Loan Default Analysis In Europe: Tracking Regional Variations Using Big Data — Phdassistance.com

The present article helps the USA, the UK, Europe and the Australian students pursuing their Economics & Finance degree to identify the right topic in the area of Finance. These topics are researched in-depth at the University of Spain, Cornell University, University of Modena and Reggio Emilia, Modena, Italy, and many more. PhD Assistance offers UK Dissertation Research Topics Services in Economics & Finance Domain. When you Order Economics & Finance Dissertation Services at PhD Assistance, we promise you the following — Plagiarism free, Always on Time, outstanding customer support, written to Standard, Unlimited Revisions support and High-quality Subject Matter Experts.

You will find the best dissertation research areas / topics for future researchers enrolled in Economics & Finance.

In order to identify the future research topics, we have reviewed the Finance (recent peer-reviewed studies) on Data Analysis.

Multiple factors that affect the bank stability and ensure that proper documentation is maintained

Background:

Banks were never anticipated to fail especially the large banks like AIG (McDonald & Paulson, 2020). Its collapse led to a complete failure of the insurance company and one of the main factors of the 2008 financial crises.

The main problem was that they had given the lenders too many loans and incentives, even though they did not have enough money in the reserves to repay them.

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Hire PhD Assistance experts to develop your loan default analysis for your Finance.

Tests:

The various tests and accounting models that are available are the Stress Tests, Credit Loss, etc (Basel Committee Banking Supervision, 2017). Bank stress tests use simulation by examining the balance of the firms and analyse the financial stress that is available.

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European Perspective:

A large portion of the existing literature has focused on the United States, while there are very few studies that consider Europe. Also, the behaviour of the borrower will not be the same between the two regions.

Big Data:

The availability of large amounts of data in some countries leads to a question about how the data is handled, as this adds new complications to the study.

It is therefore possible to implement machine learning algorithms and big data so that the model can be evaluated without complicated mathematical models.

The different type of analysis has been seen and discussed for European banks. Analysing the CECL of the banks using machine learning techniques through big data will greatly avoid loan defaults. This will avoid the failure of banks thereby avoiding economic collapse.

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