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To examine bad credit experiences in the context of identity to understand the entanglement between bad credit and the deformation of identity.

A qualitative method using depth interviews and hermeneutical analysis.

Bad credit is a major life event and plays a critical role in identity. By restricting or eliminating identity construction and maintenance through consumption, identities are deformed. Consumer identities are deformed as they are consumed by the identity deformation process as normal patterns of consumption that have built and supported their identities are disrupted and demolished. Bad credit is overwhelmingly consumptive of consumers – it consumes their time, energy, patience, lifestyle, relationships, social connections, and perhaps most importantly, it consumes their identity as it deforms who they are.

Researchers need to examine more closely not just the creation and maintenance of identity, but also how identity is deformed and deconstructed through consumption experiences that can no longer be enjoyed.

Government agencies may want to reexamine policies toward the granting of credit to reduce the incidence of loading up consumers with credit they are not able to pay for. The deformation of identity may result in anti-social behavior, although our study does not address this directly.

This study is different from previous work in several ways. We focus on identity deformation due to bad credit. By analyzing a crisis response that transcends the specific impetus of bad credit, we extend identity theory by developing an insight into “identities-in-crisis.” We also provide a theoretical framework and explore how consumers’ identities are deformed and renegotiated.

Hisbah is one of the distinguished institutions that had emerged since the early days of the Islamic empire. Based on its cardinal duty to enjoin good and prohibit evil, over time, its functions gradually expanded, and its responsibilities increasingly grew. In light of the contemporary trend in establishing institutional framework for consumer protection, entrusting an agency with multifarious tasks may not be the best and effective way in handling consumer protection issues. Thus, this chapter attempts to explore the new paradigm of hisbah as a consumer protection institution in Malaysia with a special reference to the Islamic consumer credit industry. While utilising the doctrinal legal research methodology, relevant sources of law have been examined and analysed. This research finds that the classical hisbah institution provides a good reference point in establishing regulatory agency and dispute management body. Nevertheless, some modifications are required to remain relevant especially in terms of specialisation of role and function. Likewise, it is viewed that adjustment of the hisbah institution is also necessary regarding the characteristic of the muhtasib (ombudsman).

Financial systemic risk is often assessed by the interconnectedness of financial institutes (FI) in terms of cross-ownership, overlapping investment portfolios, interbank credit exposures, etc. Less is known about the interconnectedness between FIs through the lens of consumer credits. Using detailed consumer credit data in Canada, this chapter constructs a novel banking network to measure FIs’ interconnectedness in the consumer credit markets. Results show that FIs on average are more connected to each other over the sample period, with the interconnectedness measure increases by 19% from 2013 Q4 to 2019 Q4. FIs with more diversified portfolios are more connected in the network. Among various types of FIs, secondary FIs have the notable increase in interconnectedness. Domestic Systemically Important Banks and secondary FIs offering a broad range of loan products are more connected to large FIs, while those specialized in single loan types are more connected to their industry peers. FI connectedness is also significantly related to their participation in the mortgage markets.

Both consumer and corporate credit ratings agencies played a major role in the US subprime mortgage crisis. Equifax, Experian, and TransUnion deployed a formalized scoring system to assess individuals in mortgage origination, mortgage pools then were assessed for securitization by Moody's, S&P, and Fitch relying on expert judgment aided by formal models. What can we learn about the limits of formalization from the crisis? We discuss five problems responsible for the rating failures – reactivity, endogeneity, learning, correlated outcomes, and conflict of interest – and compare the way consumer and corporate rating agencies tackled these difficulties. We conclude with some policy lessons.

The experience of the 1990s renewed economists’ interest in the role of credit in macroeconomic fluctuations. The locus classicus of the credit-boom view of economic cycles is the expansion of the 1920s and the Great Depression. In this paper we ask how well quantitative measures of the credit boom phenomenon can explain the uneven expansion of the 1920s and the slump of the 1930s. We complement this macroeconomic analysis with three sectoral studies that shed further light on the explanatory power of the credit boom interpretation: the property market, consumer durables industries, and high-tech sectors. We conclude that the credit boom view provides a useful perspective on both the boom of the 1920s and the subsequent slump. In particular, it directs attention to the role played by the structure of the financial sector and the interaction of finance and innovation. The credit boom and its ultimate impact were especially pronounced where the organization and history of the financial sector led intermediaries to compete aggressively in providing credit. And the impact on financial markets and the economy was particularly evident in countries that saw the development of new network technologies with commercial potential that in practice took considerable time to be realized. In addition, the structure and management of the monetary regime mattered importantly. The procyclical character of the foreign exchange component of global international reserves and the failure of domestic monetary authorities to use stable policy rules to guide the more discretionary approach to monetary management that replaced the more rigid rules-based gold standard of the earlier era are key for explaining the developments in credit markets that helped to set the stage for the Great Depression.

This chapter shows how to identify the characteristics of borrowers that are part of a credit scoring model. The credit risk scoring model is an important tool for evaluating credit risk associated with customer characteristics that affect defaults. This research was conducted at a financial institution, a subsidiary of a commercial bank in Indonesia, to answer the challenge of determining the feasibility of providing financing quickly and accurately. This model uses a logistic regression method based on customer data with indicators of demographic characteristics, assets, occupations, and financing payments. This study identifies nine variables that meet the goodness of fit criteria, which consist of WOE, IV, and p-value. The nine variables can be used as predictors of default probability: type of work, work experience, net finance value, tenor, car brand, asset price, percentage of down payment (DP), interest, and income. The results of the study form a risk assessment model to identify variables that have a significant effect on the probability of default.

Traditionally, loan officers use different credit scoring models to complement judgmental methods to classify consumer loan applications. This study explores the use of decision trees, AdaBoost, and support vector machines (SVMs) to identify potential bad loans. Our results show that AdaBoost does provide an improvement over simple decision trees as well as SVM models in predicting good credit clients and bad credit clients. To cross-validate our results, we use k-fold classification methodology.

Kenya basks of a vibrant digital financial sector from her mobile and digital financial services that have led to financial inclusions. On the flip side of it, the Kenyan digital loans sector is facing ethical scrutiny from all and sundry. Issues that are arising include a customer base being trapped in the debt trap, inflated pricing model, high interest rates, and short-term loan tenures. The sector is shrouded in poor transparency and many consumer rights infringement. Undeniably, providers inadvertently breach consumers' right to privacy and tend to promote ‘push loans’ with unsolicited messages to the vulnerable. Additionally, the use of Artificial Intelligence (AI) in determining the suitability of loan applicants via algorithms is seen to be intrusive. With consumer data being mined from the mobile phone, data utilisation, mobile payment usage, airtime usage without users' express consent, it renders the sector an unethical jungle for hunting consumers. Furthermore, consumers who by default end up receiving aggressive uncouth and unprofessional treatment in a bid to recover the unpaid loans. New Product Development (NPD) should, therefore, listen to the consumer's voice for ethical concerns to be reflected in the final product. Thus, marketers should endeavour to give ethical dimensions in NPD a measurable attribute by constantly reviewing it. This chapter examines the ethical implications of developing digital loans in Kenya.

Introduction: Financial development has a direct impact on the housing market by facilitating access to credit. The increase in housing loans resulting from the relaxation of the credit constraint causes an increase in housing demand and house prices. Purpose: This study aims to examine the relationship between financial development and house prices in Turkey, using the variables: the domestic credit to the private sector and total housing and consumer credits. Methodology: To determine any long-run relationship between financial development and house prices, the autoregressive distributed lag methods are used, covering the selected variables such as real GDP, inflation, mortgage interest rate, and stock price from 2010Q1 to 2020Q2. Findings: The study’s findings show that both variables representing financial development have a statistically significant and substantial positive effect on house prices. Besides, the selected macroeconomic variables have the theoretically expected impact on house prices.

Social scientists have long been interested in how political institutions affect economic performance. Nowhere are these effects more apparent today than in the current U.S. financial meltdown. This article offers an analysis of the meltdown by showing how government regulation among other things helped cause it. Specifically, the article shows how regulatory reforms closely associated with neoliberalism created perverse incentives that contributed significantly to the increased lending in the mortgage market and increased speculation in other financial markets even as such behavior was becoming increasingly risky. The result was the failure of mortgage firms, banks, a major insurance company, and eventually the market for short-term business loans, which triggered a general liquidity crisis thereby thrusting the entire economy into a severe recession. Implications for future research are explored. The article also offers a few policy prescriptions and an assessment of their political viability going forward.