Information: Hard and Soft

Liberti, José María; Petersen, Mitchell A.

doi:10.1093/rcfs/cfy009

Cited by 402 publications

(146 citation statements)

References 105 publications

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“…Many papers have found that relationships and soft information can provide advantages in borrower screening and reduce information asymmetries in banking -see, for example, Petersen and Rajan (1994); Boot and Thakor (2000); Berger and Udell (2002); Liberti and Petersen (2017); Berger, Miller, Petersen, Rajan, and Stein (2005); Stein (2002); Karlan (2007); Iyer and Puri (2012);…”

Section: The Literaturementioning

confidence: 99%

Do fintech lenders penetrate areas that are underserved by traditional banks?

Jagtiani

Lemieux

2018

Journal of Economics and Business

293

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Fintech has been playing an increasing role in shaping financial and banking landscapes. In this paper, we use account-level data from LendingClub and Y-14M data reported by U.S. banks with assets over $50 billion to examine whether the fintech lending platform could expand credit access to consumers. We find that LendingClub's consumer lending activities have penetrated areas that may be underserved by traditional banks, such as in highly concentrated markets and in areas that have fewer bank branches per capita. We also find that the portion of LendingClub loans increases in areas where the local economy is not performing well.

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Section: The Literaturementioning

confidence: 99%

Do fintech lenders penetrate areas that are underserved by traditional banks?

Jagtiani

Lemieux

2018

Journal of Economics and Business

293

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“…3 A literature review on the role of relationship banking in resolving problems of asymmetric information is for instance in Boot (2000), while Liberti and Petersen (2018) review the importance of soft information in lending.…”

Section: Introductionmentioning

confidence: 99%

Determinants of the Credit Cycle: A Flow Analysis of the Extensive Margin

Cuciniello

Iasio

2020

SSRN Journal

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We use monthly data from the Italian Credit Register on individual loans over the period from 1997 to 2019 to show that the expansion in bank lending in the non-financial private sector is mostly explained by variations in the extensive margin, calculated either in terms of credit flows or by the headcount of new borrowers. We then build on a flow approach to decompose changes in the net creation of borrowers into gross flows across three statuses: (i) borrowers, (ii) applicants and (iii) others (neither debtors nor applicants). The paper investigates the macroeconomic credit market by looking at the new obligors (inflows), which account for the bulk of volatility in the net creation of borrowers. Second, the volatility of borrower inflows is twice that of obligors exiting the credit market (outflows). Third, borrower inflows are highly procyclical, leading the economic cycle, and their fluctuations are mainly driven by the probability of getting a loan from new banks. We read these results in light of the macrofinance literature on search frictions and on competition with lender-lender informational asymmetries. Overall, our findings support the theoretical predictions of these models, but search frictions seem to play a major role in shaping movements along the extensive margin.

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“…The difference between these sorting algorithms can be seen in a view of measure of the amount of time and/or space required by an algorithm for an input of a given size (n) [8]. Now-a-days, the amount of information grow rapidly [9] by that a high speed computing to process this huge amount of data [10] is required. So, High performance computing involves parallel processing [11].…”

Section: Introductionmentioning

confidence: 99%

BulkSort: System Design and Parallel Hardware Implementation Considerations

Ihirri¹,

Errami²,

Khaldoun³

et al. 2019

IJACSA

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Algorithms are commonly perceived as difficult subjects. Many applications today require complex algorithms. However, the researchers look for ways to make them as simple as possible. In high time demanding fields, the process of sorting represents one of the foremost issues in the data structure for searching and optimization algorithms. In parallel processing, we divide program instructions among multiple processors by breaking problems into modules that can be executed in parallel, to reduce the execution time. In this paper, we proposed a novel parallel, re-configurable and adaptive sorting network of the BulkSort algorithm. Our architecture is based on simple and elementary operations such as comparison and binary shifting. The main strength of the proposed solution is the ability to sort in parallel without memory usage. Experimental results show that our proposed model is promising according to the required resources and its ability to perform a high-speed sorting process. In this study, we take into account the analysis result of the Simulink design to establish the required hardware resources of the proposed system.

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Information: Hard and Soft

Cited by 402 publications

References 105 publications

Do fintech lenders penetrate areas that are underserved by traditional banks?

Do fintech lenders penetrate areas that are underserved by traditional banks?

Determinants of the Credit Cycle: A Flow Analysis of the Extensive Margin

BulkSort: System Design and Parallel Hardware Implementation Considerations

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