Проектные лаборатории

Business Restructuring and  Value Creation: Best Practices for Corporate Antifragility.

A comprehensive presentation outlining the root causes of a company's distress, proposed restructuring measures, and the outcomes of anti-crisis actions.

Business Ecosystems: the Challenges for Value Creation and Capture

Emerging markets (EM) differ from developed economies (DE) in many ways: economy size and growth, income per capita, etc. While EMs are commonly runner-ups to DEs, in business’ digitalization many EMs teach the DMs what “state of the art looks like”. Striking facts can be found e.g. in banking, e-com, etc. However, this fact by itself does not provide evidence on the relative impact of digitalization on business in EMs vs DMs. In this paper we review the literature on this difference, covering 4 digitalization tools: AI and blockchain technologies, ecosystems business model and agile org. structures. These tools are selected due to their industry-agnostic applicability, albeit with varying impacts. We consider 3 aspects of a firm’s life: strategy and business model (where the firm plays and how it makes money), operations (how the firm delivers on the strategy), organization and governance (how the firm structures itself). The findings suggest significant variations across the board.

M&A : Identifying Value Creation Opportunities

Students will work in groups and go through the key Strategic M&A workflows – how to structure a deal, how to approach valuation, how to present and close a transaction. The goal would be to prepare a comprehensive Presentation of an M&A opportunity to an Investment Committee.

AI in Finance. Search for best Practices

The aim of the project laboratory is to acquaint students with the main interpretable and non-interpretable machine learning methods and to teach them how to apply these methods in practical cases, particularly for assessing the credit risk of corporate and retail bank borrowers. The project laboratory includes 6 seminar sessions: in the first 3 sessions, students will be shown the main interpretable and non-interpretable machine learning methods, their implementation using Python, and will be given practical homework examples to test their understanding of the material covered. In the remaining 3 sessions, students will be shown the application of machine learning methods to credit risk assessment (probability of default, loss given default, retail scoring), the implementation of these algorithms using Python, and similar homework examples to test their understanding of the material covered. Homework results are assessed on a scale from 0 to 10 points.

Non-Financial Capitals by Керт  Team

The "Non-Financial Capitals" lab is a practice-oriented educational module designed to explore the management and evaluation of a company's critical non-financial assets, including natural, human, social, and trust capital. Under the guidance of experts from the consulting firm Kept (formerly KPMG), who annually assist in preparing over 30 reports for major Russian companies, participants will delve into the complete lifecycle of non-financial reporting.

Climate Finance for Value Creation Strategies: Experience from BRICS

The Lab is focused on new professional track for graduate students in corporate finance. The 2026 Lab Final project will develop climate finance best practices collection in BRICS. The final product of team working would become a part of new book on corporate antifragility at times of new geopolitical pressures. Team’s projects would be concentrated on  country’s regulations and experience  at industry and firm - level and its contribution to value creation. The students are expected to develop a collection of national cases in climate finance applications to compare Russian companies to other BRICS  countries  in   similar industries.