Early Warning System for SMEs as a Financial Risk Detector

2009 ◽  
pp. 220-238 ◽  
Author(s):  
Ali Serhan Koyuncugil
Keyword(s):  
Data Mining ◽  
Risk Management ◽  
Early Warning ◽  
Financial Management ◽  
Early Warning System ◽  
Quantitative Data ◽  
Financial Risk ◽  
Warning System ◽  
Theoretical Background ◽  
Effect Level

This chapter introduces an early warning system for SMEs (SEWS) as a financial risk detector which is based on data mining. In this study, the objective is to compose a system in which qualitative and quantitative data about the requirements of enterprises are taken into consideration, during the development of an early warning system. Furthermore, during the formation of system; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the data and the identification of effect level of every factor. Using the system, SME managers could easily reach financial management, risk management knowledge without any prior knowledge and expertise. In other words, experts share their knowledge with the help of data mining based and automated EWS.

Design and Realization on the Financial Early-Warning Analysis System of Colleges and Universities Based on Data Mining Technology

2014 ◽  
Vol 623 ◽  
pp. 229-233 ◽  
Author(s):  
De Jiang Qi ◽  
Hai Yan Hu
Keyword(s):  
Data Mining ◽  
Early Warning ◽  
Financial Management ◽  
Financial Risk ◽  
Warning System ◽  
Colleges And Universities ◽  
Mining Technology ◽  
Id3 Algorithm ◽  
Financial Management System ◽  
Analysis System

In this thesis, in order to solve the student arrearage problems in colleges and universities, risk weight factor is introduced to improve ID3 algorithm through the research on data mining technology and the combination with financial management system of colleges and universities so that ID3 decision-making tree algorithm can classify based on the risk weights of all the factors of the financial data; the early warning system scheme on the student arrearage problems in colleges and universities is designed so as to predict the high-risk defaulting students dynamically and accurately and lay scientific foundations for avoiding financial risk in colleges and universities.

scholarly journals Establishment of a Financial Crisis Early Warning System for Domestic Listed Companies Based on Three Decision Tree Models

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Gang Wang ◽  
Keming Wang ◽  
Yingying Zhou ◽  
Xiaoyan Mo ◽  
Weilin Xiao
Keyword(s):  
Financial Crisis ◽  
Decision Tree ◽  
Early Warning ◽  
Financial Management ◽  
Early Warning System ◽  
Comprehensive Evaluation ◽  
Warning System ◽  
Predictive Ability ◽  
Tree Models ◽  
The Impact

The financial crisis is a realistic problem that the general enterprise must encounter in the process of financial management. Due to the impact of the COVID-19 and the Sino-US trade war, domestic companies with unsound financial conditions are at risk of shutdowns and bankruptcies. Therefore, it is urgently needed to study the financial warning of enterprises. In this study, three decision tree models are used to establish the financial crisis early warning system. These three decision tree models include C50, CART, and random forest decision trees. In addition, the ROC curve was used for comprehensive evaluation of the accuracy analysis of the model to confirm the predictive ability of each model. This result can provide reference for domestic financial departments and provide financial management basis for the investing public.

scholarly journals Early warning system on extreme weather events for disaster risk reduction

2019 ◽  
pp. 80-87
Author(s):  
Jacipt Alexander Ramón-Valencia ◽  
Jordi Rafael Palacios-González ◽  
Germán Rircardo Santos-Granados ◽  
Jarol Derley Ramón-Valencia
Keyword(s):  
Risk Management ◽  
Risk Reduction ◽  
Early Warning ◽  
Early Warning System ◽  
Disaster Risk Reduction ◽  
Warning System ◽  
Disaster Risk ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Events

The objective of this research was to propose a strategy based on the design and implementation of an early warning system (EWS) for extreme weather events. This project had the following phases: training for municipal and regional actors, preliminary technical diagnosis of the study areas, monitoring network, and the weather forecasts using numerical models WRF and GFS. This EWS is the result of the Macro-project EWS for Climate Events in the basins of the Pamplonita River and Zulia in the North of Santander (SATC), executed by the University of Pamplona and financed by the National Risk Management Unit (UNGRD) and the German Cooperation Agency (GIZ). The research concluded that the application of a disaster risk reduction strategy through an EWS for extreme weather events is an important tool and instrument for the planning of higher risk management because it helps anticipate disasters and consequently preserve lives.

Research on the Early Warning Mechanism of Financial Risk by Computer Technology

2014 ◽  
Vol 687-691 ◽  
pp. 4922-4925
Author(s):  
Liang Liu ◽  
Chun Ling Li
Keyword(s):  
Financial Markets ◽  
Empirical Analysis ◽  
Early Warning ◽  
Early Warning System ◽  
Financial Risk ◽  
Warning System ◽  
Warning Signal ◽  
Financial Risks ◽  
Early Warning Mechanism ◽  
Starting Point

The briefly review and the development of the financial risk early warning theory is first discussed in this study and the domestic and foreign research is analyzed as a brief summary. Secondly, the concept of financial risks, financial crisis and the financial early warning is defined. Financial fragility as a starting point is used to establish the rationality model of the financial risk early warning system. The early warning indicators is selected on the basis of the 12 indicators of macro-financial risks, 15 net financial indicators is selected to represent the financial markets according to the characteristics of China's financial markets. In the empirical part, the previous empirical analysis method is chosen to build the financial risk early warning signal system. In order to display China's financial risk profile, the proper model for the calculation is made on the basis of empirical analysis. Thus, in order to minimize the local financial risk, the early warning system should be established by the local government, together with some other necessary measures.

A Fish Swarm Algorithm for Financial Risk Early Warning

2018 ◽  
Vol 14 (4) ◽  
pp. 54-63
Author(s):  
Liu Yunshan
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Financial Risk ◽  
Simulation Analysis ◽  
Warning System ◽  
The Sustainable Development ◽  
Artificial Fish Swarm Algorithm ◽  
Artificial Fish Swarm ◽  
The Index System ◽  
Swarm Algorithm

The financial risk early warning system is important for promoting the sustainable development of enterprise, and in this article, the fish swarm algorithm is applied to it. First, the main financial risk factors of enterprise are summarized. Second, the index system of the financial risk early warning system is constructed based on relating theory. Third, the basic theory of artificial fish swarm algorithm is studied, and the mathematical models are constructed. Then, the wavelet neutral network is improved based on the fish swarm algorithm, and the algorithm procedure is designed. Finally, a simulation analysis is carried out, and the predicting correctness of samples is 100%, and results show that the fish swarm algorithm is an effective method for improving the financial risk early warning system.

Data Mining Techniques to Improve Early Warning Systems across the Bay of Bengal

2013 ◽  
pp. 1349-1383
Author(s):  
Hakikur Rahman
Keyword(s):  
Data Mining ◽  
Early Warning ◽  
Bay Of Bengal ◽  
Early Warning System ◽  
Ethical Issues ◽  
Warning System ◽  
Major Portion ◽  
Data Mining Techniques ◽  
Landing Zone ◽  
Bangladeshi Population

This chapter is a conceptual contribution to this book on data mining applications upholding ethical issues related to two extremely important aspects of the Bangladeshi population: the early warning system and the disaster management system. The chapter tries to provide a few conceptual ideas to introduce ethical data mining application in these systems to support the agencies that are involved for an improved, efficient, and transparent support system in the country, especially across the Bay of Bengal. Resembling a triangular shape (deltaic), a major portion of the bay touches the southern portion of Bangladesh. Sediments from rivers have made the bay a shallow sea. Due to its shallowness and shape, monsoon rains and cyclone storms become destructive, causing great loss of life along the southern part of the country. Moreover, the three mighty rivers (Padma, Jamuna, and Meghna) form one of the largest river systems in the world. They have a large number of distributaries and tributaries, which cause a major portion of the country to be inundated by monsoon rain. In addition, being the lowest landing zone of the Himalayan water, Bangladesh becomes victim to floods almost every year. Loss of lives, destruction of properties, suffering of numerous people and hampering of economic development have become part and parcel of Bangladeshi communities. This chapter suggests that the newly emerged data mining techniques can be introduced to collect, synthesize, analyze, archive, disseminate, and even make future forecasts forming a reliable early warning system across the Bay of Bengal.

scholarly journals INCLUSIVE DISASTER RISK MANAGEMENT (DRM) FOR BERTAM VALLEY COMMUNITY

2018 ◽  
Vol 16 (6) ◽  
Author(s):  
Rahsidi Sabri Muda ◽  
Izawati Tukiman ◽  
Mohd Ramzi Mohd Hussain ◽  
Ismawi Zen
Keyword(s):  
Risk Management ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Disaster Risk ◽  
Disaster Risk Management ◽  
Dam Failure ◽  
Emergency Responder ◽  
Reduction Program ◽  
Community Preferences

This paper focuses on the inclusiveness of Disaster Risk Management. The study assesses proactive adaptation of Early Warning System (EWS) for Disaster Risk Reduction Program in Bertam Valley. The study aims to identify community preferences as an initiative to improve the effectiveness of the EWS system. In order to sustain the awareness and preparedness of EWS, continuous involvement by the community is necessary to make them resilient. Specific focus is given to Person with Disabilities (PwDs), elderly and children. Therefore, it is vital to understand the efficient methods to alarm PwDs, elderly and children during emergencies occurrence, which will focus on the implementation of types of alarm in EWS with regards to the early warning alarm and emergency notification. The finding from this paper is useful to assist local authorities and emergency responder in the formulation of warning and evacuation procedures to save the PwDs if dam failure is imminent.

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