The Impact of“Fintech+Financial Regulation”Matching Level on Financial Risk:Evidence from China

Preventing financial risk is an important topic that academic circles and the government have paid attention to for a long time.The development of fintech and the improvement of financial regulation will affect the level of financial risk.The relationship between the degree of matching between fintech and financial regulation and financial risk is explored,which is crucial for reducing financial risk.Panel data from 31 provinces in China from 2011 to 2020 is used to explore the impact of fintech and financial regulatory matching levels on financial risk.The study finds that the improved matching level between fintech and financial regulation helps reduce financial risk.The degree of matching between fintech and financial regulation affects financial risk through financial efficiency.

Digital Transformation and Corporate Financial Risk:Evidence from Listed Companies in

As a core issue in enterprise operation management,corporate financial risk is directly related to the survival and development of enterprises,and digital transformation has brought new challenges to the control of corporate financial risk.Based on the data of The Shanghai Stock Exchange(SSE)and Shenzhen Stock Exchange(SZSE)from 2009 to 2022,this paper analyzes the impact of digital transformation on corporate financial risk and the impact mechanism.The empirical study finds that digital transformation significantly increases the financial risk of enterprises,and shows differences among different regions,different risk factors,and enterprise natures,and substantially increases the corporate financial risk in the East and West,non-state-owned enterprises,high-risk and low-risk enterprises.The mechanism analysis found that digital transformation would affect the financial risk of enterprises by increasing their R&D investment and reducing their debt level.The conclusion improves insights and guidance for analyzing and managing financial risks in enterprises under digital transformation.

Using Python to Analyze Financial Big Data

As technology and the internet develop,more data are generated every day.These data are in large sizes,high dimensions,and complex structures.The combination of these three features is the“Big Data”[1].Big data is revolutionizing all industries,bringing colossal impacts to them[2].Many researchers have pointed out the huge impact that big data can have on our daily lives[3].We can utilize the information we obtain and help us make decisions.Also,the conclusions we drew from the big data we analyzed can be used as a prediction for the future,helping us to make more accurate and benign decisions earlier than others.If we apply these technics in finance,for example,in stock,we can get detailed information for stocks.Moreover,we can use the analyzed data to predict certain stocks.This can help people decide whether to buy a stock or not by providing predicted data for people at a certain convincing level,helping to protect them from potential losses.

Performance-based seismic financial risk assessment of reinforced concrete frame structures

Engineering facilities subjected to natural hazards(such as winds and earthquakes) will result in risk when any designed system(i.e.capacity) will not be able to meet the performance required(i.e.demand).Risk might be expressed either as a likelihood of damage or potential financial loss.Engineers tend to make use of the former(i.e.damage).Nevertheless,other non-technical stakeholders cannot get useful information from damage.However,if financial risk is expressed on the basis of probable monetary loss,it will be easily understood by all.Therefore,it is necessary to develop methodologies which communicate the system capacity and demand to financial risk,Incremental dynamic analysis(IDA) was applied in a performance-based earthquake engineering context to do hazard analysis,structural analysis,damage analysis and loss analysis of a reinforced concrete(RC) frame structure.And the financial implications of risk were expressed by expected annual loss(EAL).The quantitative risk analysis proposed is applicable to any engineering facilities and any natural hazards.It is shown that the results from the IDA can be used to assess the overall financial risk exposure to earthquake hazard for a given constructed facility.The computational IDA-EAL method will enable engineers to take into account the long-term financial implications in addition to the construction cost.Consequently,it will help stakeholders make decisions.

Financial literacy,behavioral traits,and ePayment adoption and usage in Japan

This study investigates how financial literacy and behavioral traits affect the adoption of electronic payment(ePayment)services in Japan.We construct a financial literacy index using a representative sample of 25,000 individuals from the Bank of Japan’s 2019 Financial Literacy Survey.We then analyze the relationship between this index and the extensive and intensive usage of two types of payment services:electronic money(e-money)and mobile payment apps.Using an instrumental variable approach,we find that higher financial literacy is positively associated with a higher likelihood of adopting ePayment services.The empirical results suggest that individuals with higher financial literacy use payment services more frequently.We also find that risk-averse people are less likely to adopt and use ePayment services,whereas people with herd behavior tend to adopt and use ePayment services more.Our empirical results also suggest that the effects of financial literacy on the adoption and use of ePayment differ among people with different behavioral traits.

Chaotic dynamic behavior analysis and control for a financial risk system

According to the risk management process of financial markets,a financial risk dynamic system is constructed in this paper.Through analyzing the basic dynamic properties,we obtain the conditions for stability and bifurcation of the system based on Hopf bifurcation theory of nonlinear dynamic systems.In order to make the system＇s chaos disappear,we select the feedback gain matrix to design a class of chaotic controller.Numerical simulations are performed to reveal the change process of financial market risk.It is shown that,when the parameter of risk transmission rate changes,the system gradually comes into chaos from the asymptotically stable state through bifurcation.The controller can then control the chaos effectively.

Systemic risk management and investment analysis with financial network analytics:research opportunities and challenges

Recent economic crises like the 2008 financial tsunami has demonstrated a critical need for better understanding of the topologies and various economic,social,and technical mechanisms of the increasingly interconnected global financial system.Such a system largely relies on the interconnectedness of various financial entities such as banks,firms,and investors through complex financial relationships such as interbank payment networks,investment relations,or supply chains.A network-based perspective or approach is needed to study various financial networks in order to improve or extend financial theories,as well as develop business applications.Moreover,with the advance of big data related technologies,and the availability of huge amounts of financial and economic network data,advanced computing technologies and data analytics that can comprehend such big data are also needed.We referred this approach as financial network analytics.We suggest that it will enable stakeholders better understand the network dynamics within the interconnected global financial system and help designing financial policies such as managing and monitoring banking systemic risk,as well as developing intelligent business applications like banking advisory systems.In this paper,we review the existing research about financial network analytics and then discuss its main research challenges from the economic,social,and technological perspectives.

Intelligent Feature Selection with Deep Learning Based Financial Risk Assessment Model

Due to global financial crisis,risk management has received significant attention to avoid loss and maximize profit in any business.Since the financial crisis prediction(FCP)process is mainly based on data driven decision making and intelligent models,artificial intelligence(AI)and machine learning(ML)models are widely utilized.This article introduces an intelligent feature selection with deep learning based financial risk assessment model(IFSDL-FRA).The proposed IFSDL-FRA technique aims to determine the financial crisis of a company or enterprise.In addition,the IFSDL-FRA technique involves the design of new water strider optimization algorithm based feature selection(WSOA-FS)manner to an optimum selection of feature subsets.Moreover,Deep Random Vector Functional Link network(DRVFLN)classification technique was applied to properly allot the class labels to the financial data.Furthermore,improved fruit fly optimization algorithm(IFFOA)based hyperparameter tuning process is carried out to optimally tune the hyperparameters of the DRVFLN model.For enhancing the better performance of the IFSDL-FRA technique,an extensive set of simulations are implemented on benchmark financial datasets and the obtained outcomes determine the betterment of IFSDL-FRA technique on the recent state of art approaches.

The Effect of the 2007/2008 Financial Crisis on Enterprise Risk Management Disclosure of Top US Banks

We document the effect of the 2007/2008 financial crisis on the volume and the quality of enterprise risk management （ERM） disclosure in the annual reports of the largest US banks, and analyze its determinants. Using a content analysis approach of the annual reports form 10-K for the years 2006, 2007, 2008, and 2009, we find that the ERM disclosure is significantly and positively associated with the crisis, bank size, board independence, duality and significantly and negatively associated with profitability, leverage, and board size. This paper seeks to fill a gap in the literature by investigating the effect of the crisis on ERM disclosure in the US banking sector context, and gives an insight into the factors affecting risk disclosure practices during the financial crisis.

The Impact of Credit Ratings on Financial Performance (ROA) and Value Creation (Tobin’s Q)

This study employs a bibliometric and systematic approach to examine the impact of credit ratings as a measure of financial performance for companies listed in the S&P 500 index.The study identified a knowledge gap as only two researches were found,one suggesting and another using credit ratings to measure financial performance.Most researches use leverage,profitability,liquidity,and Share Return measures to explain financial performance.The empirical analysis uses the data of 2,398 observations of 240 companies rated by S&P Global Ratings for the period 2009-2013,applying a Generalized Method of Moments(GMM)methodology to estimate the models due to its ability to address potential endogeneity issues.The study considers Return on Assets(ROA)and Tobin’s Q as dependent variables.It incorporates credit ratings(CRWLTA)along with variables such as Total Debt to Total Assets(TDTA),Total Shareholder Return(TSR),EBITDA Interest coverage(EBITDAICOV),Quick Ratio(QR),Altman’s Z-Score(AZS),as well as macroeconomic factors like Gross Domestic Product(GDP)growth,inflation(Consumer Price Index-CPI),and the Federal Reserve Interest Rate(FDRI)as independent variables.The study argues that credit ratings,which incorporate historical data and confidential information about companies’strategies,provide reliable forward-looking creditworthiness assessments to the market.It is supported by specialized rating agencies that employ their methodologies.However,the findings suggested that CRWLTA,had a negative relationship with Q Tobin,although it was not statistically significant,and a negative relationship with ROA that was on the verge of significance.

Credit risk constraint mechanisms in rural financial reform

To research the operating mechanisms of rural financial reform, through setting up a contract model, the constraint roles of reputation and legal intervention on the default risk arising in the operating of the credit union funds are inspected. Analysis indicates that the increase in reputation cost can reduce the probability of union member default behavior and the probability of turning to the law for the credit union funds. Meanwhile, the amount of loans and the interest rates can increase the probability of turning to the law for the credit union funds. Below the marginal values, the penalty mechanisms can reduce the balancing probabilities of member default behavior and turning to the law for the credit union funds, namely, the penalty has some "substitution effect" for turning to the law for the credit union funds.

Population Ageing,Financial Leverage and Systemic Risk

Population ageing and high financial leverage are two common problems .faced by the worM＇s major economies. The recent financial crisis proved that the two issues could lead to systemic risk if not handled properly. Based on dynamic panel data from 1980 to 2012 in 119 countries, this paper examines the impact of population ageing on financial leverage J？om an empirical point of view and finds that there is a signOqcant inverted U-shape relationship between the two. In addition, empirical studies show that after passing the ＂turning point＂ of ageing, there will be a marked increase in the probability of financial crisis during the ＂deleveraging＂ process. It can be projected from the empirical conclusions of this paper that China will likely enter the range of a turning point between 2019 and 2028. After that, population ageing, deleveraging and asset price collapse may have a ＂resonance＂ effect to severely impact the stability of the financial system. Therefore, China should shift to more proactive macro financial regulations as quickly as possible, as dynamic and robust management of financial leverage and forward-looking control of bubbles could ensure that the financial system remain flexible enough to avoid systemic risk to the greatest extent.

Research on Industrial Relevance Degree and Industrial Financial Situation Risk Matrix Construction——Based on Chinese Information Technology Industry

Based on Input-Output Table in 2010 issued by National Bureau of Statistics of China, with the help of input-output model and with the calculation of indexes of industrial relevance degree in Chinese information technology industry, the paper reveals the industrial relevance in Chinese information technology industry. The paper also selects the relevant industries which are highly associated with the development of Chinese information technology industry based on industrial relevance degree to analyze the influences of these industries on the financial situation risk fluctuation in information technology industry and to design the matrix of financial situation risk in information technology industry. Then, the paper offers countermeasures and suggestions for the development of our information technology industry.

Clear Measures Set to Control Financial Risks

China’s top financial regulators have warned about risks in complicated financial products and banks’off-balance sheet business,in a bid to prevent cross-market risk contagion,according to senior officials recently.

Risks in Credit Financial Analyze

This article aims to study the indicators used in the financial analysis for credit and explain them. Also it checks the impact of each indicator in credit analysis and what happens if the pointer is changed deliberately to get the loan, giving some possible ways to do it and analyzing them. It proposes a new model to evaluate the indicators and the assignment of weights in formula evaluation of each indicator, so the risks of granting credit will be smaller as well as the evaluation of the financial terms of a company will be more balanced and optimal. The scope is to equilibrate the weights of each indicator in the fmancial credit analyze not by rescoring its value but by assigning shares in the evaluation formula. Doing this, it can be considered as a double checking using the same parameters and it lowers the risks in the money recovering. As it is debated in the article anyone can do fxaud to obtain a loan by altering the documents they provide through which some can do it good and even get uncaught. The scope is not to find what they did; it is to get protected even if they do it.

Risk Premiums and Financial Stability

The collective revelation of credit institutions as regards the imminence of specific risks materialising, which often follows long periods of underestimating probable losses, can trigger a broad-based financial deleveraging via an overly high upsurge in banks＇ risk premiums vis-a-vis the dynamics of fundamentals underlying loan repayment capability. In this context, this paper seeks to investigate the banking sector＇s internal mechanisms that might bring about a negative spiral of credit risk by building a model for the interaction between the increase of the risk premium and that of net interest income and provisioning rate. Statistical results confirm that a higher risk premium is one of the major determinants of credit default in Romania and its excessive widening could affect financial stability in Romania.

Coal price fluctuations and the impact on financial risk Evidence from China＇s coal listed companies

With the rise of coal price, the proportion of loss-making enterprises shows an upward trend in China＇s coal industry. This paper uses Altman Z-Score model to measure financial risk of 19 listed companies in the coal industry in A-share market from 1995 to 2007. Empirical results show that Year-Based price index of coal price has a negative correlation with the financial risk but has no significance, and coal chain price has a significant negative correlation with the financial risk. Further research indicates that enterprises increase bad investment, and a lot of debts caused by short-term rise in coal prices. The results also show that the financial risk in the coal industry declines with the rise of GDP growth rate and increases with the rise of inflation rate.

Claim reserving for insurance contracts in line with the International Financial Reporting Standards 17:a new paid‑incurred chain approach to risk adjustments

This study considers the risk management of insurance policies in line with the implementation of the new International Financial Reporting Standards 17.It applies the paid-incurred chain method to model the future unpaid losses by combining the information channels of both the incurred claims and paid losses.We propose the recovery of the empirical distribution of the outstanding claims liabilities associated with a group of contracts via moment-based density approximation.We determine the risk measures and adjustments that are compliant with the new standard using the Monte–Carlo simulation method and approximated distributions.The historical data on the aggregate Ontario automobile insurance claims over a 15-year period are analyzed to examine the appropriateness and accuracy of our approach.

Analysis of Identification and Supervision of Financial Risk Based on One Belt and One Road

With the continuous development andprogress of social economy, people pay more and moreattention to financial risks. Thus modern economy hasclose link with finance, and the One Belt and One Roadis a new exploration of social economy. If the moderneconomy wants better development, One Belt and OneRoad construction should be brought into economicdevelopment. And it has an impact on trade financingand outward investment of enterprises. Therefore,if it wants to be carried out smoothly, the financialmanagement mechanism should be improved. In thispaper, a concrete analysis of the identification andsupervision of financial risks will be made under OneBelt and One Road construction.

Implications of Financial and Non-financial Measures on the Refinement of the Assessments of Audit Risk： An Empirical Investigation

Identifying and assessing audit risk is a key part of the audit process. Prior research documented that auditors primarily look at financial data, information, and measures when assessing the audit risk for an audit engagement. However, professional standard setters, regulators, and academic researchers have discussed the potential for non-financial data, information, and measures to provide a powerful and independent benchmark for evaluating the validity of the numbers of financial statements of an audit client. A field study was conducted in Egypt during the years 2013 and 2014 to explore how auditors perceive and assess audit risk for an audit engagement in the period following the Egyptian revolution of January 25, 2011. The results of the field study indicated that auditors appear not to give sufficient attention to non-financial data, information, and measures when assessing the audit risk during an audit engagement. Auditors seem to rely on financial data, information, and measures when assessing the audit risk of an audit engagement. Furthermore, auditors do not seem to consider the inconsistencies between financial and non-financial data, information, and measures of an audit client as an indicator of the existence of fraud or material misstatements in the financial statements of an audit client.