scholarly journals Neural Networks in Credit Risk Classification of Companies in the Construction Sector

2018 ◽  
Vol 2 (2) ◽  
pp. 63-77 ◽  
Author(s):  
Aleksandra Wójcicka

The financial sector (banks, financial institutions, etc.) is the sector most exposed to financial and credit risk, as one of the basic objectives of banks' activity (as a specific enterprise) is granting credit and loans. Because credit risk is one of the problems constantly faced by banks, identification of potential good and bad customers is an extremely important task. This paper investigates the use of different structures of neural networks to support the preliminary credit risk decision-making process. The results are compared among the models and juxtaposed with real-world data. Moreover, different sets and subsets of entry data are analyzed to find the best input variables (financial ratios).

2021 ◽  
Vol 8 ◽  
Author(s):  
Meng Li ◽  
Shengqi Chen ◽  
Yunfeng Lai ◽  
Zuanji Liang ◽  
Jiaqi Wang ◽  
...  

Real world evidence (RWE) and real-world data (RWD) are drawing ever-increasing attention in the pharmaceutical industry and drug regulatory authorities (DRAs) all over the world due to their paramount role in supporting drug development and regulatory decision making. However, there is little systematic documentary analysis about how RWE was integrated for the use by the DRAs in evaluating new treatment approaches and monitoring post-market safety. This study aimed to analyze and discuss the integration of RWE into regulatory decision-making process from the perspective of DRAs. Different development strategies to develop and adopt RWE by the DRAs in the US, Europe, and China were reviewed and compared, and the challenges encountered were discussed. It was found that different strategies on development of RWE were applied by FDA, EMA, and NMPA. The extent to which RWE was adopted in China was relatively limited compared to that in the US and EU, which was highly related to the national pharmaceutical environment and development stages. A better understanding of the overall goals, inputs, activities, outputs, and outcomes in developing RWE will help inform actions to harness RWD and leverage RWE for better health care decisions.


Author(s):  
Sanja Vlaović Begović ◽  
Ljiljana Bonić

Decision trees made by visualizing the decision-making process solve a problem that requires more successive decisions to be made. They are also used for classification and to solve problems usually addressed by regression analysis. One of the problems of classification that arises is the proper classification of bankrupt companies and non-bankruptcy companies, which  is then used to predict the likelihood of bankruptcy. The paper uses a random forests decision tree to predict bankruptcy of companies in the Republic of Serbia. The research results show the high predictive power of the model with as much as 98% average prediction accuracy, and it is recommended for auditors, investors, financial institutions and other stakeholders to predict bankruptcy of companies in Republic of Serbia.


2021 ◽  
Author(s):  
Peter Klimek ◽  
Dejan Baltic ◽  
Martin Brunner ◽  
Alexander Degelsegger-Marquez ◽  
Gerhard Garhöfer ◽  
...  

UNSTRUCTURED Real-world data (RWD) collected in routine healthcare processes and transformed to real-world evidence (RWE) has become increasingly interesting within research and medical communities to enhance medical research and support regulatory decision making. Despite numerous European initiatives, there is still no cross-border consensus or guideline determining which quality RWD must meet in order to be acceptable for decision making within regulatory or routine clinical decision support. An Austrian expert group led by GPMed (Gesellschaft für Pharmazeutische Medizin, Austrian Society for Pharmaceutical Medicine) reviewed drafted guidelines, published recommendations or viewpoints to derive a consensus statement on quality criteria for RWD to be used more effectively for medical research purposes beyond registry-based studies discussed in the European Medicines Agency (EMA) guideline for registry-based studies


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sami Wasef Abuezhayeh ◽  
Les Ruddock ◽  
Issa Shehabat

Purpose The purpose of this paper is to investigate and explain how organizations in the construction sector can enhance their decision-making process (DMP) by practising knowledge management (KM) and business process management (BPM) activities. A conceptual framework is developed that recognises the elements that impact DMP in terms of KM and BPM. The development of this framework goes beyond current empirical work on KM in addition to BPM as it investigates a wider variety of variables that impact DMP. Design/methodology/approach A case study is undertaken in the context of the construction industry in Jordan. A theoretical framework is developed and assessment of the proposed framework was undertaken through a questionnaire survey of decision-makers in the construction sector and expert interviews. Findings The outcomes of this research provide several contributions to aid decision-makers in construction organizations. Growth in the usage of KM and BPM, in addition to the integration between them, can provide employees with task-related knowledge in the organization’s operative business processes, improve process performance, promote core competence and maximise and optimise business performance. Originality/value Through the production of a framework, this study provides a tool to enable improved decision-making. The framework generates a strong operational as well as theoretical approach to the organizational utilization of knowledge and business processes.


2018 ◽  
Vol 8 (9) ◽  
pp. 1275-1306 ◽  
Author(s):  
Rosemary Hunter

The various feminist judgment projects (FJPs) have explored through the imagined rewriting of judgments a range of ways in which a feminist perspective may be applied to the practice of judging. But how do these imagined judgments compare to what actual feminist judges do? This article presents the results of the author’s empirical research to date on ‘real world’ feminist judging. Drawing on case study and interview data it explores the how, when and where of feminist judging, that is, the feminist resources, tools and techniques judges have drawn upon, the stages in the hearing and decision-making process at which these resources, tools and techniques have been deployed, and the areas of law in which they have been applied. The article goes on to consider observed and potential limits on feminist judicial practice, before drawing conclusions about the comparison between ‘real world’ feminist judging and the practices of FJPs. Los proyectos de sentencias feministas, a través de la reelaboración imaginaria de sentencias judiciales, han explorado multitud de vías en las que las perspectivas feministas se podrían aplicar a la práctica judicial. Pero ¿qué resulta de la comparación entre dichas sentencias y la práctica real de las juezas feministas? Este artículo presenta los resultados de la investigación empírica de la autora. Se analiza el cómo, el cuándo y el dónde de la labor judicial feminista, es decir, los recursos, herramientas y técnicas feministas que las juezas han utilizado, las fases de audiencia y toma de decisión en las que se han utilizado y las áreas del derecho en que se han aplicado. Además, se toman en consideración los límites observados y potenciales de la práctica judicial feminista, y se extraen conclusiones sobre la comparación entre la labor judicial feminista en el “mundo real” y la práctica de los proyectos de tribunales feministas.


Author(s):  
Alejandro Rodríguez-González ◽  
Ángel García-Crespo ◽  
Ricardo Colomo-Palacios ◽  
José Emilio Labra Gayo ◽  
Juan Miguel Gómez-Berbís ◽  
...  

The combination of the burgeoning interest in efficient and reliable Health Systems and the advent of the Information Age represent both a challenge and an opportunity for new paradigms and cutting-edge technologies reaching a certain degree of maturity. Hence, the use of Semantic Technologies for Automated Diagnosis could leverage the potential of current solutions by providing inference-based knowledge and support on decision-making. This paper presents the ADONIS approach, which harnesses the use of ontologies and the underlying logical mechanisms to automate diagnosis and provide significant quality results in its evaluation on real-world data scenarios.


Author(s):  
Gleeson Simon

This chapter focuses on the standardized approach, which is the bedrock of the Basel system. Although many of the largest banks are internal ratings-based banks, there is probably no bank currently existing which does not use some elements of the standardized approach as part of its overall capital calculation. The discussions cover classification of exposures, credit conversion factors, and credit risk mitigation; ratings and rating agencies; exposures to sovereigns; multilateral development banks; exposures to banks and financial institutions; exposures to corporates; exposures to retail customers; commercial mortgage exposures; overdue undefaulted exposures; high-risk exposures; covered bonds; securitization exposures; short-term claims on financial institutions and corporates; fund exposures: and off-balance sheet items.


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