Origins and expansion of mortgage crisis

Servis plus ◽  
2015 ◽  
Vol 9 (3) ◽  
pp. 52-58
Author(s):  
Мария Хлопунова ◽  
Mariya Khlopunova
Keyword(s):  
Risk Assessment ◽  
Financial Crisis ◽  
Credit Risk ◽  
Global Economy ◽  
Credit Market ◽  
Mortgage Crisis ◽  
Global Coverage ◽  
Assessment Problems

The article reviews origins and expansion of mortgage crisis. The latter financial crisis found out to be unique as to losses, scale of recession, global coverage. Although the crisis had financial origins it becomes truly crisis of the global economy. The paper covers the following reasons and origins of the crisis: risk assessment problems in banks, underestimation of credit risk, realty owner failed to pay mortgage payments, the regulator failed to sustain interbank credit market. The possibilities of the new mortgage crisis pointed out in the paper.

scholarly journals Revealing “Mafia Inc.”? Financial Crisis, Organized Crime, and the Birth of New Enterprises

2020 ◽  
pp. 1-45 ◽  
Author(s):  
Marco Le Moglie ◽  
Giuseppe Sorrenti
Keyword(s):  
Financial Crisis ◽  
Organized Crime ◽  
Credit Market ◽  
Subprime Mortgage ◽  
Mortgage Crisis ◽  
Judicial Authority ◽  
Subprime Mortgage Crisis

We study the investment of organized crime in the legal economy. By using the shock induced on the Italian credit market by the 2007 subprime mortgage crisis, we document how provinces with a high organized crime presence have been impacted less by the crisis in terms of the establishment of new enterprises than provinces with a lower criminal infiltration. We provide evidence that the lower impact of the crisis is consistent with the presence of investments by organized crime in the legal economy. We corroborate this interpretation by comparing our results with the characterization made by the judicial authority of such investments.

Cross organizational standardized business process integration and its application in Saudi Arabian banking system regulation: A case study of advanced IRB regulation

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Hisham Al Saghier ◽  
Abdulrahman Alrabiah
Keyword(s):  
Financial Crisis ◽  
Credit Risk ◽  
Business Process ◽  
Global Economy ◽  
Banking Sector ◽  
Reporting System ◽  
Current System ◽  
Basel Ii ◽  
Business Rules ◽  
Irb Approach

The idea for this paper came after the recent financial crisis, its global consequences and specifically how it affected the banking sector. Financial institutions and regulators are – from a technical point of view - not fully integrated and automated yet. The inaccuracy in banks’ data and the long set interval period, quarterly, to send the information to the regulators leads to delays interventions by local supervisory regulators. Most of the banks are using an Internal Ratings Based (IRB) approach that allows them to use their own methods to calculate the credit risks, which makes it difficult for the regulators to verify and validate the banks’ data without adopting fully automated connectivity for the regulatory reporting system through sophisticated tools. The importance of this issue, for the central banks as well as the global economy, encourages us to investigate and to find solutions for the problem at hand. This paper is focused on the Advanced Internal Ratings Based (A-IRB) approach to evaluate credit risk due to the importance and the sensitivity of this approach on the banking sector. The flexibility of the A-IRB approach allow banks to use their own method to calculate the credit risk without regulators having the right tools to validate the data is a major issue . The second issue with the A-IRB approach is that the report is only delivered quarterly to the regulator (SAMA). This period is too long as decisions can be taken based on data that is almost a quarter old. Therefore, evaluating the existing framework and solving the issues concurrently is essential to improve the regulatory reporting system. To examine the situation of the regulatory reporting system, first, we reviewed literature on the Basel II&III regulations and the financial crisis, including impacts and responses. The second, we reviewed   factors impeding the implementation of Basel II&III, including solutions to increase coordination and integration and a holistic approach that can mitigate the outstanding issues for the Regulatory Reporting System for the local banks in Saudi Arabia. We also evaluated the current system and the proposed system in two workshops and found that the proposed system showed considerable improvements of more than 100% in some areas and hence should be implemented. Our result is a framework solution that integrates a private cloud computing network with automated and integrated features such as a Business Process Manager, a Knowledge Management Engine, a SLA Lifecycle Manager, a Business Rules Engine and a Data Quality Regulator and the Enterprise Service Bus for communication and integration between the banks and SAMA. Keywords: Business Process, Business Rules, Bank Management

NEURAL NETWORKS AND THEIR APPLICATION IN CREDIT RISK ASSESSMENT. EVIDENCE FROM THE ROMANIAN MARKET / NEURONINIAI TINKLAI IR JŲ TAIKYMAS KREDITO RIZIKAI VERTINTI RUMUNIJOS RINKOS PAVYZDŽIU

2011 ◽  
Vol 17 (3) ◽  
pp. 519-534 ◽  
Author(s):  
Smaranda Stoenescu Cimpoeru
Keyword(s):  
Neural Networks ◽  
Risk Assessment ◽  
Logistic Regression ◽  
Credit Risk ◽  
Support Vector ◽  
Back Propagation Algorithm ◽  
Credit Risk Assessment ◽  
The Neural Networks ◽  
Assessment Problems ◽  
Fuzzy Adaptive

The purpose of this article is to see how neural networks are used in credit risk assessment problems. For this, we firstly introduce the main theoretical concepts of the neural calculus, as well as the fundaments for the main training algorithm: the error back-propagation algorithm. We review the specialty literature and find that the neural networks yield better results than other classification techniques, like multivariate discriminant analysis or logistic regression, when applying them in credit risk assessment problems. We focus on a few types of networks: feed-forward networks with multiple layers, fuzzy adaptive networks, support vector machines. We develop an analysis on Romanian Small and Medium Enterprises (financial ratios) and the results are in line with the findings from the literature: the neural networks give better results than the logistic regression. The study can be developed by analyzing a support vector machine or a fuzzy adaptive network. Santrauka Šio straipsnio tikslas – parodyti, kaip neuroniniai tinklai yra naudojami kredito rizikos vertinimo problemoms spręsti. Iš pradžių pristatoma pagrindinė teorinė koncepcija, paskui – pagrindinis algoritmas. Literatūros analizė atskleidė, kad sprendžiant kredito rizikos vertinimo problemas neuroniniai tinklai duoda objektyvesnius rezultatus už kitus klasifikacijos metodus, t. y. daugiamatę diskriminantinę analizę arba logistinę regresiją. Dėmesys sutelkiamas į kelių tipų neuroninius tinklus: daugiasluoksnius, prisitaikančius ir vektorinius. Atlikta Rumunijos mažų ir vidutinių įmonių finansinių rodiklių analizė ir gauti rezultatai patvirtino prielaidą, kad neuroniniai tinklai duoda objektyvesnį rezultatą už logistinę regresiją.

International Financial Centres after the Global Financial Crisis and Brexit

2018 ◽  
Keyword(s):  
New York ◽  
Financial Crisis ◽  
Global Economy ◽  
Global Financial Crisis ◽  
New Technology ◽  
Interdisciplinary Approach ◽  
Important Change ◽  
Social Scientists ◽  
The Global Financial Crisis ◽  
Financial Technology

This book gathers leading economic historians, geographers, and social scientists to focus on the developments in key international financial centres following the 2008 Global Financial Crisis and to consider the likely effects of Brexit on these centres. Eleven centres in eight countries are taken into consideration: New York, London, Frankfurt, Paris, Zurich/Geneva, Hong Kong/Shanghai/Beijing, Tokyo, and Singapore. The book addresses three main issues. The first is the hierarchy of international financial centres, in particular whether Asian financial centres have taken advantage of the crisis in the West. The second is the medium-term effects of the crisis, with respect to the volume of business activity (including employment), and the level of regulation, with concerns regarding the risks of regulatory overkill. And the third is the rise of new technology, known as fintech, possibly the most important change in the decade following the crisis, with questions as to whether it will render financial centres, as we know them, unnecessary for the functioning of the global economy, and which cities are likely to emerge as hubs of new financial technology. Finally, the book discusses the likely effects of Brexit on international financial centres, in particular London, Paris, and Frankfurt. The book takes a decidedly interdisciplinary approach, with a general introduction providing a global overview from a historical perspective, and a general conclusion providing a global overview from a geographical perspective. Its focus on the implications for global financial centres is unique among books about the aftermath of the Global Financial Crisis.

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