Name
Abstract | ||
|---|---|---|
Business bankruptcy is a negative phenomenon, whose symptoms can be identified in advance by means of financial data analyses. The aim of this paper is to present two experimental studies using two different approaches to analyze company's financial situation based on selected financial indicators. The first approach used data from financial database called Amadeus to generate a binary prediction model to evaluate a possible future financial health status of the EU companies using suitable machine learning algorithms. The second one included a design and creation of data warehouse based on data from two financial databases Albertina and Creditinfo (SK and CZ companies) to evaluate financial health status of the companies from Slovakia and Czech Republic through index of bankruptcy IN99. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-38366-3_13 | Lecture Notes in Business Information Processing |
Keywords | Field | DocType |
bankruptcy,decision trees,k-nearest neighbor,data warehouse | Data warehouse,Decision tree,Czech,Actuarial science,Computer science,Knowledge management,Bankruptcy prediction,Bankruptcy,Knowledge extraction | Conference |
Volume | ISSN | Citations |
157 | 1865-1348 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frantisek Babic | 1 | 16 | 8.02 |
| Cecília Havrilová | 2 | 2 | 0.77 |
| Jan Paralic | 3 | 56 | 13.96 |