Cyberattack Ramifications, The Hidden Cost of a Security Breach

In this in-depth exploration, I delve into the complex implications and costs of cybersecurity breaches. Venturing beyond just the immediate repercussions, the research unearths both the overt and concealed long-term consequences that businesses encounter. This study integrates findings from various research, including quantitative reports, drawing upon real-world incidents faced by both small and large enterprises. This investigation emphasizes the profound intangible costs, such as trade name devaluation and potential damage to brand reputation, which can persist long after the breach. By collating insights from industry experts and a myriad of research, the study provides a comprehensive perspective on the profound, multi-dimensional impacts of cybersecurity incidents. The overarching aim is to underscore the often-underestimated scope and depth of these breaches, emphasizing the entire timeline post-incident and the urgent need for fortified preventative and reactive measures in the digital domain.

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.

A Study on The Timeliness of Credit Rating on Bond Defaults--Evidence from Chinese Bond Market

With the increase of China’s bond issuance and slowdown of the economic growth,the potential credit risks such as bond default in the bond market are gradually emerging.The frequent occurrence of bond defaults and the problem of false credit ratings make bond investors and market participants more cautious about the credit ratings issued by rating agencies.Based on the default bonds from 2016 to 2019,this paper analyzes the adjustment of rating of defaulted bonds by rating agencies before default.It also compares the impact of both the regulatory events and the entrance of international agencies on timeless of credit ratings on default bonds.At the same time,the divergence of rating timeliness between different rating agencies is compared.The research shows that after the unified supervision of regulators and the punishment of Dagong Global Credit Rating Co.Ltd in 2018,the timeliness of rating agencies'downgrading of defaulted bonds has increased significantly;Compared with other rating agencies,the timeliness of rating agencies owned by international rating agencies are better.

Ruin probabilities with random rates of interest

A model was proposed for addressing investment risk of the flee reserve in the form of credit or currency risk. This risk was expressed by a constant amount K （ e. g., securitization） upon an interest-increasing event and a random variable Z representing the recovery rate of a bond or a devaluation factor. The model equation is an integro-differential equation with deviating arguments. The analytical solutions were obtained for the probability of survival as Z is a discrete random variable and as Z is a continuous random variable respectively.

Clinical efficacy and safety of flexible ureteroscopy and percutaneous nephrolithotomy for large kidney stones:A retrospective comparative study

BACKGROUND Renal stones ranging 20–40 mm are very common in China.Although no largesample clinical studies have confirmed the clinical efficacy and safety of this method,there is also a lack of comparative data with traditional treatment.AIM To investigate the clinical efficacy of flexible ureteroscopy(FURS)and percutaneous nephrolithotomy(PCNL)by postoperative stone clearance and changes in soluble vascular cell adhesion molecule 1(sVCAM-1)and kidney injury molecule 1(KIM-1)levels in patients with large kidney stones(>2 cm in diameter).METHODS This single-center observational study was performed at a Chinese hospital between January 1,2021,and October 30,2023.All 250 enrolled patients were diagnosed with large kidney stones(>2 cm)and divided into a FURS group(n=145)and a PCNL group(n=105)by the surgical method.The FURS group was treated with flexible ureteroscopy and the PCNL group was treated with percutaneous nephrolithotomy.The operation time,time to palinesthesia,intraoperative blood loss,drop in hemoglobin,length of hospital stay,stone clearance rate,and complications were recorded in the two groups.Preoperative and postoperative serum sVCAM-1 levels,erythrocyte sedimentation rate(ESR),urine KIM-1 levels,preoperative and postoperative pain visual analog scale(VAS)and Wisconsin Stone Quality of Life Questionnaire(WISQOL)scores were also documented.RESULTS All 250 eligible patients completed the follow-up.There were no significant differences in baseline characteristics between the two groups(P>0.05).The operation time in the FURS group was significantly greater than that in the PCNL group.The time to ambulation,intraoperative blood loss,decrease in hemoglobin,and length of hospital stay were significantly lower in the FURS group than in the PCNL group.The FURS group also had a significantly higher stone clearance rate and a lower incidence of postoperative complications.There was no significant difference in antibiotic use between the groups.Postoperative serum sVCAM-1 levels,urine KIM-1 levels,and VAS scores were lower in the FURS group than in the PCNL group,but postoperative ESR and WISQOL scores were greater in the FURS group than in the PCNL group.CONCLUSION FURS demonstrated superior clinical efficacy in treating large kidney stones(>2 cm in diameter)compared PCNL.It not only improved the postoperative stone clearance rate and reduced complications and recovery time but also positively affected serum SCM-1,ESR,and urine KIM-1 levels,subsequent improvement of patient quality of life.

Detecting conflicts of interest in credit rating changes:a distribution dynamics approach

In this study,we compare the adjustments of credit ratings by an investor-paid credit rating agency(CRA),represented by Egan-Jones Ratings Company,and an issuer-paid CRA,represented by Moody’s Investors Service,vis-à-vis conflict of interest and reputation.A novel distribution dynamics approach is employed to compute the probability distribution and,hence,the downgrade and upgrade probabilities of a credit rating assigned by these two CRAs of different compensation systems based on the dataset of 750 U.S.issuers between 2011 and 2018,that is,after the passage of the Dodd–Frank Act.It is found that investor-paid ratings are more likely to be downgraded than issuerpaid ratings only in the lower rating grades,which is consistent with the argument that investor-paid agencies have harsher attitudes toward potentially defaulting issuers to protect their reputation.We do not find evidence that issuer-paid CRAs provide overly favorable treatments to issuers with threshold ratings,implying that reputation concerns and the Dodd–Frank regulation mitigate the conflict of interests,while issuerpaid CRAs are more concerned about providing accurate ratings.

The impact of working capital management on credit rating

This study investigates the possible nonlinear relationship between working capital and credit rating.Furthermore,it examines the relationship between the three components of working capital(inventory,accounts receivable,and accounts payable)and a firm’s credit rating.Employing data for U.S listed firms for the period between 1985 and 2017,the results of our ordered probit model show a nonlinear relationship between working capital and its components and credit rating.Finally,we find that the deviation from the optimal working capital adversely affects the credit rating.The results of this study are of significant importance for policy makers,managers,decision makers,and credit-rating agencies,as they help highlight the importance of working capital management for a firm’s credit rating.

Research on the Influencing Factors of Personal Credit Based on a Risk Management Model in the Background of Big Data

Between states, between enterprises and enterprises, between people, it can be stated that credit is full of every corner of our lives. But the current lack of social credit is fundamental. Credit risk is particularly prominent. In the extensive data generation today, the information on personal credit statistics is very large, but still lack the data system processing and screening. Through the information retrieval of 200 credit information reports, this paper constructs the evaluation system of personal credit by using the basic information of the individual. The basic information of these individuals has great convenience in information collection and information statistics, and this basic information covers all aspects that are likely to result in the breach of contract. Through the use of single factor analysis and logistic model to solve the index system, you can not only find the impact of individual indicators on the degree of personal credit, but also see the overall impact of indicators on the degree of credit, that is, the weight of the indicators. Finally, four different credit ratings are divided by assigning the indicators to the scores. Credit rating can clearly measure the respective credit situation. Through the classification of these levels, measuring the credit line when a person in the individual credit operation, at the same time, it can provide reference and proval to administrative departments, which is benefit for managing credit risks. It has a substantial meaning and value in use. The solution to the rating system cannot only be applied to individuals, but also to the enterprises, with a wide range of versatility.

The valuation of multi-counterparties CDS with credit rating migration

In this paper,the pricing of a Credit Default Swap(CDS)contract with multiple counterparties is considered.The pricing model takes into account the credit rating migration risk of the reference.It is a new model established under the reduced form framework,where the intensity rates are assumed to have structural styles.We derive from it a non-linear partial differential equation system where both positive and negative correlations of counterparties and the references are considered via a single factor model.Then,an ADI(Alternating Direction Implicit)difference method is used to solve the partial differential equations by iteration.From the numerical results,the comparison of multi-counterparty CDS contract and the standard one are analyzed respectively.Moreover,the impact of default parameters on value of the contracts are discussed.

Measuring the model risk-adjusted performance of machine learning algorithms in credit default prediction

Implementing new machine learning(ML)algorithms for credit default prediction is associated with better predictive performance;however,it also generates new model risks,particularly concerning the supervisory validation process.Recent industry surveys often mention that uncertainty about how supervisors might assess these risks could be a barrier to innovation.In this study,we propose a new framework to quantify model risk-adjustments to compare the performance of several ML methods.To address this challenge,we first harness the internal ratings-based approach to identify up to 13 risk components that we classify into 3 main categories—statistics,technology,and market conduct.Second,to evaluate the importance of each risk category,we collect a series of regulatory documents related to three potential use cases—regulatory capital,credit scoring,or provisioning—and we compute the weight of each category according to the intensity of their mentions,using natural language processing and a risk terminology based on expert knowledge.Finally,we test our framework using popular ML models in credit risk,and a publicly available database,to quantify some proxies of a subset of risk factors that we deem representative.We measure the statistical risk according to the number of hyperparameters and the stability of the predictions.The technological risk is assessed through the transparency of the algorithm and the latency of the ML training method,while the market conduct risk is quantified by the time it takes to run a post hoc technique(SHapley Additive exPlanations)to interpret the output.

From Credit Fraud to Meaningful Recovery： The Role of Credit Rating Agencies and How Auditors Might Be Affected by the Dodd-Frank Act

The way investors, banks and constituents rely on rating agencies will drastically change with the implementation of the Dodd-Frank Act. The historical background of rating agencies including potential changes in the process of issuing their reports after the Dodd-Frank act is explored by the authors. CPAs （Certified Public Accountant） audit the financial statements of Securities and Exchange Commission [SEC] regulated issuers and are subject to the provisions of the Dodd-Frank act. Accountants may have new potential liabilities with clients that rely on credit agencies representations in financial statements. Analysis is made and conclusions are drawn on the effects of new credit rating agency responsibilities and that of auditors.

An Evaluation of the Effect of Credit Risk Management （CRM） on the Profitability of Nigerian Banks

This paper assesses the effect of credit risk management （CRM） on the profitability of Nigerian banks with a view to discovering the extent to which default rate （DR）, cost per loan asset （CLA）, and capital adequacy ratio （CAR） influence return on asset （ROA） as a measure of banks＇ profitability. Data were generated from secondary sources, specifically, the annual reports and accounts of quoted banks from 2002 to 2011. Descriptive statistics, correlation, as well as random-effect generalized least square （GLS） regression techniques were utilized as tools of analysis in the study. The findings establish that CRM as measured by three independent variables has a significant positive effect on the profitability of Nigerian banks as indicated by the coefficient of determinations ＂R2 value＂ which shows the within and between values of 40.89% and 58.35% （which are impressive） while the overall R2 iS 43.91%, indicating that the variables considered in the model account for about 44% change in the dependent variable, that is, profitability. The study recommends that banks＇ management should be more scientific （application of risk evaluation techniques） in their credit risk assessment and management of loan portfolios in order to minimize the high incidence of non-performing loans and their negative effect on profitability.

Research on the Pricing of Convertible bonds in China Migration risk based on credit rating

At present,further research and exploration on credit risks are being carried out in the global field,and increasingly profound modem credit risks are exposed to the bond market.This requires that we cannot ignore the impact of credit rating migration risk on bond pricing,so as to adapt to the sustainable and healthy development of the bond market under the new normal of China's economy.The innovation point of this paper is to try to analyze the pricing of Convertible bonds in China from the perspective of credit rating migration risk.Tsiveriotis and Femandes(1998)model is selected,and the credit risk in the model is assumed to be caused by the credit rating migration risk,and the credit spread is used to measure the credit rating migration risk.The research conclusion of this paper is as follows:First,it is valid to consider the risk of credit rating migration in the TF(1998)model.The market price of convertible bonds is on average 1.22% higher 1han the theoretical value of the model.In general,the theoretical value obtained from the model has little deviation from the market price,and has a good fitting degree.Second,from the Angle of credit rating,the selection of 32 samples of convertible bonds only empirical research shows that the credit rating of AA-convertible bonds average deviation rate is negative,suggest that the credit rating of AA-the phenomenon of convertible bonds value is underestimated,and AAA credit rating to AA,AA+,the average deviation rate of convertible bonds is positive,that credit rating AA(containing AA)more convertible bond value is overrated phenomenon,and the higher the credit rating of the average deviation rate of convertible bond,the greater the overvalued levels.It has certain guiding significance for participants in the convertible bond market.

The Development of an Alternative Method for the Sovereign Credit Rating System Based on Adaptive Neuro-Fuzzy Inference System

The main purpose of this article is to determine the factors affecting credit rating and to develop the credit rating system based on statistical methods, fuzzy logic and artificial neural network. Variables used in this study were determined by the literature review and then the number of them was reduced by using stepwise regression analysis. Resulting variables were used as independent variables in the logistic model and as input variables for ANN and ANFIS model. After evaluating the models and comparing with each other, the ANFIS model was chosen as the best model to forecast credit rating. Rating determination was made for the countries that haven’t had a credit rating. Consequently, the ANFIS model made consistent, reliable and successful rating forecasts for the countries.

P2P network lending in the credit risk rating of the individual

P2P lending network is person to person lending network, lnternet-based applications, individuals lending financial model to others through the network intermediary,＇ platform. Currently P2P lending network has developed rapidly, but the P2P network lending platform also are lacing increasing risks, the biggest risk is credit risk. This article from the credit rating perspective, comparative analysis of the existing credit rating methodology, Analysis to establish a relatively sound credit rating mechanisms, thus reducing credit risk.

Does the Financial Status of Company Affect the Bond Credit Rating?--Empirical Evidence from China's Shanghai and Shenzhen Stock Exchanges

This article takes the companies that publicly issued corporate bonds on the Shanghai and Shenzhen Stock Exchanges from 2006 to 2018 as the research objects selecting six aspects that comprehensively reflect the 17 financial variables in 6 aspects:profitability,operating ability,bond repayment ability,development ability,cash flow and market value of the company.Principal component analysis method and factor analysis method are used to extract the principal factors of these financial indicator variables.That is how an ordered multi-classification Logistic regression model is constructed to test the impact of the Shanghai and Shenzhen Stock Exchanges’financial status on the corporate bond credit rating.It turns out that the financial status of the Shanghai and Shenzhen Stock Exchanges have an important impact on the credit rating of corporate bonds.The financial status has a greater impact on corporate bonds with credit ratings of A-and AA-,while it has a smaller impact on corporate bonds with credit ratings above AA.The results of this article can help individual and institutional investors prevent risks from investing.

Dynamic Characteristics of Transmission System for the Internal Grinder

The dynamics model of the transmission system of the internal grinder is established on the bases of Riccati transfer matrix. The dynamic characteristics of the internal grinder are obtained by analyzing the relationship between dynamic modal flexibility and modal flexibility, which is used to find out the dangerous model of the transmission system and its weak areas. Then design parameters of weak areas are modified, the new one from the old structure is put forward, and the dynamic characteristics of new ...

Sources and significance of variation in basal,summit and maximal metabolic rates in birds

The rates at which birds use energy may have profound effects on fitness, thereby influencing physiology, behavior, ecology and evolution. Comparisons of standardized metabolic rates （e.g., lower and upper limits of metabolic power output） present a method for elucidating the effects of ecological and evolutionary factors on the interface between physiology and life history in birds. In this paper we review variation in avian metabolic rates [basal metabolic rate （BMR; minimum normothermic metabolic rate）, summit metabolic rate （Msum; maximal thermoregulatory metabolic rate）, and maximal metabolic rate （MMR; maximal exercise metabolic rate）], the factors associated with this variation, the evidence for functional links between these metabolic traits, and the ecological and evolutionary significance of avian metabolic diversity. Both lower and upper limits to metabolic power production are phenotypically flexible traits, and vary in association with numerous ecological and evolutionary factors. For both inter- and intraspecific comparisons, lower and upper limits to metabolic power production are generally upregulated in response to energetically demanding conditions and downregulated when energetic demands are relaxed, or under conditions of energetic scarcity. Positive correlations have been documented between BMR, Msum and MMR in some, but not all studies on birds, providing partial support for the idea of a functional link between lower and upper limits to metabolic power production, but more intraspecific studies are needed to determine the robustness of this conclusion. Correlations between BMR and field metabolic rate （or daily energy expenditure） in birds are variable, suggesting that the linkage between these traits is subject to behavioral adjustment, and studies of the relationship between field and maximal metabolic rates are lacking. Our understanding of avian metabolic diversity would benefit from future studies of： （1） the functional and mechanistic links between lower and upper limits of metabolic power output; （2） the environmental and ecological cues driving phenotypically flexible metabolic responses, and how responses to such cues might impact population responses to climate change; （3） the shapes of metabolic reaction norms and their association with environmental variability; and （4） the relationship of metabolic variation to fitness, including studies of repeatability and heritability of minimum and maximum metabolic power output [Current Zoology 56 （6）： 741-758, 2010].

Effect of Preoperative Double-J Ureteral Stenting before Flexible Ureterorenoscopy on Stone-free Rates and Complications

The effect of preoperative Double-J(DJ)ureteral stenting before flexible ureterorenoscopy(FURS)in the treatment for urinary stones was evaluated.We retrospectively enrolled 306 consecutive patients who underwent FURS from Jan.2014 to Dec.2017.All the patients were classified into two groups according to whether they had DJ ureteral stenting before FURS.Baseline characteristics(age,sex,stone location,stone size,surgical success rate,operation time,stone-free rate of the first day after surgery,stone-free rate of the first month after surgery,total complication rate)were compared using Chi-square test for categorical variables and Kruskal-Wallis test for continuous variables.In total,306 patients were included in this study.The group of DJ stenting before FURS included 203(66.3%)patients,and non-DJ stenting before FURS was observed in 103(33.7%)patients.The group of DJ stenting before FURS was significantly associated with a shorter operation time(53.8 vs.59.3 min,P<0.001),a higher stone-free rate of the first day after surgery(69.0%vs.51.5%,P=0.003).However,statistical significant differences were not found in the age,sex,stone location,stone size,surgical success rate,stone-free rate of the first month after surgery(89.2%vs.81.6%,P=0.065)and total complication rate(5.4%vs.9.7%,P=0.161)between the two groups.Preoperative DJ ureteral stenting before FURS could reduce the operation time and increase stone-free rate of the first day after surgery.However,it might not benefit the stone-free rate of the first month after surgery and reduce the complication rate.Preoperative DJ stenting should be not routinely performed.

Value of big data to finance:observations on an internet credit Service Company in China

Background:his paper presents a case study on 100Credit,an Internet credit service provider in China.100Credit began as an IT company specializing in e-commerce recommendation before getting into the credit rating business.The company makes use of Big Data on multiple aspects of individuals’online activities to infer their potential credit risk.Methods:Based on 100Credit’s business practices,this paper summarizes four aspects related to the value of Big Data in Internet credit services.Results:1)value from large data volume that provides access to more borrowers;2)value from prediction correctness in reducing lenders’operational cost;3)value from the variety of services catering to different needs of lenders;and 4)value from information protection to sustain credit service businesses.Conclusion:The paper also discusses the opportunities and challenges of Big Databased credit risk analysis,which needs to be improved in future research and practice.