Business Value Analysis at Yes Bank

This case is related with the biggest 2020 scam by one of the major new private sector banks (i.e., YES bank). The case is related with the misuse of the power of banks in providing the benefits to one person, due to the power and influence granted by the political party leaders that influence providing unlimited loans to one person and further the acts of the bank officials that led to the partial breakdown of the banking system in India. Further, the case deals with the major accused and the shell company's creator as DHFL. The present analysis put lights on the future lessons to be learnt by various sectors in order to prevent heavy losses and loss of customer faith (being the most vital component). It starts by giving a background of the crisis that led the RBI to come into picture. It also shows the effectiveness of the actions of RBI for YES bank. At last, it points out the importance of independent management and the roles of auditors and other regulators in dealing with this crisis.

Exploring Shared Work Values and Work Collaboration With a Network Approach

A real-life case study presented in this chapter reports on how organizational network analysis approach was used in a medium-sized Italian company with circa 100 employees to examine how the company employees were connected by shared values at work, what these values are, and whether and how their value connectedness impacted the quality of their collaboration. The findings indicate that there was a positive correlation between shared work values and work collaboration, present benchmarks for network parameters, as well as propose macro-categories of work values. To the best of the authors' knowledge, this is the first study to use the network-analysis approach to explore shared values and employee collaboration at work. The chapter should be of substantial interest not only to academic scholars but also to organizational leaders and HR practitioners.

The Integrated Value Model (IVM)

The integrated value model (IVM) empowers analysis of the interdependent aspects of policies, plans, performance measures, priorities, and programs (P5). As organizations are holistic systems of processes and performance, knowing how P5 adds value becomes critical to success and achievement of internal goals and responses to external demands. Modeling these artifacts and mapping them to policies and practices allows analysts to measure the alignment to initiatives. The IVM supports efforts in strategic communications, change management, strategic planning, and decision support. Elements of P5 have explicit hierarchical and relational connections, but modeling the connections and developing logical inferences is an uncommon strategic business practice. This chapter describes how to use those goals to create a logical model for a public sector organization and how to use this model to identify, describe, and align business value. Further, this chapter demonstrates the model's capabilities and suggests future applications.

Strategic Analytics Augmented Organization

Business strategy is all the actions and decisions taken by the management to achieve the business goals for sustaining the competitive edge. A successful business strategy determines the longevity of the organization. The strategists analyse the vision, mission, and values to frame and articulate the business strategy. Different tools such a Business Model Canvas, etc. are then used to create the business model. Once the business strategy is created, it is also equally critical to evaluate the same amidst the changing business environment. For the validation of strategies at all levels, data plays a vital role for the management to proceed with fact-based decision making. Informed decisions based on facts reduce the probability of erroneous results assisting the businesses align to the documented strategy. Strategic analytics practice creates the essential understanding about how the quantitative techniques and methods can be deployed using the structured and unstructured data that assists strategic decision making for the organization.

Implementing AI Techniques to Address the Challenges Surrounding Cryptocurrencies

The research work is focused on examining the role of artificial intelligence (AI) in addressing challenges associated with cryptocurrencies like Bitcoin, Ethereum, etc. The popularity of Bitcoin has sparked the emergence of new alternative cryptocurrencies, commonly referred to as ‘altcoins'. Simultaneously with its growing popularity and public awareness, the Bitcoin system has been branded as a haven for security breaches, selfish mining, money laundering, extreme volatility, and unpredictability of future prices. To address these challenges, stakeholders accepting cryptocurrencies must apply AI techniques to process and analyze large amounts of cryptocurrency data. In this context, this chapter discusses the recent research work to assist the researchers and practitioners in the cryptocurrency domain to make fact-based decisions by using AI techniques. Consequently, the chapter provides a detailed review of the background on fiat currencies, cryptocurrencies, challenges associated with cryptocurrencies, and the role of AI techniques in addressing those challenges.

Credit-Market Imperfection and Monetary Policy Within DSGE Models

This survey presented the various ways that are utilized in the literature to include financial market frictions in dynamic stochastic general equilibrium (DSGE) models. It focuses on the fundamental issue: to what extent the Taylor rules are optimal when the central bank introduces the goal of financial stability. Indeed, the latest financial crisis shows that the vulnerability of the credit cycle is considered the main source for the amplification of a small transitory shock. This conclusion changed the instrument that drives the transmission of monetary policy through the economy and pushed the policymakers to include financial stability as a second objective of the central bank.

Entrepreneurial Resilience and Market Turbulence in SMEs

Entrepreneurial resilience is a recent topic and is widespread in scientific research, especially when associated with periods of instability and crises. This chapter aims to analyze the relationship between the variables open-mindedness (OM), entrepreneurial resilience (ER), market turbulence (MT), and overall performance (OP) in SMEs located in the legal amazon. Data collection coincided with the pandemic of COVID-19, with 384 SME managers participating. The sample was analyzed using structural equation modeling (SEM). The results suggest mediation of the variable ER on the relationship between OM and OP, and moderation of the variable MT on OM and ER. The research's originality is attested by the model's empirical relationships, research context, and adverse scenario provided by the COVID-19 expansion. The practical implications indicate that managers should pay more attention to the variables investigated through the creation of new skills and competencies necessary for entrepreneurial activity in periods of economic crisis and market turbulence.

A Study on the Use of Business Intelligence Tools for Strategic Financial Analysis

The research work is focused on examining the role of business intelligence (BI) tools in strategic financial analysis. The effective utilization of data is essential in order to survive in today's competitive business environment. Traditionally, data analysis was performed manually by using a spreadsheet. However, due to big data proliferation at an unprecedented pace, it becomes difficult for the financial services industry to manage large datasets. Therefore, to address this issue, both academia and industry practitioners have come forward to meet the needs of a growing business with the help of BI tools. In this context, this chapter aims to assist the BI researchers and practitioners in the financial services industry to make fact-based decisions by using popular BI tools like Power BI, Tableau, and SAS analytics. Consequently, the chapter provides a detailed review of the applications of these BI tools in strategic financial analysis and to enhance overall corporate performance.

Cold Calling as a Strategic Tool to Improve the Recruitment and Selection Processes

Cold calling has been an essential tool for decades in marketing of goods and services. On the other hand, with time, recruitment and selection has become a hectic and hefty task for organizations. This report tries to highlight the scope and importance of cold calling in recruitment and selection. It also highlights the effectiveness and efficiency of recruitment agencies and their proficiency in finding the best possible candidate. It also tries to find the importance of various factors like company image, remuneration, job position, etc. that shape the attitude of a potential candidate towards a job offer. The chapter also puts focus on the skills of the sales representative that have an important effect in shaping the attitude of a prospect towards the job opening.

Simple Valuation of Compounded Deferred Tax Assets Using a Binomial Algorithm

Deferred tax asset (DTA) is a tax/accounting concept that refers to an asset that may be used to reduce future tax liabilities of the holder. In a company's balance, it usually refers to situations where it has either overpaid taxes, paid taxes in advance, or has carry-over of losses (the latter being the most common situation). In fact, accounting and tax losses may be used to shield future profits from taxation, through tax loss carry-forwards. The purpose of this chapter is to propose a precise and conceptually sound approach to value DTAs. For that purpose, making use of an adapted binomial CRR (Cox, Ross, and Rubinstein) algorithm, the authors derive a precise way to value DTAs. This way, the DTAs are valued in a similar way of the binomial options pricing model, and the subjectivity of its evaluation is greatly reduced. The authors show that with the proposed evaluation techniques, the DTA's expected value will be much lower than the values normally used in today's practice, and the bank's financial analysis will lead to much more sound and realistic results.