Mortgage Stress And Probability Of Default Is Rising

We have just finished the December update of our mortgage stress and probability of default modelling for the Australian mortgage market. Our model has been updated to take account of the latest employment, wage, interest rate and growth data, and we look are the current distribution of mortgage stress (can households settle their mortgage repayments, … Continue reading “Mortgage Stress And Probability Of Default Is Rising”

Loan Probability Of Default By Post Code

DFA’s coverage in the SMH today relating to the probability of default by post code has stimulated significant interest. As part of our household surveys, we capture data on mortgage stress, and when we overlay industry employment data and loan portfolio default data, we can derive a relative risk of default score for each household … Continue reading “Loan Probability Of Default By Post Code”

Mortgage Stress And Default Probability Rise Again In April

Digital Finance Analytics has released new mortgage stress and default modelling for Australian mortgage borrowers, to end April 2017.  Across the nation, more than 767,000 households are now in mortgage stress (last month 669,000) with 32,000 of these in severe stress. This equates to 23.4% of households, up from 21.8% last month. We also estimate … Continue reading “Mortgage Stress And Default Probability Rise Again In April”

3D Mapping Mortgage Default Probability

Here is a map of Australia, showing the relative probability of default by post code, looking ahead over the next 12-18 months.  This is a 3d visualisation of the relative default risk, the higher the relief, the higher the risk. It nicely shows the potential issues across WA, as the mining boom subsides, some the … Continue reading “3D Mapping Mortgage Default Probability”

Probability Of Mortgage Default Rises

We have re-run our Probability of Mortgage Default modelling, based on our most recent household surveys. This modelling takes the basic household finance data in our survey, and models the impact of economic changes, inflation, income growth, and other factors, to estimate the probability of 30+ day mortgage default at a post code level. As … Continue reading “Probability Of Mortgage Default Rises”

Probability of Mortgage Default – Latest Estimates in 3D

As we finish our series on deep analysis of mortgages by LVR, DSR and LTI, we have incorporated the latest household survey data into our probability of mortgage default modelling by post code.  The national average is 1.3%, but it rises to more than 3% in some places. We take the DSR, LTI and LVR … Continue reading “Probability of Mortgage Default – Latest Estimates in 3D”

The Latest Top 10 Post Codes In Risk Of Mortgage Default

Today using our latest mortgage stress and probability of default data, we explore the top ten highest risk post codes across the country. Specifically, we look at where we expect the largest number of mortgage defaults to occur over the next few months. We explore the latest mortgage stress and default modelling, using data to … Continue reading “The Latest Top 10 Post Codes In Risk Of Mortgage Default”

Mortgage Default Heat Map Predictions

In our last post for 2016 we have geo-mapped the probability of mortgage default by post code across the main urban centres through 2017. You can read about our approach to the analysis here. We start with Sydney, which is looking pretty comfortable. Melbourne is also looking reasonable, though with a few hot spots. Brisbane … Continue reading “Mortgage Default Heat Map Predictions”

New DFA Video Blog – Household Mortgage Stress and Defaults

Using data from our household surveys in this new video blog we discuss the findings from our latest modelling. More than 22% of households are currently in mortgage stress, and 1.9% of households are likely to default. Both are likely to rise next year.  

A Segmented View Of Mortgage Stress and Default

As we continue our series on mortgage stress, using the latest data from our surveys, we look at how stress aligns with our core household and property owning segments. To set the context for this, here are a couple of charts showing the mortgage distribution by income and age bands. The majority of mortgages are … Continue reading “A Segmented View Of Mortgage Stress and Default”