• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • A
  • A
  • A
  • A
  • A
Обычная версия сайта
  • RU
  • EN
  • HSE University
  • Publications
  • Articles
  • Designing an AI-Based Financial Advisor for Distressed Firms: A Decision Support Framework for Actionable and Accounting-Consistent Algorithmic Recourse
  • RU
  • EN
Расширенный поиск
Высшая школа экономики
Национальный исследовательский университет
Priority areas
  • business informatics
  • economics
  • engineering science
  • humanitarian
  • IT and mathematics
  • law
  • management
  • mathematics
  • sociology
  • state and public administration
by year
  • 2027
  • 2026
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2012
  • 2011
  • 2010
  • 2009
  • 2008
  • 2007
  • 2006
  • 2005
  • 2004
  • 2003
  • 2002
  • 2001
  • 2000
  • 1999
  • 1998
  • 1997
  • 1996
  • 1995
  • 1994
  • 1993
  • 1992
  • 1991
  • 1990
  • 1989
  • 1988
  • 1987
  • 1986
  • 1985
  • 1984
  • 1983
  • 1982
  • 1981
  • 1980
  • 1979
  • 1978
  • 1977
  • 1976
  • 1975
  • 1974
  • 1973
  • 1972
  • 1971
  • 1970
  • 1969
  • 1968
  • 1967
  • 1966
  • 1965
  • 1964
  • 1963
  • 1958
  • More
Subject
News
May 20, 2026
HSE University Opens First Representative Office of Satellite Laboratory in Brazil
HSE University-St Petersburg opened a representative office of the Satellite Laboratory on Social Entrepreneurship at the University of Campinas in Brazil. The platform is going to unite research and educational projects in the spheres of sustainable development, communications and social innovations.
May 18, 2026
The 'Second Shift' Is Not Why Women Avoid News
Women are more likely than men to avoid political and economic news, but the reasons for this behaviour are linked less to structural inequality or family-related stress than to personal attitudes and the emotional perception of news content. This conclusion was reached by HSE researchers after analysing data from a large-scale survey of more than 10,000 residents across 61 regions of Russia. The study findings have been published in Woman in Russian Society.
May 15, 2026
Preserving Rationality in a Period of Turbulence
The HSE International Laboratory for Logic, Linguistics and Formal Philosophy studies logic and rationality in a transformed world characterised by a diversity of logical systems and rational agents. The laboratory supports and develops academic ties with Russian and international partners. The HSE News Service spoke with the head of the laboratory, Prof. Elena Dragalina-Chernaya, about its work.

 

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!

Publications
  • Books
  • Articles
  • Chapters of books
  • Working papers
  • Report a publication
  • Research at HSE

?

Designing an AI-Based Financial Advisor for Distressed Firms: A Decision Support Framework for Actionable and Accounting-Consistent Algorithmic Recourse

IEEE Access. 2025. Vol. 14. P. 20084–20099.
Lashkevich Y., Zelenkov Y.
Language: English
DOI
Keywords: bankruptcy predictionmulti-objective optimisationcounterfactual explanationsDecision Support Systemsfirm financial failurealgorithmic recourseactionable AI
Similar publications
Designing an AI-Based Financial Advisor for Distressed Firms: A Decision Support Framework for Actionable and Accounting-Consistent Algorithmic Recourse
Elizaveta Lashkevich, Zelenkov Y., IEEE Access 2026 Vol. 14 P. 20084–20099
While machine learning models have achieved high accuracy in predicting firm financial failure (FFF), they often function as “closed boxes” that fail to provide actionable guidance for decision-makers. Existing counterfactual explanation methods typically operate in the space of financial ratios (FR), neglecting fundamental accounting identities and implementation costs, thereby producing recommendations that are theoretically valid ...
Added: February 20, 2026
Artificial Intelligence and Environmental Decision Support Systems
Gribkova D. E., Milshina Y., , in: Artificial Intelligence Enabled Real Time Environmental Monitoring.: Springer, 2026. P. 231–252.
The environment, as a dynamic system influenced by anthropogenic factors, requires evidence-based decision-making to ensure sustainable resource management and mitigate adverse effects. This chapter explores the transformative role of artificial intelligence (AI) in environmental decision support systems (EDSS), focusing on its potential to address complex environmental challenges. EDSS, characterized by their interactivity and ability to ...
Added: January 12, 2026
Повышение точности прогнозирования банкротств с использованием оценок Data Envelopment Analysis
Zelenkov Y., Бизнес-информатика 2025 Т. 19 № 3 С. 7–21
Most current bankruptcy prediction models are based on financial ratios, although their usage is not supported by formal theory and their interpretation is problematic. One of the prospects for improving the predictive models is the study of other firm performance measures, such as the data envelopment analysis (DEA) scores. However, this raises the problem of ...
Added: October 6, 2025
Counterfactual explanations based on synthetic data generation
Yuri A. Zelenkov, Elizaveta V. Lashkevich, Business Informatics 2024 Vol. 18 No. 3 P. 24–40
A counterfactual explanation is the generation for a particular sample of a set of instances that belong to the opposite class but are as close as possible in the feature space to the factual being explained. Existing algorithms that solve this problem are usually based on complicated models that require a large amount of training data and significant ...
Added: October 13, 2024
Bankruptcy factors at different stages of the lifecycle for Russian companies
Zelenkov Y., Fedorova E., Electronic Journal of Applied Statistical Analysis 2022 Vol. 15 No. 1 P. 187–210
Many aspects of bankruptcy have not yet been thoroughly studied, among such issues are the causes that lead to bankruptcy at various stages of the company’s lifecycle. We hypothesize that the most significant factors in- fluencing the probability of company bankruptcy at a particular stage of its lifecycle are those the effectiveness of which is ...
Added: June 7, 2022
Bankruptcy prediction on the base of the unbalanced data using multi-objective selection of classifiers
Zelenkov Y., Volodarskiy N., Expert Systems with Applications 2021 Vol. 185 Article 115559
The goal of the paper is to develop a new algorithm for predicting whether the company will go bankrupt on the base of unbalanced data. To do it, we propose to consider the classification as a multi-objective optimization problem and construct a prediction model as an ensemble while minimizing the parameters FPR (False Positive Rate) ...
Added: July 21, 2021
Recycling Privileged Learning and Distribution Matching for Fairness
Quadrianto N., Sharmanska V., , in: Advances in Neural Information Processing Systems 30 (NIPS 2017).: Montreal: Curran Associates, 2017. P. 678–689.
Конференция Computer Science уровня A* по рейтингу CORE Equipping machine learning models with ethical and legal constraints is a serious issue; without this, the future of machine learning is at risk. This paper takes a step forward in this direction and focuses on ensuring machine learning models deliver fair decisions. In legal scholarships, the notion of ...
Added: November 13, 2017
Моделирование региональной эколого-экономической системы с механизмом государственного регулирования на примере Республики Армения
Akopov A. S., Beklaryan A., Бекларян Л. А. et al., Экономическая наука современной России 2016 Т. 72 № 1 С. 109–119
Actual challenges of the ecological-economic system for the case study of the Republic of Armenia (RA) are considered in the paper. The simulation of the ecological-economic system based on methods of the agent-based modelling and the system-dynamics, which allowed designing the Ecological Map of RA, was created.  The important purpose of the suggested approach is ...
Added: May 19, 2016
Bankruptcy visualization and prediction using neural networks: A study of U.S. commercial banks
Lopez Iturriaga F. J., Sanz I. P., Expert Systems with Applications 2015 Vol. 42 No. 6 P. 2857–2869
We develop a model of neural networks to study the bankruptcy of U.S. banks, taking into account the specific features of the recent financial crisis. We combine multilayer perceptrons and self-organizing maps to provide a tool that displays the probability of distress up to three years before bankruptcy occurs. Based on data from the Federal ...
Added: December 10, 2015
Многокритериальная оптимизация эколого-экономической системы: на примере Республики Армения
Akopov A. S., Beklaryan A., В кн.: Устойчивость и процессы управления: Материалы III международной конференции (Санкт-Петербург, 5-9 октября 2015 г.).: СПб.: Издательский дом Федоровой Г.В., 2015. С. 401–403.
Actual challenges of the ecological-economic system for the case study of the Republic of Armenia (RA) are considered in the paper. The simulation of the ecological-economic system based on methods of the agent-based modelling and the system-dynamics, which allowed designing the Ecological Map of RA, was created.  The important purpose of the suggested approach is ...
Added: October 14, 2015
A Binary Model Versus Discriminant Analysis to Corporate Bankruptcies for Emerging Market
Neretina E., Pirogov N., Makeeva E., SSRN Working Papers 2012
The problem of the firm bankruptcy prediction was investigated by foreign researchers in the 1930s and it still remains relevant. Since publishing of the major Altman’s work (1968), based on multiple discriminant analysis, this methodological area has been considerably changed. Taking into consideration that new data have appeared in the course of time, companies’ average ...
Added: April 3, 2015
Применение нейронных сетей и семантического анализа для прогнозирования банкротства
Makeeva E. Y., Аршавский И. В., Корпоративные финансы 2014 Т. 4 № 32 С. 130–141
This paper is concerned with stock liquidity as a factor in making capital structure decisions by managers of Russian firms. Although a big number of studies on capital structure occurred over the last few decades, stock liquidity has only recently attracted scholars’ attention as a possible driver for the choice of capital structure. Yet the ...
Added: March 25, 2015
Динамика прогнозной силы моделей банкротства для средних и малых российских компаний оптовой и розничной торговли
Demeshev B., Тихонова А. С., Корпоративные финансы 2014 Т. 31 № 3 С. 4–22
The chief aim of this paper is to analyse dynamics of linear and non-linear methods to predict bankruptcy for Russian private small and medium-sized retail and wholesale trade  companies. We use financial and non-financial data prior and subsequent to the economic crisis of 2008—2009. We use the following methods: logistic regression and random forest. This research ...
Added: November 22, 2014
Прогнозирование банкротства российских компаний: межотраслевое сравнение
Demeshev B., Тихонова А. С., Экономический журнал Высшей школы экономики 2014 Т. 18 № 3 С. 359–386
The primary aim of this research is to compare diverse statistical models to predict critical financial state for Russian private small and medium-sized companies belonging to different sectors of economy. We use the following methods: Linear Discriminant Analysis, Quadratic Discriminant Analysis, Mixture Discriminant Analysis, Logistic Regression, Probit Regression, Tree and Random Forest. Our dataset consists of ...
Added: November 22, 2014
Прогнозирование банкротства российских компаний: межотраслевое сравнение.
Тихонова А. С., Demeshev B., / Высшая школа экономики. Серия WP2 "Количественный анализ в экономике". 2014. № 4.
The primary aim of this research is to compare diverse statistical models to predict critical financial statefor Russian private small and medium-sized companies belonging to different sectors of economy. We use the following methods: Linear Discriminant Analysis, Quadratic Discriminant Analysis, Mixture Discriminant Analysis, Logistic Regression, Probit Regression, Tree and Random Forest.Our dataset consists of approximately ...
Added: September 22, 2014
Parallel genetic algorithm with fading selection
Akopov A. S., International Journal of Computer Applications in Technology 2014 Vol. 49 No. 3/4 P. 325–331
This work presents a novel approach to designing the parallel genetic algorithm (GA) with fading selection for the solving of the problem of the shareholder value maximisation of an oil company. The algorithm based on the dynamical interaction of synchronised processes, which are interdependent GAs having own separate evolutions of their populations. The developed system ...
Added: June 6, 2014
A Binary Model versus Discriminant Analysis Relating to Corporate Bankruptcies: The Case of Russian Construction Industry
Neretina Ekaterina, Neretina E., Journal of Accounting, Finance and Economics 2013 Vol. 3 No. 1 P. 65–76
The last market crash of 2008-2009 showed that the construction sphere is one of the most fragile subject to the crisis effect. The destructive effect of this crash resulted in substantial decrease in mortgage lending, price index, capital investment, and in growth of the cost level. As the construction industry remains strategically important, the eruption ...
Added: September 5, 2013
  • About
  • About
  • Key Figures & Facts
  • Sustainability at HSE University
  • Faculties & Departments
  • International Partnerships
  • Faculty & Staff
  • HSE Buildings
  • HSE University for Persons with Disabilities
  • Public Enquiries
  • Studies
  • Admissions
  • Programme Catalogue
  • Undergraduate
  • Graduate
  • Exchange Programmes
  • Summer University
  • Summer Schools
  • Semester in Moscow
  • Business Internship
  • Research
  • International Laboratories
  • Research Centres
  • Research Projects
  • Monitoring Studies
  • Conferences & Seminars
  • Academic Jobs
  • Yasin (April) International Academic Conference on Economic and Social Development
  • Media & Resources
  • Publications by staff
  • HSE Journals
  • Publishing House
  • iq.hse.ru: commentary by HSE experts
  • Library
  • Economic & Social Data Archive
  • Video
  • HSE Repository of Socio-Economic Information
  • HSE1993–2026
  • Contacts
  • Copyright
  • Privacy Policy
  • Site Map
Edit