Credit Entities Research Articles

RATS: A regulatory anonymous transaction system based on blockchain

With the rapid development of digital currency such as Bitcoin, the digital currency transaction system with blockchain as the key underlying technology is booming, but the traditional transaction system has the risk of revealing sensitive information such as transaction content and identity. In order to enhance the security, many transactions system with privacy preserving have been proposed, such as Zerocoin, Monero, etc. As there are a decentralized credit entity and strong anonymity in these transaction systems, the authorities can effectively audit and control the participants and transactions in the digital currency system, thus making digital currency a tool for illegal transactions. Recognizing the importance of privacy preserving and regulatory, in this paper, we propose a new regulatory anonymous transaction system based on blockchain—RATS, which can not only protect the privacy of transactions on the blockchain, but also regulate illegal transactions. Firstly, we introduce regulators into the system, and at the same time, we propose a regulatory mechanism that the regulator is allowed to trace the identity of the user without affecting the transaction operation of the system when suspicious transactions are found. In particularly, during the normal transaction, we protect the privacy of users' transaction contents and addresses without affecting the anonymity of the original system. We formalize the system model and security model of RATS. Moreover, the security of the proposed scheme is strictly proved and analyzed.

Multi-Feature Fusion Method for Chinese Shipping Companies Credit Named Entity Recognition

Shipping Enterprise Credit Named Entity Recognition (NER) aims to recognize shipping enterprise credit entities from unstructured shipping enterprise credit texts. Aiming at the problem of low entity recognition rate caused by complex and diverse entities and nesting phenomenon in the field of shipping enterprise credit, a deep learning method based on multi-feature fusion is proposed to improve the recognition effect of shipping enterprise credit entities. In this study, the shipping enterprise credit dataset is manually labeled using the BIO labeling model, combining the pre-trained model Bidirectional Encoder Representations from Transformers (BERT) and bidirectional gated recurrent unit (BiGRU) with conditional random field (CRF) to form the BERT-BiGRU-CRF model, and changing the input of the model from a single feature vector to a multi-feature vector (MF) after stitching character vector features, word vector features, word length features, and part-of-speech (pos) features; BiGRU is introduced to extract the contextual features of shipping enterprise credit texts. Finally, CRF completes the sequence annotation task. According to the experimental results, using the BERT-MF-BiGRU-CRF model for NER of shipping enterprise credit text data, the F1 Score (F1) reaches 91.7%, which is 8.37% higher than the traditional BERT-BiGRU-CRF model. The experimental results show that the BERT-MF-BiGRU-CRF model can effectively perform NER for shipping enterprise credit text data, which is helpful to construct a credit knowledge graph for shipping enterprises, while the research results can provide references for complex entities and nested entities recognition in other fields.

Розвиток цифрових інновацій на ринку кредитних послуг України

Digital technologies nowadays play a key role in the development of the entire financial system of the country. The consequences of such influence are especially noticeable in the sphere of functioning of banking and non-banking institutions. These financial intermediaries are precisely the ones who today actively attract, create and use information and communication innovations in their own activities, allowing them to improve the quality of services provided to their clients and ensure the growth of the efficiency of their own activities. The article analyzes the role of modern innovations, primarily in the sphere of digitalization of financial relations, in the development of the market of credit services of Ukraine. The main attention is focused on deepening the theoretical provisions of the functioning of such a market in the new conditions – with the active development of information and communication technologies. Thus, the question of the role of information innovations in the processes of transformation of the credit services market is considered. Also, significant attention is paid to the issues of separation and specification of the role of individual credit innovations in the development of relations between credit institutions and their customers. In the article, such innovations primarily include p2p lending, remote servicing and functioning of neobanks; the essence of these new directions of development of the credit services market is considered and the peculiarities of their use by credit entities are described. It is determined that digital technologies already play a key role in the development of relations between lenders and borrowers in Ukraine. The results of the carried out analysis confirm the assumption that such technologies will be actively used by banking and non-banking institutions in the future. At this, it can definitely be argued that the level of application of information and communication technologies by these institutions will only grow in the future, taking into account new promising directions of their application in the sphere of financial services.

Heuristic Algorithm for Cross‐Platform Credit Risk Transmission Based on Hybrid Strategies

Credit risk transmission between cross‐platforms is an important issue in the construction of a credit service system. The effect of credit risk transmission between credit entities (nodes) is analyzed in this paper. A heuristic algorithm based on hybrid strategies (HAHS) is proposed to find risk transmission paths and calculate the influence of nodes. Besides, a novel community model is applied to predict the credit risk areas in advance. In detail, the mathematical association structure between credit entities is firstly given in the algorithm, and the breadth first search algorithm is used to find the hierarchical nodes on the credit risk transmission paths. Then, the characteristics of credit risk transmission are analyzed, and the calculation methods of single‐path and multipath influence are proposed. Finally, the credit entities are divided into communities based on a greedy strategy considering the characteristics of the credit entity association structure. The threshold control strategy is adopted to find global key nodes among all of the entities and local key nodes in communities, respectively, so as to realize the early warning of credit risk.

Mortgage Lending as a Component of Economic Growth

The purpose of the article is to reveal the role and importance of the mortgage lending development to overcome the financial and economic crisis and ensure the positive dynamics of macroeconomic indicators. The article reveals the essence of mortgage lending, substantiates the necessity of its development and improvement to create an effective mortgage lending system in Ukraine, which helps to solve the problems related to providing housing for the population and accelerating the development of not only the construction industry but also related areas of the activity. It is proven within the study that the volume and dynamics of the investment in housing has a significant impact on the macroeconomics, and therefore, by improving the mortgage lending system, it is possible to transmit positive impulses to the real sector of the economy and bring the country out of crisis. The article outlines the features of a mortgage lending which distinguish it into a separate sphere in the credit market. Based on these features, the functions of mortgage lending in modern conditions are defined, namely: investment, social, stimulating, and formation of the fictitious capital in the securities market. The research proves the importance of developing and improving mortgage lending by identifying the benefits and disadvantages of all credit entities. On the basis of statistics, the main parameters of the domestic mortgage market, which indicate a conservative approach to the formation of lending conditions and the reluctance of banking institutions to provide long-term mortgages, are determined. The main reason for this situation is the imperfect legal base of real estate lending. It has been concluded by the study results that mortgage lending is an important tool for ensuring the social and economic growth of a country, and its role and importance have increased significantly since the financial and economic crisis. JEL classіfіcatіon: G21 Manuscript received 27.04.2020

Associated Credit Risk Contagion with Incubatory Period: A Network-Based Perspective

Associated credit risk is a kind of credit risk among the associated credit entities formed by credit-related entities. Focusing on this hot topic of associated credit risk and the relevant contagion and considering the latent entities and their incubatory period, this paper builds an infectious dynamic model to describe the associated credit risk contagion of associated credit entities based on the mean-field theory of complex networks. Firstly, this paper analyzes the stable state of the associated credit risk contagion in the associated entity network, considering the latent entities and their incubatory period. Secondly, from the perspective of complex network and considering the incubatory period, a SHIS model is built to reveal how the incubatory period influences associated credit risk contagion. Finally, the sensitivity of some parameters is analyzed in the Barabási–Albert (BA) scale-free network. The results show the following: (i) the contagion threshold of associated credit risk is related to the incubatory period of latent entities, the recovery rate and infectivity of infected entities, and the newborn rate of credit entities; (ii) the infectious rate of infected entities, the mortality rate of credit entities, and the important factors stated in (i) are all significantly correlated with the density of infected entities.

¿Los Sistemas de Garantía se orientan al prestatario o a las entidades de crédito? Estudio de la experiencia en Latinoamérica

Los sistemas de garantía responden a diversos tipos de esquemas y presentan diseños particulares sin que se haya estudiado hasta la fecha la eficacia de los mismos. Por otra parte, la actividad de garantía es beneficiosa para el empresario y para la entidad financiera, encontrando ambos agentes intereses comunes en los mismos que, unidos a los del sector público, configuran la actividad de garantía como una política que encuentre los vectores de coordinación más eficaces. El objetivo de este trabajo es explicar si las características de los sistemas se orientan a la atención de las entidades de crédito o de los prestatarios. Nuestros resultados revelan que los sistemas latinoamericanos utilizan a las entidades crediticias como distribuidoras y son las características relacionadas con satisfacer las necesidades de la banca las que determinan un mayor número de pymes beneficiarias.

Credit rating and microfinance lending decisions based on loss given default (LGD)

This paper proposes a credit rating model that considers the impact of key macroeconomic variables on commercial banks' credit decisions and loss given default (LGD). The findings provide additional insight into the phenomena that under some circumstances a higher credit rating may lead to a higher LGD. The empirical analysis is based on actual bank data from 2,044 farmers in China. The theoretical analysis and empirical verification provides key insights into regulatory and commercial bank credit policy in a developing country setting, while helping to alleviate financing problems of small and micro credit entities.

La industria bancaria española frente a los nuevos modelos de negocio «Fintech». ¿Competencia, colaboración o integración? «fintegration»

El sector bancario está en un proceso continuo de transformación que no deja de ser un reflejo de los cambios profundos que se están produciendo en la sociedad como consecuencia de las nuevas tecnologías. Hoy los bancos están en lucha por el cliente no solo con otros bancos, sino con todo tipo de «no-bancos» que desarrollan los modelos de negocio FinTech. En este contexto de transformación digital planetaria, no solo actúan exclusivamente startups , sino las grandes tecnológicas (como las denominadas «GAFAs»), las Telecos o los grandes retailers que deciden desarrollar productos y servicios financieros, conformando una nueva competencia en los modelos de negocio FinTech. Analizaremos en este artículo la reacción de la industria bancaria ante la irrupción de estos nuevos servicios y estos nuevos competidores: cómo debe abordarse los nuevos modelos de negocio sin ignorar los objetivos de eficiencia y rentabilidad, cuáles serán realmente viables, cuándo debe establecerse la colaboración con las compañías que pueden desarrollarlos («fintegration»), o cuándo procede como única alternativa la pura competencia. Para concluir plantearemos las líneas generales de la estrategia planteada por Bankia en este nuevo contexto representadas por su participación en el Fintech Hub Insomnia y la startup Nettit.

Partial differential equation pricing method for double-name credit-linked notes with counterparty risk in a reduced-form model with common shocks

In this study, we propose a partial differential equation method for pricing a double-name credit-linked note (CLN) with counterparty risk in a reduced-form framework. The default correlation among the CLN issuer and the reference entities of the double-name CLN is related to the occurrence of “common shocks,” which can simultaneously trigger defaults in some pre-specified groups of the aforementioned credit entities. By assuming that the stochastic intensities of common shocks are directly and inversely proportional to the spot interest rate, which follows a Cox–Ingersoll–Ross process, we deduce the corresponding explicit formulae for double-name CLN values. We also conducted some numerical experiments to examine how the correlated default risks among the credit entities affect the double-name CLN values and their credit valuation adjustment.

Chinese Shadow Banking—Credit Creation Mechanism and Credit Expansion of Bank Financial Products

In China, shadow banking can be described as credit intermediations involving entities and activities outside the regular banking system broadly, also some non-bank credit entities and activities. Then we should pay more attention on shadow banking, which can particularly increase maturity and liquidity transformation, imperfect credit risk transfer and/or leverage by different financial tools. In our country, the financial system is dominated by commercial banks, so more and more internal financial innovations, especially bank financial products could be viewed as the representative of shadow banking. In essence, the process of bank financial products is not an independent credit creation, but it can enlarge the credit creation of commercial banks and enhance the scale of credit expansion by means of trust loans, entrusted loans, trust beneficiary, specific assets usufruct, and the asset pool, which will result in a higher liquidity risk. Therefore, expanding the scope of the legal deposit reserve rate, establishing more laws and regulations about bank financial products, and constantly improving the internal management mechanism of bank financial products are particularly important.

Econometric Model to Estimate Defaults on Payment in the Spanish Financial Sector in Oliver Wyman’s Stress Tests

This work develops an econometric model based on the exogenous economic variables used in Oliver Wyman´s report. In this case the model is used in order to estimate late payments (NPLs) by Spanish credit entities. A model based on variables considered to be optimal to quantify impact on the NPLs is developed by studying the aforementioned variables, modifying them and eliminating any which are superfluous. Furthermore, whether or not the model is optimal for long periods of time is corroborated. This is due to the fact that the scenario in Oliver Wyman´s report from September 2012 (Wyman 2012) is based on 30 years of Spanish economical historical data, as stated in the report itself. The results indicate the variables that have impact on defaults. The increase in housing prices, the Madrid Stock Exchange Index, the Exchange Rate the euro against USD. The Euribor 12 months and the industries Credit to other residents, decreases the delinquency. The NPLs also fell by transfers from riskier assets to SAREB. However, these results are different if the economy is growing or in recession. So the results will not be optimal but the appropriate model is employed.

Quanto CDS

This paper presents a new modeling approach for credit quanto spreads, covering credit default swap quanto spreads, bond quanto spreads and bond redenomination spreads. Credit quanto spreads are implied from a hazard rate diffusion model and a FX rate jump diffusion model, where the jumps are triggered by defaults. Here, we additionally let the expectation of a default influence the FX rate, as would be expected with rational economic agents. The quanto spread arise from correlation between the hazard rate and FX rate and a jump in the FX rate in case of default. One source of correlation is the common macroeconomic environment governing the FX and underlying credit entities. Another source stems from the FX rate depreciation at default of the credit entity. This second source can be subdivided into the direct depreciation effect and FX rate changes arising from changes in credit default expectation by the economic agents. Correlation arising from a common macroeconomic environment, will be present for all credit entities, whereas correlation arising from movements of the FX rate at default or at changes of default expectation, will be significant only for systemically important credit entities. We find that rational agent behavior reduces the credit quanto effect which arises from FX jumps when credit defaults. Numerical results are obtained by Monte Carlo simulations. Analytically, and model independently, we find that the credit default swap quanto spread can be expressed directly in terms of bond prices and annuities and is roughly equal to the bond quanto spread.

Access, acceptance and use of payment instruments in Colombia

Individual decisions about whether or not to use the payment instruments offered by credit entities depends on their access cost. Their use, however, is inevitably determined by the administrative costs of each instrument, people’s preferences and merchants’ level of acceptance. The use of credit cards, cheques and orders for electronic funds transfers is more common in developed countries than in emerging countries such as Colombia, where less than half the population have access to these alternative forms of payment. In the case of this country, the fundamental predictors of the consumers’ preferences with respect to payment are people’s education and income. Meanwhile, accepting such instruments depends on the sales volume of the business and the degree of formality with which the business has been established. Thus, the propensity to use payment instruments other than cash is greater among people with high and medium levels of education and income, whereas its acceptance is more common in commercial establishments that are large and have a high sales volume.

Risk Measurement for Portfolio Credit Risk Based on a Mixed Poisson Model

Experiences manifest the importance of comovement and communicable characters among the risks of financial assets. Therefore, the portfolio view considering dependence relationship among credit entities is at the heart of risk measurement. This paper introduces a mixed Poisson model assuming default probabilities of obligors depending on a set of common economic factors to construct the dependence structure of obligors. Further, we apply mixed Poisson model into an empirical study with data of four industry portfolios in the financial market of China. In the process of model construction, the classical structural approach and option pricing formula contribute to estimate dynamic default probabilities of single obligor, which helps to obtain the dynamic Poisson intensities under the model assumption. Finally, given the values of coefficients in this model calculated by a nonlinear estimation, Monte Carlo technique simulates the progress of loss occurrence. Relationship between default probability and loss level reflected through the MC simulation has practical features. This study illustrates the practical value and effectiveness of mixed Poisson model in risk measurement for credit portfolio.

El desajuste del crédito en el sistema bancario y la acción de la economía social: el camino de la reestructuración

During the last five years, after the beginning of the financial crisis in 2007, one of the major banking restructuring was caused, both in a global perspective and in a domestic dimension for Spain. The credit entities of the social economy, savings banks and credit cooperatives, have led an extraordinary concentration process. The first credit entities, suffered a radical transformation that has modified their corporate structure by converting many of them into banks, and consequently, its business model. From another perspective, the crisis has revealed the failure of financial institutions to fulfill their primary mission as credit entities. Its threatened solvency, the need to implement a strict risk control and the high default rates have led to an unprecedented restriction of lending which has ended up crushing much of the real economy or production. The three financial reforms approved by August 2012 have generated certain “discredit” between society for its direct and indirect high cost that bind to the discredited by the credit squeeze that the sector and reforms imposed

Modeling Credit Risk: An Application of the Rough Set Methodology

The Basel Accords encourages credit entities to implement their own models for measuring financial risk. In this paper, we focus on the use of internal ratings-based (IRB) models for the assessment of credit risk and, specifically, on one component that models the probability of default (PD). The traditional methods used for modelling credit risk, such as discriminant analysis and logit and probit models, start with several statistical restrictions. The rough set methodology avoids these limitations and as such is an alternative to the classic statistical methods. We apply the rough set methodology to a database of 106 companies that are applicants for credit. We obtain ratios that can best discriminate between financially sound and bankrupt companies, along with a series of decision rules that will help detect operations that are potentially in default. Finally, we compare the results obtained using the rough set methodology to those obtained using classic discriminant analysis and logit models. We conclude that the rough set methodology presents better risk classification results.

New Technical and Normative Challenges for XBRL: Multidimensionality in the COREP Taxonomy

The New Basel Capital Agreement, known as Basel II, requires some notable changes in the systems of measurement and control of risks of credit entities and investment firms. It introduces new concepts and requirements. The systems of risk management to which the Framework or Agreement makes reference can be implemented in various degrees of sophistication. By measuring the different exposures to risk with greater accuracy, a more advanced system offers such firms and entities the prospect of needing less own funds and using increased financial leverage over secure bases. The national Supervisors, in the various central banks, must approve the systems and instruments established. The new reporting tool that is destined to fulfil this function, for the moment in the context of the European Union only, is the COREP-XBRL Taxonomy. This is based on the mark-up language of the business world, the eXtensible Business Reporting Language, and makes use of the concept of Multidimensionality. This concept is being incorporated into the XBRL specification currently in force, since it is necessary for the structure of the new reporting model that is required.

Bank acquisitions and performance: evidence from a panel of European credit entities

The aim of our research is to study the effect on European Union credit entities performance of financial acquisitions, overcoming three limitations found in previous studies: most studies have focused on the United States market (characterised by higher regulatory restrictions for banking expansion both geographically and in products); they have not considered acquisitions of other banks as distinct from acquisitions of other non-banking financial entities; and statistical limitations have been evidenced. Our study, therefore, is the first to analyse bank performance derived from both the acquisition of another bank and the acquisition of other non-banking financial entities, using panel data methodology, for the period 1993–2000, in a sample of 1629 banks, where 181 acquisitions are noted. The results show an increase in the acquirers’ long-term profitability. The increase in performance, however, is more significant for bank acquisitions than for non-bank acquisitions.

The Effect of Acquisitions on the Performance of European Credit Institutions: Panel Data Analysis for the 90s

The aim of our research is to study the effect of financial acquisitions over European Union credit entities performance overcoming three limitations found in previous studies: most studies have been done for the United States market (characterised by higher regulatory restrictions for banking expansion both geographically and in products); they have not considered jointly acquisitions of other banks and acquisitions of other non-banking financial entities; and they have suffered from statistical limitations. Therefore, our study becomes the first one that analyses bank performance derived from both the acquisition of another bank and the acquisition of other non-banking financial entities, using panel data methodology during the period 1992-2000 for a sample of 2196 banks, where 240 acquisitions can be observed. The results show an increase in the acquirer's long-term profitability. In both acquisitions, when the target is a credit entity and when it is a non-banking financial entity, an increase in the acquirer's performance can be observed. Domestic acquisitions and those developed inside the European Union are more profitable than the ones taken outside EU. Lastly, the acquirer's country legal system does not affect the performance obtained, which continues being positive in the long run.