Finance and Financial Management Commons^™

Contingency Planning Amidst A Pandemic, Natalie C. Belford

KSU Proceedings on Cybersecurity Education, Research and Practice

Proper prior planning prevents pitifully poor performance: The purpose of this research is to address mitigation approaches - disaster recovery, contingency planning, and continuity planning - and their benefits as they relate to university operations during a worldwide pandemic predicated by the Novel Coronavirus (COVID-19). The most relevant approach pertaining to the University’s needs and its response to the Coronavirus pandemic will be determined and evaluated in detail.

Data-Driven Investment Decisions In P2p Lending: Strategies Of Integrating Credit Scoring And Profit Scoring, Yan Wang

Doctor of Data Science and Analytics Dissertations

In this dissertation, we develop and discuss several loan evaluation methods to guide the investment decisions for peer-to-peer (P2P) lending. In evaluating loans, credit scoring and profit scoring are the two widely utilized approaches. Credit scoring aims at minimizing the risk while profit scoring aims at maximizing the profit. This dissertation addresses the strengths and weaknesses of each scoring method by integrating them in various ways in order to provide the optimal investment suggestions for different investors. Before developing the methods for loan evaluation at the individual level, we applied the state-of-the-art method called the Long Short Term Memory (LSTM) …

A Credit Analysis Of The Unbanked And Underbanked: An Argument For Alternative Data, Edwin Baidoo

Doctor of Data Science and Analytics Dissertations

The purpose of this study is to ascertain the statistical and economic significance of non-traditional credit data for individuals who do not have sufficient economic data, collectively known as the unbanked and underbanked. The consequences of not having sufficient economic information often determines whether unbanked and underbanked individuals will receive higher price of credit or be denied entirely. In terms of regulation, there is a strong interest in credit models that will inform policies on how to gradually move sections of the unbanked and underbanked population into the general financial network.

In Chapter 2 of the dissertation, I establish the …

A Comparison Of Machine Learning Algorithms For Prediction Of Past Due Service In Commercial Credit, Liyuan Liu M.A, M.S., Jennifer Lewis Priestley Ph.D.

Published and Grey Literature from PhD Candidates

Credit risk modeling has carried a variety of research interest in previous literature, and recent studies have shown that machine learning methods achieved better performance than conventional statistical ones. This study applies decision tree which is a robust advanced credit risk model to predict the commercial non-financial past-due problem with better critical power and accuracy. In addition, we examine the performance with logistic regression analysis, decision trees, and neural networks. The experimenting results confirm that decision trees improve upon other methods. Also, we find some interesting factors that impact the commercials’ non-financial past-due payment.

Deployment Evaluation Of Accounting Information Systems In Libyan Commercial Banks, Omar Sharkasi, Martin George Wynn

The African Journal of Information Systems

This article reports on the recent implementation and current deployment of accounting information systems in Libyan commercial banks. A case study approach is adopted that moves from an initial screening of the 14 main Libyan banks to a final in-depth study of just three banks. Business process modeling and systems profiling are used to assess the status of the banks in terms of systems use, process change and information systems strategy development. Libyan banks are well advanced in their installation of modern packaged software but could be used to greater effect to optimize business processes and improve efficiencies. Training and …