Evolving Strategies for the Structuring of Working Capital Loans during Covid Times: An Analysis of Select Indian Private Sector Banks

Predicting human behavior is a difficult task, yet bankers perform this regularly while sanctioning working capital loans, so that money advanced is recoverable. For this, they try to assess credit worthiness of clients based on past performance through financials and banking habits amongst other parameters. Clients also look at fees and instalment burden, duration of loan, etc. However, with the adverse impact of Covid pandemic on earning capacities, banks need to relook at the way they structure loans. This study suggests that customer-focused, risk-adjusted analysis should be undertaken to reduce non-performing assets and improve asset portfolio quality of banks.

Legislative Capacity and Credit Risk

Legislatures differ in their institutional capacity to draft and enact policy. While strong legislatures can increase the congruence of policy outcomes to the electorate's preferences, they can also inject uncertainty into markets with their ability to alter the political economic landscape. We argue that this uncertainty will manifest in a state's ability to borrow and hypothesize a negative relationship between legislative capacity and credit-worthiness. Using ratings of general obligation bonds issued by the American states over nearly two decades and data on the institutional capacity of state legislative assemblies, we find support for the claim that having a legislature that is better equipped to affect policy change increases credit risk evaluations. The results we present broaden our understanding of the importance of legislative institutions, the determinants of credit risk, and the economic implications of democratic responsiveness.

ALGORITHMIC IMAGINATIONS: RETHINKING “ALGORITHMIC” AS A HEURISTIC FOR UNDERSTANDING COMPUTATIONALLY-STRUCTURED CULTURE

How we imagine our place within the structure of sociotechnical-human relationships—specifically, in domains of life affected by data-analytics and the probabilistic bets institutions and people in power make on the future of our credit worthiness, political leanings, shopping habits etc.—is our “algorithmic imagination.” The purpose of this panel is to explore the “algorithmic imagination” as it manifests in particular scholarly, historical, socio-cultural, and technical contexts. The panelists prioritize how social actors, situated in distinct settings, go about constructing an “algorithmic imagination” in conversation/opposition with how computational systems have “imagined” them; they will also reflect critically and self-reflexively on the implications of an algorithmic imagination, so conceived. Collectively, the panelists demure from monolithic understandings of the “algorithmic imagination” while also embracing algorithmic intersectionality. The primary contention of this panel is that the ways in which algorithms have been “thought,” or imagined, have made it difficult to conceive of practicable strategies for transforming algorithmic cultures and, indeed, for delinking them from both state and corporate control. The panel, thus, makes three primary contributions. First, we situate, define, and distinguish the concept, “algorithmic imagination.” Second, the panel provides analyses of key facets of the algorithmic imagination, in specific historical settings and life-worlds defined by intersectionality. Lastly, it aims to contribute, however provisionally, to a political theory that recognizes the deterministic power of computational systems but rejects the notion that power is inherently democratic or monolithically insurmountable.

Corporate Perspectives on the Panoptic Sort

This chapter is focused on understanding the similarities and differences within the corporate sectors actively engaged in the development and use of the panoptic sort in support of their business ventures. The chapter focuses on three central actors of the time: the American Express Corporation, a dominant data services provider; TRW, a major defense contractor; and Equifax, an emerging giant in the provision of information about credit worthiness and other assessments of financial worth. Additional attention is focused on the special role played by a market auxiliary, the Direct Marketing Association, which played a central role in defending the industry against privacy laws and regulations emerging on the horizon. An additional effort to understand the corporate perspective on surveillance and the pursuit of power and influence made use of a survey of Fortune 500 companies at the time. Despite the quite low participation rate of the members of this special class, characteristics of their marketing techniques, their concerns about government regulation, and their assignment of responsibility for the development of a regulatory response were subject to analysis. It was not surprising to see how concerned they actually were about a consumer backlash against their collection and use of transaction-generated information.

Credit-worthiness Prediction in Energy-Saving Finance using Machine Learning Model

Companies can form their own "ESCO model" with their capitals. New opportunities that Energy Saving Company (ESCO) can do was to offer PSS business model in the form of Energy Saving Agreement (ESA) or Energy Saving Performance Contract (ESPC), which was known as "saving back arrangement financing." ESCO contracts could free business owners from new upfront investment. Unfortunately, customer's creditworthiness was becoming more crucial for ESCO. Machine learning was used to predict the creditworthiness of clients in ESCO financing processes. This research aimed to develop a scoring model to leverage a machine learning and life cycle cost analysis (LCCA) to evaluate alternative financing for Energy Saving in Indonesia. Research from the case studies leads to a clearer understanding of the factors that affect all parties' decisions to implement and continue with their ESCO project. Both considerations, technology, and administration emerge from this case study which greatly influenced the participants to adopt the decision and continue with the ESCO project. In contrast, both parties agreed to solve the credit risk constraints on the project. This study indicates that administration influences were more significant than the technological factor in shaping their decisions.

Methodological approach to the credit worthiness estimation of counterparties at mining enterprises

Purpose. Development of a comprehensive methodological approach to the credit worthiness estimation of counterparties in the mining industry as a part of a conservative credit policy. Methodology. The tasks set in the article have been solved by using modern general scientific and special methods: abstract and logical method for the implementation of theoretical generalizations, the conclusions and recommendations formation; the hierarchy analysis method to justify the priority of structural parameters for credit worthiness estimation of counterparties of mining enterprises. Moreover, the authors own previous research results regarding receivables management are used. Findings. The structural parameter priority of the credit worthiness estimation of counterparties at mining enterprises within the conservative credit policy has been propose`d, which is substantiated by the hierarchy analysis method. Synthesizing the formed hierarchical model and theoretical achievements on the issues of receivables management, a structural and logical sequence of the credit worthiness estimation of counterparties of mining enterprises has been developed. Originality. A comprehensive methodological approach to the credit worthiness estimation of counterparties in the mining industry within a conservative credit policy has been developed. Compared to the existing ones, it is a clear algorithm of estimation stages based on a hierarchical model of structural parameters of credit worthiness estimation. The advantages of the authors development are: system flexibility at the stage of formation of criterion base and structural components; clear formalization of results; detailed structuring of evaluation parameters; the possibility of forming a clear unambiguous conclusion about the credit worthiness estimation of counterparties of mining enterprises; compliance of the methodological tools of the estimation system to current trends in the mining industry. Practical value. A comprehensive methodological approach to the credit worthiness estimation of counterparties in the mining industry is used to achieve the effective planning, regulation, control, rational organization of relations in the field of cash flow.

The Impact of a Social Assistance Program on the Quality of Life of Older People in Uganda

This study explores the impact of social assistance on older persons’ quality of life in a Ugandan district. The purpose of the study is to establish how older persons aged above 65 years provide their livelihood in the wake of declining and waning informal family/clan/society support systems. These systems have been the source of their care for a long time. The study therefore examines how the recipients of the grant manage their everyday life amid changing norms in reciprocal care. The study is based on two focus group discussions with 13 older grant beneficiaries and four in-depth interviews with key participants affiliated with the social assistance scheme. The study’s main results include themes such as fulfilling basic needs, start-up capital and credit worthiness, supplementary income, and respite from isolation and loneliness. The study shows positive changes in the lives of older persons and a notable relative improvement in the standards of living of older persons in beneficiary districts.

Feeling the Heat

Climate change is an existential threat to the world economy like no other, with complex, evolving and nonlinear dynamics that remain a source of great uncertainty. There is a bourgeoning literature on the economic impact of climate change, but research on how climate change affects sovereign risks is limited. Building on our previous research focusing on the impact of climate change on sovereign risks, this paper empirically investigates how climate change may affect sovereign credit ratings. By means of binary-choice models, we find that climate change vulnerability has adverse effects on sovereign credit ratings, after controlling for conventional macroeconomic determinants of credit worthiness. On the other hand, with regards to climate change resilience, we find that countries with greater climate change resilience benefit from higher (better) credit ratings. These findings, robust to a battery of sensitivity checks, also show that impact of climate change is disproportionately greater in developing countries due largely to weaker capacity to adapt to and mitigate the consequences of climate change.

CREDIT WORTHINESS OF AGRICULTURAL ENTERPRISES

Background. Agriculture is a source of increased credit risk for banks and other lenders, which requires special approaches to assessing the credit worthiness of the enter­prises in this industry. The assessment improving of the credit worthiness of the agricu­ltural enterprises is one of the key scientific and practical problems. The aim of the article is to identify and systematize the factors influencing the level of credit worthiness of the agricultural enterprises. Materials and methods. The theoretical basis of the research is a systematic app­roach that has been used to identify and analyze the factors of credit worthiness of the agricultural enterprises. The methodological basis consisted of system-structural, compa­rative analysis and logical generalization methods. The information basis of the research is analytical materials, scientific researches, results of own researches. Results. The purpose of assessing the credit worthiness of the agricultural enterprise is to obtain a quantitative and qualitative assessment of the borrower’s activities by a cre­ditor. Based on this, creditor assesses the risk of lending and decides about the possibility and con­ditions of lending or refusal to the borrower. Existing methods of assessing the credit worthiness of the agricultural enterprises do not often take into account the peculiarities of their activities, which directly affect the ability of these enterprises to repay the loan. During the assessing the credit worthiness of the agricultural enterprise, it is appropriate to take into account financial indicators that characterize its financial position and non-financial factors that describe the actual and potential conditions of its management. Based on the results of systematization of existing approaches and own conclusions, it is proposed to classify the factors influencing the credit worthiness of the agricultural enterprises by the source of influence on the company, the possibility of influence by the company, the method of measurement, nature. Conclusion. The article presents the author’s vision of the classification factors influencing the agricultural enterprises ability to obtain credit and expand their list by addition them with factors of soil quality and organic production, which will reduce the credit risk of financial institutions in lending.