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Analysis of mortgage prices in Sydney suburbs to determine the best location to buy in desire to the clients needs.

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Analysis of mortgage stress by geography in Australia

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Our project is to analyse mortagage stress by geography in NSW, Australia. Mortgage stress defined as an excessive portion of income dedicated to mortgage payments 


Background

Interest rates have risen rapidly during 2022 and further rate rised are expected in 2023. This is resulting in significant inreases in mortgage repayments. Where a household is in 'mortgage stress' where it has an excessive portion of its income allocated to mortgage payments.

Fin Tech use of mortgage stress data

Many online/digital home loan providers have emerged (e.g. Ubank, Unloan, etc) which would be interested in geographical areas of high mortgage stress.

Questions asked

  1. Characteristics of mortgage stress for NSW in aggregate
  2. NSW regions with highest levels of mortgage stress

  3. Drivers for mortgage stress


Visualisations

NSW total graphs

NSW_mortgage_no_bar_plot

NSW_mortgage_%_plot

%NSW_mortgage

Data Sources used

  1. Australia Bureau of Statstics (ABS)
  2. Reserve bank of Australia (RBA)
  3. Folium for geospatial
  4. Domain.com.au for analysis

Summary of findings

Highest levels of mortgage stress are in Sydney and within Sydney the highest levels are in the Northern Beaches/Baulkham Hills and Hawksbury.

Data challenges/Postmortem

  1. ABS website has many different ways to extract data which is confusing
  2. ABS API difficult to use
  3. Some APIs have a cost or take time to set-up
  4. Data gaps exist in lower level ABS geographic data

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Analysis of mortgage prices in Sydney suburbs to determine the best location to buy in desire to the clients needs.

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