A fuzzy expert system for small business loan processing

In recent years, managerial applications of artificial intelligence, especially in the area of financial services, has received considerable attention. In this paper, a fiizzy logic expert system is developed for approvals of small business loans. Previous studies have used non-fuzzv expert systems. But the fuzzification of the variables used in a business loan approval decisionmaking promises more efficient results. Furthermore, another distinct feature of this paper is its focus on small business loans. CubiCalc fuzzy expert system shell is used to develop the expert system. Knowledge acquisition is made using the resources and expertise of a Small Business Development Center. Tests to establish generalizability and validity of the results are conducted

Data Mining: How Popular Is It?

Data Mining is a process used in the industry, to facilitate decision making. As the name implies, large volumes of data is mined or sifted, to find useful information for decision making. With the advent of E-business, Data Mining has become more important to practitioners. The purpose of this paper is to find out the importance of Data Mining by looking at the different application areas that have used data mining for decision making

FRAUD PREVENTION AND DETECTION SYSTEM IN NIGERIA BANKING INDUSTRIES

Fraud is on the rise as a result of the advent of modern technology and the global superhighways of banking transactions, resulting in billions of dollars in losses worldwide each year. Although fraud prevention technologies are the most effective method of combating fraud, fraudsters are flexible and will usually find a way around them over time. We need fraud detection approaches if we are to catch fraudsters after fraud prevention has failed. Statistics and machine learning are effective fraud detection technologies that have been used to detect money laundering, e-commerce credit card fraud, telecommunications fraud, and computer intrusion, to name a few. The program is simple to use, and anyone with permission can use it. The importance of computer technology has expanded as it has advanced in all areas of human endeavor.                        Keywords: Fraud Detection, Fraud Prevention, Banking Industries, Telecommunications

Security Analysis and Improvement Model for Web-based Applications

Today the web has become a major conduit for information. As the World Wide Web?s popularity continues to increase, information security on the web has become an increasing concern. Web information security is related to availability, confidentiality, and data integrity. According to the reports from http://www.securityfocus.com in May 2006, operating systems account for 9% vulnerability, web-based software systems account for 61% vulnerability, and other applications account for 30% vulnerability. In this dissertation, I present a security analysis model using the Markov Process Model. Risk analysis is conducted using fuzzy logic method and information entropy theory. In a web-based application system, security risk is most related to the current states in software systems and hardware systems, and independent of web application system states in the past. Therefore, the web-based applications can be approximately modeled by the Markov Process Model. The web-based applications can be conceptually expressed in the discrete states of (web_client_good; web_server_good, web_server_vulnerable, web_server_attacked, web_server_security_failed; database_server_good, database_server_vulnerable, database_server_attacked, database_server_security_failed) as state space in the Markov Chain. The vulnerable behavior and system response in the web-based applications are analyzed in this dissertation. The analyses focus on functional availability-related aspects: the probability of reaching a particular security failed state and the mean time to the security failure of a system. Vulnerability risk index is classified in three levels as an indicator of the level of security (low level, high level, and failed level). An illustrative application example is provided. As the second objective of this dissertation, I propose a security improvement model for the web-based applications using the GeoIP services in the formal methods. In the security improvement model, web access is authenticated in role-based access control using user logins, remote IP addresses, and physical locations as subject credentials to combine with the requested objects and privilege modes. Access control algorithms are developed for subjects, objects, and access privileges. A secure implementation architecture is presented. In summary, the dissertation has developed security analysis and improvement model for the web-based application. Future work will address Markov Process Model validation when security data collection becomes easy. Security improvement model will be evaluated in performance aspect

Business Analytics Using Predictive Algorithms

In today's data-driven business landscape, organizations strive to extract actionable insights and make informed decisions using their vast data. Business analytics, combining data analysis, statistical modeling, and predictive algorithms, is crucial for transforming raw data into meaningful information. However, there are gaps in the field, such as limited industry focus, algorithm comparison, and data quality challenges. This work aims to address these gaps by demonstrating how predictive algorithms can be applied across business domains for pattern identification, trend forecasting, and accurate predictions. The report focuses on sales forecasting and topic modeling, comparing the performance of various algorithms including Linear Regression, Random Forest Regression, XGBoost, LSTMs, and ARIMA. It emphasizes the importance of data preprocessing, feature selection, and model evaluation for reliable sales forecasts, while utilizing S-BERT, UMAP, and HDBScan unsupervised algorithms for extracting valuable insights from unstructured textual data

Advanced Information Systems and Technologies

This book comprises the proceedings of the VI International Scientific Conference “Advanced Information Systems and Technologies, AIST-2018”. The proceeding papers cover issues related to system analysis and modeling, project management, information system engineering, intelligent data processing, computer networking and telecomunications, modern methods and information technologies of sustainable development. They will be useful for students, graduate students, researchers who interested in computer science

Supply chain operation strategies and risk management with working capital consideration: a case study of the supply chain of lightning protection products in China

JEL: G32; D21With the advent of economic globalization, competition is increasingly hinged on supply chain. Meanwhile, working capital becomes a key element of a successful supply chain. This thesis researches the supply chain of a typical lightning protection products manufacturer in China, i.e. Company Z. The thesis starts with the working capital issues in the supply chain of Company Z; then, with the help of questionnaires and a sensible indicator system and weight assignments; analyzes and summarizes the status quo of the working capital and related key issues in the supply chain consisting of Company Z and its suppliers and customers. Building on such analysis, a two-dimensional classification matrix is created to divide suppliers and customers into four groups (namely, strategic-type, partner-type, general-type, and bottleneck-type) and supply chain operation strategies are devised for each group. Furthermore, based on such supply chain operations strategies of Company Z, a working capital risk management mechanism with an early warning system is developed, and a supply chain-based financing platform is designed to help the supply chain participants seek financing and share the risks with working capital.Com o advento da era da globalização económica, a cadeia de suprimentos tornou-se cada vez mais importante para a concorrência empresarial, e ao mesmo tempo, o fundo de maneio tornou-se num elemento chave para o sucesso da gestão da cadeia de suprimentos. Neste trabalho, a cadeia de suprimentos de uma empresa chinesa de fabricação de produtos típicos de proteção contra relâmpagos, a empresa Z, é o objeto de estudo. Tomando como ponto de partida os problemas de fundo de maneio existentes na cadeia de suprimentos da empresa Z, por meio de questionários combinados com o estabelecimento de um sistema de indexação e de ponderação, foram realizadas análises precisas sobre problemas-chaves existentes e da situação atual da gestão do fundo de maneio da cadeia de suprimentos a montante e a jusante da empresa Z. Estabeleceram-se matrizes bidimensionais de classificação para respectivamente subdividir os fornecedores e clientes em quatro categorias, a saber, categoria de fornecedores/clientes estratégicos, categoria de fornecedores/clientes parceiros, categoria de fornecedores/clientes comuns e categoria de fornecedores/clientes críticos (“engarrafamentos”) e propor estratégias diferentes na cadeia de suprimentos para diferentes categorias. Por fim, o nosso estudo indica que segundo a estratégia de operação da cadeia de suprimentos da empresa Z, deve ser estabelecido um mecanismo de controle e gestão de risco de fundo de maneio, um sistema de alerta de risco e, ainda, projetar uma plataforma de financiamento a fim de prover o financiamento emergente da cadeia de suprimentos da empresa Z e a partilha dos riscos de gestão do fundo de maneio