intricate landscape, our research presents a predictive model that pinpoints the MLI policies at risk of lapse and disentangles the underlying factors propelling this risk. The objective is to provide insurers with a practical and strategic tool to improve customer retention, enabling them to identify specific actions to reduce customer attrition, improve financial stability, and strengthen customer loyalty. We used a dataset obtained from an insurance company and its partner bank to build the model. The effectiveness of four machine learning models, namely Logistic Regression, Random Forest, Neural Networks, and XGBoost, is investigated, with XGBoost outperforming the others. SHapley Additive exPlanations (SHAP) were utilized to bolster interpretability, thereby facilitating the conception and explication of the predictive model’s most influential features. Underpinning the benefits of a nuanced exploration, the study’s focus on a solitary insurance protection product and integrating bank data enabled us to apprehend the multifaceted drivers of lapse behavior. The study accentuates the merit of comprehensive data encapsulating a holistic perspective, with the four most influential features originating from bank data. From an insurer’s standpoint, this research provides a strategic vantage point to proactively identify and engage with customers at risk of policy lapse and reformulate their policies to mitigate customer attrition.

DIGITALLY DRIVEN MODEL OF A CLIMATE-NEUTRAL ECONOMY IN TERMS OF GLOBAL FINANCIAL CAPACITY

The article explores the conditions and drivers for the development of a climate-neutral economy model, emphasizing the pivotal role of digital transformation. A crucial lever in deploying this model is the proactive engagement of international financial entities within the realm of global green financing. The study highlights the instrumental role of green funds as key players in shaping global financial capacity and providing multilateral support for climate change adaptation worldwide. It delves into the overarching frameworks and mechanisms of such assistance. Employing a systematic analysis alongside case studies of the Green Climate Fund's projects, the authors aim to identify the most impactful sectors for cultivating a climate-neutral economy. The research identifies four essential segments for achieving climate neutrality: digitalization for climate, strengthening the financial capacity and business sustainability, rethinking ecosystem development, and community empowerment. The investigation draws on extensive data regarding the execution of 240 climate projects across major beneficiaries of climate finance in Eastern Europe, Africa, the Asia-Pacific, and Latin America. It shows that modern climate finance demonstrates signs of geopolitical dependency and polarization in global influence. The findings argue for bolstering the regional presence of climate funds to increase the financial capacity to implement climate-neutral projects at the local level. The article underscores the scale of financial support required across each segment, as well as the leading role of pre-project preparation. The authors substantiate the overarching and twofold role of digitalization in the model of a climate-neutral economy. The digital transformation produces a whole cluster of independent and versatile IT products for green businesses, industries and governance. On the other hand, digitalization creates an informational environment and a powerful digital infrastructure for better efficacy of other crucial segments. Specifically, it provides digital decisions for financial solvency and sustainability of green businesses in terms of green lending, grants and Fintech; strengthens information awareness and involvement of vulnerable communities in green economy processes; promotes digital support for overall ecosystem adaptation.

Cyber Operations in Ukraine: Emerging Patterns in Cases

The Ukrainian state has been a target of cyber-related incidents since the annexation of Crimea in 2014. Cyberattacks have targeted Ukrainian critical infrastructure, government offices, and several public and private organisations. Sometimes, these cyberattacks have caused significant impacts within the nation's borders. Some of the most well-known cyber-incidents in Ukraine include attacks on the Ukrainian electrical grid, which cut out the power supply for hundreds of thousands of people in 2015 and 2016. Attacks have also targeted presidential election systems and financial entities operating in Ukraine. The majority of attacks within Ukraine's borders have been attributed to Russian-affiliated non-state actors and organisations, and the number of attacks correlates with the escalation of the war in 2022. This implies previous cyberattacks potentially belonging to a series of hybrid operations related to the Ukrainian conflict and the general geopolitical situation since the annexation of Crimea. The paper focuses on this context by examining cyber incidents targeting Ukraine since 2014. We study the unifying factors related to Ukrainian cyber incidents, and we will discuss emerging patterns related to the attacks during the last ten years. This study will uncover the general traits of state-affiliated attacks in Ukraine, which will help uncover emerging patterns. Our particular focus will be cyber-attacks, where the target is the Ukrainian state and its critical infrastructure. We will examine methods of attacks, the attack targets, and the impacts, among other things. With the patterns emerging from our study, we can predict future cyber-attacks targeting Ukraine, providing tools for preparing for future incidents. We can use the information to improve national cyber-defences, where the attacks are likely to happen in the future. Studying the Ukrainian cases may also provide additional insights for improving cyber defences in other nation-states within the parts that apply to these nation-states and their geopolitical contexts.

A proposal for a composite indicator based on ratios (CIBOR) to compare the evolution of Spanish financial institutions

This paper introduces a new Financial Stress Indicator (FSI) named Composite Indicator Based on Ratios (CIBOR). This paper discusses the importance of monitoring the quality of loans and capital, operational performance, profitability, and liquidity of financial institutions to prevent systemic risks in the financial system. To address this, CIBOR is proposed as a means to indirectly capture the instability of a financial entity by identifying potential tensions and their underlying causes. Specifically, we compare the results for 25 financial entities operating in the Spanish banking market, analysing the evolution since 2018 to 2022. CIBOR permits a straight interpretation of the variations between periods and a dynamic analysis that not only measures the variation between the ratios over time, but also identifies the sources of such variations: variations derived from changes in sub-indicators, changes stemming from the oscillation of the baseline, and the impact of the selection of weights in the construction of the composite indicator.

Green bond issuance and credit risk: International evidence

We present the first empirical study of the impact of corporate green bond issuance announcements on issuer credit risk, as measured by their CDS spreads. We use a broad international sample of 1,048 green bonds issued between 2013 and 2022 by 200 entities from 26 countries. Our analysis reveals a significant, though not uniform, reaction in the CDSs. The sector of activity emerges as a critical determinant, particularly with respect to environmental exposure. While sectors highly exposed to environmental risk exhibit a reduction in issuer credit risk, all others, especially financial entities, react in the opposite direction. Our study highlights that the impact on credit risk is influenced by several other factors, including the issuer’s overall ESG score, its E score, and various country-level metrics such as development level, environmental performance and political rights. We also identify other factors that affect credit risk, such as green bond ratings and operating cash flow.

Evaluating air pollution exposure among cyclists: Real-time levels of PM2.5 and NO2 and POI impact

Although cycling has numerous health benefits, the increased breathing volume and lack of protection from exposure to the environment while cycling poses health risks that cannot be disregarded. Previous studies evaluating the exposure of cyclists to air pollution have typically focused on assessing exposure to a single pollutant or exposure concentrations on specific urban routes, and have not performed a comprehensive assessment considering the distribution of cyclists. The present study used bicycle-sharing big data to conduct a more comprehensive and refined real-time population weighted exposure risk assessment of pileless bike sharing riders in Beijing. We quantified the spatial distribution of high exposure areas at different times and found that the exposure risk during the evening peak period was significantly higher than that during the morning peak and early morning periods, particularly in the city center and its environs. By establishing stepwise regression models, we identified the significant impact of various urban points of interest (POIs) on exposure risk, with sports venues, public toilets, educational institutions, scenic spots, and financial entities particularly influential at different time periods. Medical institutions and shopping venues have a significant negative impact on the exposure levels of PM2.5 and NO2 among cyclists in most cases. These findings emphasize the need for targeted pollution control strategies. The aim of this study is to mitigate the impact of air pollution on cyclists and create a healthier cycling environment. The research results can provide new ideas for urban health planning and support scientific decision-making for sustainable urban development.

Green credit policy and default risk of the heavy polluting corporations

This paper uses a double-difference model to test the impact of green credit policy on the default risk of heavy polluters based on the data of China listed companies from 2008 to 2021. It is found that green credit policy can significantly reduce the default risk of heavy polluters, and the reduction effect is more significant in state-owned enterprises. Further mechanism tests show that green credit policy reduces default risk by guiding heavily polluting firms to reduce financial leverage. Government environmental regulation and corporate green innovation capacity affect the role of green credit policy on corporate default risk. With the strengthening of regional environmental regulations and the enhancement of corporate green innovation capabilities, the effect of green credit policies in diminishing the default risk for companies with high pollution levels is increasingly evident. This study not only enriches the literature on green credit but also demonstrates the effectiveness of directing banks and various financial entities to allocate resources reasonably, guiding heavily polluting enterprises to control risks, and steadily achieving green transformation. These findings hold significant implications for decision-making in designing environmental policy and management strategies.

Blockchain-Enabled Utility Optimization for Supply Chain Finance: An Evolutionary Game and Smart Contract Based Approach

In recent years, blockchain technology has attracted substantial interest for its capability to transform supply chain management and finance. This paper employs evolutionary game theory to investigate the application of blockchain in mitigating financial risks within supply chains, taking into account the technology’s maturity and the risk preferences of financial institutions. By modeling interactions among financial institutions, small and medium enterprises (SMEs), and core enterprises within the accounts receivable financing framework, this study evaluates blockchain’s impact on their decision-making and its efficacy in risk reduction. Our findings suggest the transformative potential of blockchain in mitigating financial risks, solving information asymmetry, and enhancing collaboration between financial entities and SMEs. Additionally, we integrate smart contracts into supply chain finance, proposing pragmatic procedures for their deployment in real-world contexts. Via a detailed examination of blockchain’s maturity and financial institutions’ risk preferences, this research demonstrates the primary determinants of strategic decisions in supply chain finance and underscores how blockchain technology fosters system stability using risk mitigation. Our innovative contribution lies in the design of smart contracts for the ARF process, rooted in blockchain’s core attributes of security, transparency, and immutability, thereby ensuring efficient operation and cost reduction in supply chain finance.

The Impact of International Financial Regulation on Financial Management of Chinese Enterprises

With the globalization of financial markets, international financial regulation has become increasingly crucial in shaping the financial landscape of countries worldwide. This paper explores the influence of international financial regulation on the financial management of Chinese enterprises. By examining the regulatory frameworks, compliance requirements, and their effects on financial practices, this study aims to provide insights into how Chinese financial enterprises navigate through the complex regulatory environment. Through a comprehensive analysis of case studies and empirical data, this paper sheds light on the challenges and opportunities presented by international financial regulation for Chinese financial entities, and suggests strategies for effective financial management in this context.

The Impact of Government Schemes and Fintech in Financial Inclusion

Access to and use of formal financial services by individuals and enterprises is known as financial inclusion, and it has grown to be a crucial issue in many nations. Various measures have been implemented by governments and financial entities. Programs aimed at improving financial inclusion, especially for the underprivileged and unbanked population. The use of technology to deliver financial services, or fintech, has also come to light as a possible way to improve financial inclusion. The study’s objectives are to determine whether these government programs and fintech are beneficial in promoting financial inclusion, to pinpoint the elements that make them successful or unsuccessful, and to make policy recommendations to maximize their influence. This subject is pertinent given the state of the world economy today, where digital financial services are more crucial than ever—particularly in the wake of the COVID-19 pandemic. The study’s emphasis on the technological components of banking is particularly noteworthy since it is commonly known that FinTech and technology play a major role in advancing financial inclusion. In developing nations with high rates of mobile phone use, mobile banking has become an increasingly potent instrument for promoting financial inclusion. People who reside in distant places without access to physical bank offices will find mobile banking extremely useful as it enables them to access banking services via their phones. Additionally, mobile banking makes it possible for users to do transactions swiftly and efficiently without having to travel far

An Investigation of Financial Inclusion in Ranchi: Challenges and Opportunities in Ranchi City

This study provides an inclusive examination of the intricacies of financial inclusion in Ranchi, India, shedding light on the challenges and opportunities within the local financial landscape. Through a comprehensive survey involving 141 participants, the research uncovers significant obstacles, including but not limited to, limited access to formal financial institutions and cultural barriers hindering the adoption of modern financial services. These challenges are juxtaposed with encouraging prospects, such as the increasing acceptance and utilization of digital payment solutions, as well as the emergence of collaborative initiatives between financial entities and non-governmental organizations. The findings underscore the critical need for tailored policy interventions focusing on multiple key areas. Firstly, there is a pressing need for enhancing financial literacy among the local population to promote a better understanding of financial products and services. Moreover, the study emphasizes the significance of forging strategic partnerships between various stakeholders, including governmental bodies, financial institutions, and non-governmental organizations, to promote a more inclusive and sustainable financial ecosystem in Ranchi. By addressing the identified challenges and capitalizing on the opportunities within the local financial landscape, the study advocates for the creation of a more accessible, equitable, and sustainable financial system that can support the region's overall development and growth.

Harnessing AI and machine learning for enhanced credit risk analysis: A comprehensive exploration of computational techniques in the financial realm

Within the confluence of the banking and financial sectors, the integration of machine learning in credit risk analysis signifies a paradigm shift towards data-centric decision-making. Historically, methodologies for credit risk were limited in predictive accuracy and computational efficiency. The advent of expansive language models, exemplified by Ant Group's AntFinGLM, offers a solution. These models, underpinned by deep learning, amalgamate financial texts and transactional data, facilitating the discernment of intricate financial paradigms and market nuances. This paper conducts a rigorous exploration of machine learning methodologies, from Bayesian classifiers to k-means clustering, offering an analytical perspective on their advantages and challenges. As the industry inclines towards innovations like AntFinGLM, the imperatives of professionalism, precision, and data sanctity gain significance. Upholding standards that encompass five dimensions and 28 categories, AntFinGLM epitomises these benchmarks, championing enhanced functionalities while fostering collaborative initiatives with financial entities. Addressing challenges, particularly around data security and professional integrity, becomes crucial. Techniques encompassing intent recognition, fact verification, and robust data protection mechanisms are indispensable. In summation, the endeavours of entities like AntFinGLM underscore the transformative prowess of expansive language models, ushering the financial sector into an epoch characterised by astute, efficient, and safeguarded decision-making paradigms.

DIRECT EFFECT ANALYSIS OF ONLINE INTEGRATED BANKING SYSTEM IMPLEMENTATION ON CUSTOMER SATISFACTION AND COMPLIANCE OF SUMUT BANK

This study investigates the influence of the OLIBs management information system implementation in PT Bank Sumut Pematang Siantar Branch's banking services on customer satisfaction, loyalty, and compliance. Employing quantitative analysis via Smart PLS, collected data was assessed. Outcomes highlight a significant positive impact of OLIBs on customer satisfaction, loyalty, and compliance. Smart PLS analysis establishes notable connections between OLIBs-related factors (service quality, accessibility, personalization, data security) and customer-oriented aspects. The study suggests that embracing OLIBs can amplify customer satisfaction, loyalty, and compliance. Implications extend to PT Bank Sumut Pematang Siantar Branch and other financial entities, providing insights to refine strategies, uphold robust relationships, and ensure compliance, ultimately enhancing overall customer experiences.

Board structure and risk-taking behavior: evidence from the financial sector of Pakistan

PurposeThe board structure (BS) is pivotal in modern corporate governance (CG). This study aims to investigate BS variables (BSIZE, BIND and chief executive officer [CEO] duality) and their correlation with risk-taking behavior indicators, enriching the understanding of how CG shapes financial institutions’ (FIs) decision-making in Pakistan.Design/methodology/approachBy scrutinizing data from 67 financial entities listed on the Stock Exchange of Pakistan spanning from 2011 to 2022 through panel data regression techniques, the research emphasizes that BS holds a substantial influence over the risk tendencies exhibited by these firms.FindingsKey findings suggest that board size has a positive influence, aligned with previous CG research. Smaller boards perform better and avoid excessive risk-taking, contrasting some negative relationship claims. More independent directors are recommended to curtail risk and financial disruption. Holding both CEO and chair roles reduces risk exposure, resonating with reputational and employment risk theory. It is essential to recognize that BS’s impact on risk-taking is nuanced and context-dependent.Practical implicationsPolicymakers, scholars, practitioners and investors working in the market for financial companies might greatly benefit from the empirical findings of this study. Imposing mandates on FIs to uphold adequate capital reserves functions as a safeguard against unforeseen losses, thereby diminishing the probability of unwarranted risk-taking.Originality/valuePrior studies in this domain predominantly focus on nonfinancial sectors. In addition, existing research often explores the relationship between BS and firm risk-taking solely within the banking sector, overlooking other FIs. This study contributes by using a comprehensive data set encompassing all types of FIs, thus extending the existing literature.

Human capital management – values, competencies, and motivation – concerning Industry 4.0

The article aims to determine the current situation in economic subjects (ESs), what values and competencies are for managers and executives, and what motivational factors are essential for financial entities in the era of Industry 4.0. The article used standard scientific methods, such as analysis, synthesis, induction, and deduction, but also methods, such as content analysis of professional and scientific literature, comparison, modelling, and basic statistical methods, which verified the dependencies between the selected elements. The article processes data from a questionnaire survey conducted in 2020 (905 respondents) and 2021 (561 respondents). The respondents who filled out the questionnaire survey were managers or owners of ESs, which are based in Slovakia and are classified as micro, small, medium, or large enterprises. We found in the study that there is a dependence between the employment orientation of managers and the use of career motivation factors, as well as between the passion for work and the creativity of employees, and between the technological and IT skills of managers and executive employees. It is surprising that ES in Slovakia consider soft skills more important than technological ones despite the pressure to support and develop people’s digital skills.

The Disguise of Cyber Crime in Illegal Investment Entities Post the Re-formulation of Law No. 11 of 2020 Concerning Job Creation in Indonesia

This research delves into cybercrime in the post-truth era, where falsehoods are often masked as truths. This phenomenon, known as "talbis talbis," gives rise to illegal activities in the cyber world that exploit cybercrime scams such as phishing, pharming, sniffing, money mule, and social engineering. Despite being harmful, online fraud crimes are sometimes perceived positively by the public. Data from the Ministry of Communication and Information of the Republic of Indonesia in 2022 indicates that a majority of respondents have experienced online digital fraud, especially through fake gift schemes and illegal online loans. The Financial Illegal Activity Eradication Task Force (PASTI) has blocked illegal financial entities, including bogus investments and illegal online loans. Illegal investment crimes primarily rely on duplicating licensed entity websites, deceiving the public with promises of high returns. This study reveals the modus operandi of domestic illegal investment crimes and compares them with regulations governing foreign direct investment. The conclusion emphasizes the need for assertiveness from PASTI and the Investment Alert Task Force of the Financial Services Authority in supervising and providing legal protection for legal foreign direct investment activities in Indonesia.