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IMPROVE YOUR CREDITWORTHINESS IN 2020 - Journal

2019-11-15
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Release : 2019-11-15
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Kind : eBook
Book Rating : 301/5 ( reviews)

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Book Synopsis IMPROVE YOUR CREDITWORTHINESS IN 2020 - Journal by : Cj THOMAS

Download or read book IMPROVE YOUR CREDITWORTHINESS IN 2020 - Journal written by Cj THOMAS. This book was released on 2019-11-15. Available in PDF, EPUB and Kindle. Book excerpt: This journal shows you how to read your credit report, how to keep track of your bills, and how to manage your credit profile to increase your credit score in as little as ninety days. Your credit report is usually the first thing that is used by financial risk managers to decide as to whether you are creditworthy. Lenders want to know some key information as to how well you have paid your debts over time. The length of payment history is a good indication as to the probability that an individual will repay his/her bills as agreed. For more information about credit, you can get the book - (Credit Power ... Stay In The Black.) Available on Amazon.

FinTech in Financial Inclusion: Machine Learning Applications in Assessing Credit Risk

2019-05-17 Business & Economics
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Release : 2019-05-17
Genre : Business & Economics
Kind : eBook
Book Rating : 422/5 ( reviews)

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Book Synopsis FinTech in Financial Inclusion: Machine Learning Applications in Assessing Credit Risk by : Majid Bazarbash

Download or read book FinTech in Financial Inclusion: Machine Learning Applications in Assessing Credit Risk written by Majid Bazarbash. This book was released on 2019-05-17. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in digital technology and big data have allowed FinTech (financial technology) lending to emerge as a potentially promising solution to reduce the cost of credit and increase financial inclusion. However, machine learning (ML) methods that lie at the heart of FinTech credit have remained largely a black box for the nontechnical audience. This paper contributes to the literature by discussing potential strengths and weaknesses of ML-based credit assessment through (1) presenting core ideas and the most common techniques in ML for the nontechnical audience; and (2) discussing the fundamental challenges in credit risk analysis. FinTech credit has the potential to enhance financial inclusion and outperform traditional credit scoring by (1) leveraging nontraditional data sources to improve the assessment of the borrower’s track record; (2) appraising collateral value; (3) forecasting income prospects; and (4) predicting changes in general conditions. However, because of the central role of data in ML-based analysis, data relevance should be ensured, especially in situations when a deep structural change occurs, when borrowers could counterfeit certain indicators, and when agency problems arising from information asymmetry could not be resolved. To avoid digital financial exclusion and redlining, variables that trigger discrimination should not be used to assess credit rating.

Financial Literacy and Responsible Finance in the FinTech Era

2021-07-21 Business & Economics
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Release : 2021-07-21
Genre : Business & Economics
Kind : eBook
Book Rating : 528/5 ( reviews)

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Book Synopsis Financial Literacy and Responsible Finance in the FinTech Era by : John O.S. Wilson

Download or read book Financial Literacy and Responsible Finance in the FinTech Era written by John O.S. Wilson. This book was released on 2021-07-21. Available in PDF, EPUB and Kindle. Book excerpt: A growing body of evidence suggests that financial literacy plays an important role in financial well-being, and that differences in financial knowledge acquired early in life can explain a significant part of financial and more general well-being in adult life. Financial technology (FinTech) is revolutionizing the financial services industry at an unrivalled pace. Views differ regarding the impact that FinTech is likely to have on personal financial planning, well-being and societal welfare. In an era of mounting student debt, increased (digital) financial inclusion and threats arising from instances of (online) financial fraud, financial education and enlightened financial advising are appropriate policy interventions that enhance financial and overall well-being. Financial Literacy and Responsible Finance in the FinTech Era: Capabilities and Challenges engages in this important academic and policy agenda by presenting a set of seven chapters emanating from four parallel streams of literature related to financial literacy and responsible finance. The chapters in this book were originally published as a special issue of The European Journal of Finance.

Doing Business 2020

2019-11-21 Business & Economics
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Release : 2019-11-21
Genre : Business & Economics
Kind : eBook
Book Rating : 414/5 ( reviews)

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Book Synopsis Doing Business 2020 by : World Bank

Download or read book Doing Business 2020 written by World Bank. This book was released on 2019-11-21. Available in PDF, EPUB and Kindle. Book excerpt: Seventeen in a series of annual reports comparing business regulation in 190 economies, Doing Business 2020 measures aspects of regulation affecting 10 areas of everyday business activity.

Data Science for Economics and Finance

2021 Application software
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Release : 2021
Genre : Application software
Kind : eBook
Book Rating : 916/5 ( reviews)

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Book Synopsis Data Science for Economics and Finance by : Sergio Consoli

Download or read book Data Science for Economics and Finance written by Sergio Consoli. This book was released on 2021. Available in PDF, EPUB and Kindle. Book excerpt: This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

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