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Гришунин Сергей Вадимович

Факультет экономических наук

Профиль на hse.ru ↗ тел.: +7 (495) 7729590 | 27422
Публикаций
56
Языков
2
Наград
2
Конференций
13
Профиль Публикации (56) Курсы (40)

Профессиональные интересы

банковский риск-менеджментКредитный анализ, кредитоспособность, кредитный рискуправление рисками на предприятииСтратегическое управление финансами фирмыстратегическое управление82.33.21 Контроллинг06.81.00 Экономика и организация предприятия. Управление предприятием82.33.00 Стратегический менеджмент. Стратегическое планирование

Должности

  • Старший научный сотрудник — Факультет экономических наук, Научно-учебная лаборатория финансовых инноваций и риск-менеджмента
  • Доцент — Факультет экономических наук, Школа финансов

Био

  • · Начал работать в НИУ ВШЭ в 2019 году.
  • · Научно-педагогический стаж: 5 лет.

Образование

  • 1999 · Кандидат экономических наук: Санкт-Петербургский государственный технический университет
  • 1996 · Магистратура: Ленинградский государственный технический университет, специальность «Экономика и управление на машиностроительных предприятиях», квалификация «Инженер-экономист»

Опыт работы

  • · 2026: Рейтинговое агентство "Эксперт РА", апрель настоящее время. Советник проектных инициатив заместителя генерального директора. В зону ответственности входит построение и внедрение системы интегрированного управления рисками, развитие перспективных продуктовых направлений и расширение международных направлений деятельности агентства в странах ЕАЭС и БРИКС. Эксперт рабочих групп Делового совета БРИКС
  • · 2026: Национальное рейтинговое агенство, управляющий директор, ноябрь 2019-март
  • · 2017: АО «Делойт и Туш СНГ, октябрь старший менеджер, risk advisory
  • · 2017: АКРА (АО), июнь июнь
  • · 2017: директор (корпоративные финансы)
  • · 2010: Moody's Investor Services, август май
  • · 2017: младший вице-президент-кредитный аналитик
  • · 2010: Fitch Ratings, август 2008- август директор (корпоративные финансы)
  • · 2008: ЗАО "Делойт и Туш СНГ, ноябрь 2004-июнь менеджер

Награды и поощрения

  • · Благодарность школы финансов НИУ ВШЭ (январь 2023)
  • · Лучший преподаватель — 2023–2025

Гранты и проекты

  • — · на соискание учёной степени кандидата наук

Конференции (13)

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  • · 2021: 8th International Conference on Information Technology and Quantitative Management (Chengdu). Доклад: The Impact of ESG factors on the performance of Information Technology Companies
  • · 2020: Международный молодежный научный форум «ЛОМОНОСОВ-2020 (Moscow). Доклад: Оценка влияния киберрисков на предприятиях розничной торговли
  • · 2020: Global Strategy and Emerging Markets Conference 2020 (Ithaca). Доклад: Developing a cyber risk management mechanism for retail companies operating in emerging market
  • · 2020: Analytics for Management and Economics Conference (AMEC) (St. Petersburg). Доклад: Comparison of empirical methods for modelling of credit ratings of machine building companies from developed and developing markets
  • · 2020: Analytics for Management and Economics Conference (AMEC) (St. Petersburg). Доклад: Development of a rating system for predicting credit risk and default probabilities of Russian banks using machine learning models
  • · 2020: Analytics for Management and Economics Conference (AMEC) (St. Petersburg). Доклад: Rating agencies in the BRICS countries
  • · 2020: Annual GSOM Emerging Market Conference 2020 (St. Petersburg). Доклад: Application of a System-synergistic Approach in the Development of the Target Costing Mechanism for a High-tech Industrial Enterprise in Emerging Market
  • · 2020: 2nd International Scientific Conference on innovations in digital economy: SPBPU IDE-2020 (St. Petersburg). Доклад: Comparison of Empirical Methods for the Reproduction of Global Manufacturing Companies’ Credit Ratings
  • · 2020: Четвертый Российский экономический конгресс (Moscow). Доклад: Разработка рейтинговой системы для прогнозирования кредитного риска и вероятностей дефолта российских банков с помощью моделей машинного обучения
  • · 2020: Eurasia Business and Economic Society (Madrid). Доклад: Development of credit rating model of assessing the creditworthiness and predicting defaults of Russian insurance companies
  • · 2020: Internet of Things, Smart Spaces, and Next Generation Networks and Systems. 20th International Conference, NEW2AN 2020, and 13th Conference, ruSMART 2020 (St. Petersburg). Доклад: Development of Risk Controlling Mechanism and Tools for Agile Projects in Telecommunications
  • · 2020: Global Strategy and Emerging Markets Conference 2020 (Ithaca). Доклад: "Developing a Cyber Risk Management Mechanism for Retail Company Operating in Emerging Market
  • · 2019: 19th International Conference on Next Generation Wired/Wireless Advanced Networks and System (Санкт-Петербург). Доклад: Development of the Mechanism of Assessing Cyber Risks in the Internet of Things Projects

Идентификаторы исследователя

Публикации (56)

Developing a Mechanism for Assessing Cyber Risks in Digital Technology Projects Implemented in an Industrial Enterprise

2020 · CHAPTER · en

This study discusses the development of a mechanism for assessing cyber risks in investment projects aimed at digitalizing industrial enterprises. The relevance of the study is determined by the increasing susceptibility of companies to cyber risks due to the introduction of innovations, as well as by the growing complexity and frequency of cyber threats. The study focuses on eliminating the methodological and functional problems of cyber risk assessment described in literature. The results include the development of a concept for the mechanism and its architecture, the structural and logical scheme of the mechanism, and the specifications of the blocks it comprises. The theoretical and methodological basis of the research is formed on the works of foreign and Russian researchers in the field of corporate finance, risk management and cyber security. When building the mechanism, risk control approaches were used to ensure an inextricable connection between the risk factors and the goals of a project. The following tools were used: (1) a bow-tie chart for risk identification; (2) statistical data analysis methods; (3) risk-oriented budgeting and simulation modelling using the Monte-Carlo method; and (4) the “Micromort” method for evaluating the probability distribution parameters. In comparison to analogues, the mechanism represents an integrated approach to risk management and ensures integration and coordination of risk management actions between project management and other information security services. It allows the confidence intervals of return on invested capital values to be calculated for a project with due regard of cyber risks at the planning stage, as well as to identify and prioritize the degree of influence the main sources of threats have, which, as a result, provides a comprehensive and objective assessment of cyber risks. The calculation data can be used by project managers to enhance risk management actions. The functionality of the mechanism includes the analysis of how individual cyber risks affect the goals of a project, consideration of correlations between risks, calculation of the expected, unexpected and critical level of losses and forecasting in circumstances where information is limited. These advantages make the risk assessment process dynamic, iterative, and reactive to the changes in the environment and to the appearance of new threats.

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Оценка влияния киберрисков на предприятиях розничной торговли

2020 · CHAPTER · ru

Доклад посвящен представлению разработанного механизма управления рисками информационной безопасности (киберрисков) и модели оценки влияния таких рисков на предприятия сектора розничной торговли. Актуальность темы объясняется высокой подверженностью розничных компаний киберратакам и значительными финансовыми потерями предприятий от реализации киберрисков

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Comparison of Empirical Methods for the Reproduction of Global Manufacturing Companies’ Credit Ratings

2020 · ARTICLE · en

The quantitative assessment of the credit quality of manufacturing companies is a task of great interest to researchers and practitioners. This is underpinned by the elevated credit risk of these companies stemming from rapid technological changes. However, few studies have addressed this issue specifically for manufacturing companies. This study aimed to fill this research gap by comparing the predictive power of various methods in reproducing manufacturing companies’ public credit ratings from available financial and non-financial data. The sample included 109 manufacturing companies from developed and emerging markets over the period 2005–2016. The analysis included three methods: ordered logistic regression (OLR) and two machine learning techniques, random forest and gradient boosting. The results showed that machine learning techniques outperformed OLR in terms of predictive power. In the best specification model, random forest had an accuracy of 50%, followed by gradient boosting (47%) and OLR (25%). We also tested two types of sampling in the training and test sets: random and time-dependent. The results showed that the models’ predictive power was greater with random sampling. The inclusion of macroeconomic variables did not improve the models’ predictive power due to the rating agencies’ preferred through-the-cycle rating approach. The study’s findings have implications for the development of manufacturing firms’ internal credit ratings. They can also be useful for researchers exploring the accuracy of empirical models in predicting industrial firms’ insolvency and creditworthiness.

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Application of a System-synergistic Approach in the Development of the Target Costing Mechanism for a High-tech Industrial Enterprise in Emerging Market

2020 · CHAPTER · en

The goal of this study is the development of the target costing mechanism for a high-tech industrial enterprise based on system-synergistic approach (SSA). The relevance of the study is underpinned by increasing uncertainty of business environment. The “conventional” cost management systems based on functional, process, project or systembased approaches have become inefficient due to their low flexibility and adaptability to the external changes. Application of approach ensures the continuous interaction to the environment, accounting for risks and adaptation of costing system to the external changes. The mechanism is aimed for implementation in the company’s R&D processes. It provides monitoring and assessment of impact of uncertainties on the cost drivers and on the cash flow return on investment (CFROI) during the product lifecycle. The results include the mechanism’s concept, its block diagram, and tools. The mechanism provides holistic approach to SSA applications and ensures integration and coordination of target costing activities.

Development of Risk Controlling Mechanism and Tools for Agile Projects in Telecommunications

2020 · CHAPTER · en

We developed the mechanism and tools of risk controlling in agile projects for companies in information and communication (ICT) industry. The relevance of this topic is underpinned by (1) the growing number of failures of agile projects due to realization of unique set of risks; and (2) the fact that standard agile practices neglect important risk management steps. The paper fills the research gaps in this area and addresses inefficiencies in explicit agile risk management frameworks. The results include the development of the mechanism’s concept and the block diagram for scrum framework. They also include risk controlling tools: risk-based release planning, system of key risk indicators and agile risk controlling effectiveness evaluation tree. Unlike peers mentioned in existing studies the mechanism provides holistic approach to the agile risk management while keeps the spirit of agile. It addresses risk governance issues, ensures integration and coordination of risk management activities both inside the team and across the company and provides for lightweight but efficient tools. The mechanism can be adapted for other agile frameworks and can be applied by scrum masters and project managers in ICT industry as well as by the researches who are interested in further enhancement in agile risk management practices.

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Development of the Mechanism of Assessing Cyber Risks in the Internet of Things Projects

2019 · CHAPTER · en

We developed the mechanism of assessing cyber risks for Internet of Things (IoT) projects. The relevance of this topic is explained by growing sophistication of cyber-attacks, the speed of new threats emergence and increasing damage from the attacks. The paper addresses decreasing efficiencies of existing mechanisms of cyber risk assessment and fills the research gaps in this area. Results include development of the mechanism’s concept, its block diagram, the specification and description of its comprising tools and the case study. Unlike peers, the mechanism provided holistic approach to cyber risk assessment; integrated and coordinated all related activities and tools. It simulated the confidence interval of project return on investments (ROI) and showing the chances to go above risk appetite. It makes cyber risk assessment dynamic, iterative, responsive to changes in cyber environment. These advantages let us conclude that the mechanism should have a significant scientific and practical use.

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Developing a Cybersecurity Risk Analysis System for High-Tech Equipment in Machine Industry

2019 · CHAPTER · en

The paper is dedicated to developing a system for identifying and assessing cyber-risks to support investment decision-making in a machine industry enterprise. It is designed for projects related to high-tech equipment development and introduction. The problem is acute because the existing methods of cyber-risk analysis have some drawbacks, which prevent them from being used at a time of growing information threats. A structural-logical scheme for the cyber-risk analysis system has been developed, and detailed descriptions are provided for some blocks of the system and their tools. The research methods include system approach to problem-studying, analysis of fundamental statements given in literature, and analysis of the existing tools used in practice for solving these problems. The presented system has some advantages in comparison with such common approaches as risk maps or factor analysis of information risks (FAIR). Since it is built on risk-control principles, it ensures that all actions of management concerning cyber-risk-control are integrated and coordinated. The system also contains effective tools and methods for assessing cyber-risks in quantitative terms, calculating a consolidated effect with due consideration of risks, assessing the impact this effect makes on the strategic goal indicator of a project, comparing project implementation scenarios given cyber threats with risk appetite to evaluate the acceptability of the project. These advantages make the system dynamic and integrative, reactive to the changes of the cyberspace and emergence of new threats. It can have a substantial practical application in managing investment projects related to the development and introduction of high-tech equipment in enterprises of the sector. The paper is dedicated to developing a system for identifying and assessing cyber-risks to support investment decision-making in a machine industry enterprise. It is designed for projects related to high-tech equipment development and introduction. The problem is acute because the existing methods of cyber-risk analysis have some drawbacks, which prevent them from being used at a time of growing information threats. A structural-logical scheme for the cyber-risk analysis system has been developed, and detailed descriptions are provided for some blocks of the system and their tools. The research methods include system approach to problem-studying, analysis of fundamental statements given in literature, and analysis of the existing tools used in practice for solving these problems. The presented system has some advantages in comparison with such common approaches as risk maps or factor analysis of information risks (FAIR). Since it is built on risk-control principles, it ensures that all actions of management concerning cyber-risk-control are integrated and coordinated. The system also contains effective tools and methods for assessing cyber-risks in quantitative terms, calculating a consolidated effect with due consideration of risks, assessing the impact this effect makes on the strategic goal indicator of a project, comparing project implementation scenarios given cyber threats with risk appetite to evaluate the acceptability of the project. These advantages make the system dynamic and integrative, reactive to the changes of the cyberspace and emergence of new threats. It can have a substantial practical application in managing investment projects related to the development and introduction of high-tech equipment in enterprises of the sector.

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Development of the Mechanism of Risk-Adjusted Scheduling and Cost Budgeting of R&D Projects in Telecommunications

2018 · CHAPTER · en

We developed the mechanism of risk-adjusted scheduling and cost budgeting of research and development (R&D) projects in telecommunication. The relevance of this topic is explained by growing complexity and uncertainty of innovation activity; high importance of cost and time as key metrics of R&D projects’ performance. The paper addresses decreasing efficiency of existing mechanisms which poorly incorporate risks and fills the gaps in the research in this area. Results included development of the concept of the mechanism, its block diagram, the specification of its comprising tools, the step-by-step description of its phases. Unlike the “conventional” peers, the developed mechanism allows timely identification of uncertainties; facilitates robust and transparent evaluation of risks; focuses management efforts on key threats; and ensures remediation of risks earlier in the process thus improving speed and quality of decision making. These advantages let us conclude that the suggested mechanism should have a significant practical use.

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Паттерны кредитных рейтингов промышленных компаний стран БРИКС

2018 · CHAPTER · ru

Данная работа посвящена изучению вопроса о связи кредитных рейтингов и финансовыми показателями промышленных компаний. В основу исследования был взят один из современных методов построения нелинейных взаимосвязей для выделения групп разнородных объектов влияния, также известный как метод паттернов. Дополнительно, было проведено эконометрическое оценивание выделенных разнородных групп, полученных паттернов промышленных компаний, с помощью модели Тобина. Результаты работы можно использовать в целях практического управления финансовыми рисками на краткосрочном периоде времени

Разработка концепции риск-контроллинга для промышленного предприятия

2018 · ARTICLE · ru

Введение. Статья посвящена разработке новой концепции риск-контроллинга (РК) на промышленном предприятии, действующем в условиях динамичного окружения. Решение концептуальных вопросов РК актуально, поскольку существующие концепции обладают недостатками, ограничивающими их применение. Данные и методы. Дано определение концепции РК, как структурированного и точного представления сути РК, определяющего его место в системе управления предприятием. Определены методы исследования: системный подход к изучению проблемы; фундаментальные теоретические положения, изложенные в источниках. Полученные результаты. Проанализированы существующие концепции РК. Показано, что среди них только «интеграционная концепция» ограниченно подходит для промышленных предприятий, действующих в турбулентном окружении. Доказано, что заложенное в этой концепции представление РК в виде «организующей метафункции» управления рисками (УР) приводит к проблемам с: (1) разделением управляющей и исполнительной систем, (2) определением границ между «метафункцией» и другими функциями УР и; (3) наличием конфликтов между менеджерами и риск-контроллерами. Разработана «управленческая» концепция РК, согласно которой РК - система УР, имеющая свои функции, инструментарий и эволюцию развития. Она информационно и методически обеспечивает все функции и сферы УР для их координации и интеграции. Достоинствами предложенной концепции являются: (1) обеспечение связи УР с бизнес-целями предприятия; (2) ориентация на поиск возможностей и раннее выявление угроз; (3) обеспечение координации и интеграции УР во все функции, сферы и процессы управления; (4) распространение УР на всю цепочку ценностей предприятия. Заключение. «Управленческая концепция» РК отвечает требованиям к системам управления рисками промышленных предприятий, действующих в динамичном окружении, а также преодолевает ограничения, свойственные ранним концепциям РК. Она может быть использована практикующими контроллерами в качестве основы для создания системы РК

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Курсы (40)