Households Under The Mortgage Stress Gun In December

Digital Finance Analytics has released the December mortgage stress and default analysis update. Across Australia, more than 921,000 households are estimated to be now in mortgage stress (last month 913,000). This equates to 29.7% of households. In addition, more than 24,000 of these in severe stress, up 3,000 from last month. We estimate that more than 52,000 households risk 30-day default in the next 12 months, similar to last month. We expect bank portfolio losses to be around 2.8 basis points, though with losses in WA rising to 4.9 basis points. Households in NSW are showing the most significant rise in stress, thanks to larger mortgages relative to income, while income growth is slow.

Martin North, Principal of Digital Finance Analytics said “the number of households impacted are economically significant, especially as household debt continues to climb to new record levels. Mortgage lending is still growing at three times income. This is not sustainable”. The latest household debt to income ratio is now at a record 199.7.[1]

Risks in the system continue to rise, and while recent strengthening of lending standards will help protect new borrowers, there are many households currently holding loans which would not now be approved. This is a significant sleeping problem and the risks in the system are higher than many recognise.

Our analysis uses the DFA core market model which combines information from our 52,000 household surveys, public data from the RBA, ABS and APRA; and private data from lenders and aggregators. The data is current to end December 2017. We analyse household cash flow based on real incomes, outgoings and mortgage repayments, rather than using an arbitrary 30% of income.

Households are defined as “stressed” when net income (or cash flow) does not cover ongoing costs. Households in mild stress have little leeway in their cash flows, whereas those in severe stress are unable to meet repayments from current income. In both cases, households manage this deficit by cutting back on spending, putting more on credit cards and seeking to refinance, restructure or sell their home.  Those in severe stress are more likely to be seeking hardship assistance and are often forced to sell.

The forces which are lifting mortgage stress levels remain largely the same. In cash flow terms, we see households having to cope with rising living costs whilst real incomes continue to fall and underemployment remains high. Households have larger mortgages, thanks to the strong rise in home prices, especially in the main eastern state centres, but now there are signs prices are slipping. While mortgage rates remain quite low for owner occupied borrowers, those with interest only loans or investment loans have seen significant rises.  We expect some upward pressure on real mortgage rates in the next year as international funding pressures mount, a potential for local rate rises and margin pressure on the banks.

Probability of default extends our mortgage stress analysis by overlaying economic indicators such as employment, future wage growth and cpi changes.  Our Core Market Model also examines the potential of portfolio risk of loss in basis point and value terms. Losses are likely to be higher among more affluent households.

Stress by The Numbers.

Regional analysis shows that NSW has 258,572 households in stress (251,576 last month), VIC 254,485 (253,248 last month), QLD 156,097 (157,019 last month) and WA 121,934 (123,849 last month). The probability of default rose, with around 9,800 in WA, around 9,500 in QLD, 13,000 in VIC and 14,000 in NSW.

The largest financial losses relating to bank write-offs reside in NSW ($1.3 billion) from Owner Occupied borrowers) and VIC ($957 million) from Owner Occupied Borrowers, which equates to 2.1 and 2.7 basis points respectively. Losses are likely to be highest in WA at 4.9 basis points, which equates to $682 million from Owner Occupied borrowers.

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[1] RBA E2 Household Finances – Selected Ratios September 2017

Author: Martin North

Martin North is the Principal of Digital Finance Analytics

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