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Payday loans -- blessing or growth suppressor? Machine Learning Analysis

Author

Listed:
  • Rohith Mahadevan
  • Sam Richard
  • Kishore Harshan Kumar
  • Jeevitha Murugan
  • Santhosh Kannan
  • Saaisri
  • Tarun
  • Raja CSP Raman

Abstract

The upsurge of real estate involves a variety of factors that have got influenced by many domains. Indeed, the unrecognized sector that would affect the economy for which regulatory proposals are being drafted to keep this in control is the payday loans. This research paper revolves around the impact of payday loans in the real estate market. The research paper draws a first-hand experience of obtaining the index for the concentration of real estate in an area of reference by virtue of payday loans in Toronto, Ontario in particular, which sets out an ideology to create, evaluate and demonstrate the scenario through research analysis. The purpose of this indexing via payday loans is the basic - debt: income ratio which states that when the income of the person bound to pay the interest of payday loans increases, his debt goes down marginally which hence infers that the person invests in fixed assets like real estate which hikes up its growth.

Suggested Citation

  • Rohith Mahadevan & Sam Richard & Kishore Harshan Kumar & Jeevitha Murugan & Santhosh Kannan & Saaisri & Tarun & Raja CSP Raman, 2022. "Payday loans -- blessing or growth suppressor? Machine Learning Analysis," Papers 2205.15320, arXiv.org.
    • Handle: RePEc:arx:papers:2205.15320
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    File URL: http://arxiv.org/pdf/2205.15320
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    References listed on IDEAS

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    1. Giacomo De Giorgi & Matthew Harding & Gabriel Vasconcelos, 2021. "Predicting Mortality from Credit Reports," Papers 2111.03662, arXiv.org.
    2. Stephen S. Poloz, "undated". "The Causes of Unemployment in Canada: A Review of the Evidence," Staff Working Papers 94-11, Bank of Canada.
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