Data analytic approach for bankruptcy prediction

Son, Hwijae; Hyun, Chongseok; Phan, Du; Hwang, Hyung Ju

doi:10.1016/j.eswa.2019.07.033

Cited by 103 publications

(66 citation statements)

References 22 publications

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“…For the duration of the moratorium, the deadline for filing bankruptcy petitions will be suspended (for the omission of which, for example, the head of the organization is liable for subsidiary purposes). So, the course of the term for the debtor (this applies to both individuals and legal entities), who is obliged to submit an application within 1 month after he discovers objective signs of insolvency, is suspended [14].…”

Section: Methodsmentioning

confidence: 99%

Legal aspects of the moratorium on bankruptcy as an innovative trend in business support in a pandemic

Sapozhnikova

2020

E3S Web Conf.

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At the beginning of 2020, a difficult epidemiological situation developed in Russia against the background of the development of the Covid-19 pandemic. This situation had an extremely negative impact on the country's economy. The government has developed anti-crisis measures aimed at supporting economic entities in the most affected sectors of the economy. One of the measures to overcome the crisis was the transformation of legislation in the field of bankruptcy.

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Section: Methodsmentioning

confidence: 99%

Legal aspects of the moratorium on bankruptcy as an innovative trend in business support in a pandemic

Sapozhnikova

2020

E3S Web Conf.

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“…is is the measurement of corporate solvency and the creation of prediction models [72] to forecast the company failure or distress. It has been intensively discussed over the past decades [73], using traditional statistical techniques [74][75][76] or machine learning methods, such as gradient boosting [72], neural networks [77], support vector machine [78], or the comparison of different methods [79,80].…”

Section: Complexitymentioning

confidence: 99%

Bidders Recommender for Public Procurement Auctions Using Machine Learning: Data Analysis, Algorithm, and Case Study with Tenders from Spain

et al. 2020

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Recommending the identity of bidders in public procurement auctions (tenders) has a significant impact in many areas of public procurement, but it has not yet been studied in depth. A bidders recommender would be a very beneficial tool because a supplier (company) can search appropriate tenders and, vice versa, a public procurement agency can discover automatically unknown companies which are suitable for its tender. This paper develops a pioneering algorithm to recommend potential bidders using a machine learning method, particularly a random forest classifier. The bidders recommender is described theoretically, so it can be implemented or adapted to any particular situation. It has been successfully validated with a case study: an actual Spanish tender dataset (free public information) which has 102,087 tenders from 2014 to 2020 and a company dataset (nonfree public information) which has 1,353,213 Spanish companies. Quantitative, graphical, and statistical descriptions of both datasets are presented. The results of the case study were satisfactory: the winning bidding company is within the recommended companies group, from 24% to 38% of the tenders, according to different test conditions and scenarios.

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“…It is important to understand that the absence of a rapid increase in the number of bankrupt companies is also due to the fact that the courts worked in a restricted mode, and some of the procedures were postponed due to the moratorium on the initiation of procedures by creditors, which has already been applied to more than 2 million individual entrepreneurs and companies. Accordingly, it is possible that, based on the results of the second half of the year, we will see continued growth in bankruptcy indicators in the Russian Federation [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Analysis of foreign and domestic models for assessing the level of insolvency (bankruptcy) for organizations in the Russian Federation

Sivolapenko

Tyutyunik

2020

E3S Web Conf.

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In modern economic conditions, the main goal of managing an organization is to provide an effective management model, the main characteristic of which is the construction of a strategy for the development of an organization that will ensure the achievement of the indicators specified in it, the production efficiency of the resources used, financial stability, competitiveness and effective management of the organization's personnel. One of the main elements of building this system is the timely identification of existing risks that directly affect the assessment of the likelihood of insolvency (bankruptcy) of the organization. This article presents the calculations of nine operating models for assessing the level of bankruptcy of an organization, made on the basis of financial statements of a large Russian company engaged in the sale of goods.

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Data analytic approach for bankruptcy prediction

Cited by 103 publications

References 22 publications

Legal aspects of the moratorium on bankruptcy as an innovative trend in business support in a pandemic

Legal aspects of the moratorium on bankruptcy as an innovative trend in business support in a pandemic

Bidders Recommender for Public Procurement Auctions Using Machine Learning: Data Analysis, Algorithm, and Case Study with Tenders from Spain

Analysis of foreign and domestic models for assessing the level of insolvency (bankruptcy) for organizations in the Russian Federation

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