Household Survey – Page 32 – Digital Finance Analytics (DFA) Blog

Major banks increase ‘share of wallet’

New research findings from Roy Morgan found that over the last decade, the big four banks have all increased their share of their customers’ dollars (‘share of wallet’). This metric is the most objective measure of customer loyalty because it is based on their financial behaviour rather than the more subjective measures that lead to this outcome.

These are the latest findings from Roy Morgan’s Single Source survey of over 50,000 consumers conducted over the 12 months to May 2017.

Big potential remains to increase business from existing customers

The following chart shows that the only two major banks obtaining more than 60% of their customers’ business are Bank SA (60.9% share of wallet) and CBA (60.4%). Both of these banks have shown improvement over the last decade, with Bank SA up 12.4% points and CBA up 7.4% points.

All of the big four banks have shown improvement in ‘share of wallet’ over the last decade, which correlates with their improvement in satisfaction over this period. Apart from the CBA (up 7.4% points), the ANZ improved by 5.2% points (to 52.4%), the NAB was up 4.0% points (to 55.3%) and Westpac improved by 1.3% points (to 52.5%).

’Share of Wallet’ depends mainly on the performance in the top quintile

The top quintile (or 20%) of banking customers, based on the value of all their banking products, accounts for nearly three quarters (74.2%) of the total value of banking products and as a result it becomes critical to measure performance in this key segment.

The best performer for ‘share of wallet’ in the top quintile is Bank SA (60.3%), followed by the CBA (58.1%).

All of the banks shown in this chart have a higher ‘share of wallet’ among their lower value quintile customers, largely as a result of their having less overall value in banking products, making it difficult to split their banking across different institutions. Bank customers in the highest value quintile on the other hand, with a minimum value in banking products of $466,000, generally have considerable scope to split their banking,

Norman Morris, Industry Communications Director, Roy Morgan Research says:

“This research has shown that in order to maximise the value to banks obtained from each of their customers, it is necessary to increase and track ‘share of wallet’, particularly in the higher value segment. The advantage of using ‘share of wallet’ is that it is the best behavioural metric for measuring brand loyalty.

“Results in this survey show that it generally takes time to improve ‘share of wallet’, as evidenced by the fact that the major banks have taken a decade to show significant improvement. There is a strong indication that the major improvement in customer satisfaction with banks over this period is likely to have contributed to this positive trend in ‘share of wallet’. The challenge now is to maintain this momentum by improving the proportion of ‘very satisfied’ customers in the high value (top quintile) segment, as they are not only likely to then become strong advocates for their bank but have the most potential to increase their ‘share of wallet’.

“There remains considerable opportunity for banks to increase business with their existing customers as they are currently only capturing around half of what is possible”.

Mortgage Stress Grinds Higher In June

Digital Finance Analytics has released mortgage stress and default modelling for Australian mortgage borrowers, to end June 2017. Across the nation, more than 810,000 households are estimated to be now in mortgage stress (last month 794,000) with 29,000 of these in severe stress. This equates to 25.4% of households, up from 24.8% last month. We also estimate that nearly 55,000 households risk default in the next 12 months.

The main drivers are rising mortgage rates and living costs whilst real incomes continue to fall and underemployment is on the rise. This is a deadly combination and is touching households across the country, not just in the mortgage belts.

This analysis uses our 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 June 2017.

We analyse household cash flow based on real incomes, outgoings and mortgage repayments. Households are “stressed” when income does not cover ongoing costs, rather than identifying a set proportion of income, (such as 30%) going on the mortgage.

Those 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.

Martin North, Principal of Digital Finance Analytics said “flat incomes and underemployment mean rising costs are not being managed by many, and when added to rising mortgage rates, household budgets are really under pressure. Those with larger mortgages are more impacted by rate rises”.

“The latest housing debt to income ratio is at a record 190.4[1] so households will remain under pressure. Stressed households are less likely to spend at the shops, which acts as a drag anchor on future growth. The number of households impacted are economically significant, especially as household debt continues to climb to new record levels.”

[1] *RBA E2 Household Finances – Selected Ratios March 2016

Big four bank satisfaction well behind mutuals

From Investor Daily.

Smaller banks continue to be significantly ahead of the big four banks when it comes to overall customer satisfaction, according to Roy Morgan.

Australia’s four largest banks are “well behind the smaller banks” when it comes to the proportion of ‘very satisfied’ customers, the company said.

Teachers Mutual Bank and Greater Bank had the highest number of ‘very satisfied’ customers, Roy Morgan found, with 62.3 per cent of Teachers Mutual Bank customers and 58.8 per cent of Greater Bank customers falling in to this category.

The big four banks on the other hand have only around a third of their customers feeling ‘very satisfied’, led by the Commonwealth Bank with 33.5 per cent of customers selecting this option.

Overall, general satisfaction with the big four banks has increased marginally in the six months to May 2017, climbing up 0.1 of a percentage point to 80.2 per cent, which Roy Morgan attributed to improvement in satisfaction among the banks’ home loan customers.

“Satisfaction among home-loan customers of the big four continues to be below that of their other customers, but over the last year they have narrowed the gap marginally,” the company said.

“The small overall improvement in satisfaction from last month was the result of minor gains among both home-loan and non-home loan customers.”

Lower interest rates reducing mortgage stress – Roy Morgan

New results from Roy Morgan’s mortgage stress data show that in the three months to April 2017, 16.8% or 666,000 mortgage holders can be considered to be ‘at risk’ or facing some degree of stress over their repayments. This compares favourably with 18.4% or 744,000
mortgage holders 12 months ago.

These are the latest findings from Roy Morgan’s Single Source survey of 50,000+ people pa, which includes more than 10,000 owner occupied mortgage holders.

Mortgage stress is much higher among the lower income groups (Under $60kpa) where it currently reaches 85.3% for those considered ‘at risk’ and 65% for ‘extremely at risk’.

Mortgage stress is based on the ability of home borrowers to meet the repayment guidelines currently provided by the major banks. The level of mortgage holders being currently considered ‘at risk’ is based on their ability to meet repayments on the original amount borrowed. This is currently 16.8%, which is well below the average over the last decade.

DFA comments – interesting findings, presumably looking at owner occupied mortgages? The basis of assessment is different. Also, current repayment guidelines are in our opinion too generous, given current income growth. We think underwriting standards need to be tighter, judging by overall household cash flow, which have been tracking in our mortgage stress analysis.

Finally, whether 666,000 households from Roy Morgan, or 794,000 from DFA, are both big numbers!

Mortgage Growth In Adelaide and Hobart

We finish our series on mortgage growth by looking at data from Adelaide and Hobart and plotting the relative change in volumes of loans between 2015 and 2017, by post code, drawing data from our core market models, and geo-mapping the results.

Here is Adelaide.

Here is Hobart.

The yellow shades show the areas with the largest growth in the number of mortgages, the red shades show a relative fall in volumes. You can click on the map to view full screen. This is a picture of mortgage counts, not value, we may look at this later.

Compare these pictures with those for Sydney, Melbourne, Brisbane and Perth and we see just how different these markets are!

Of course this is just one of the many potential views available from the 140+ fields which are contained in our Core Market Model.

What’s The Correlation Between Mortgage Stress And Loan Non Performance?

Last night DFA was involved in a flurry of tweets about the relationship between our rolling mortgage stress data and mortgage non-performance over time. The core questions revolved around our method of assessing mortgage stress, and the strength, or otherwise of the correlation.

We were also asked about our expectations as to when non-performing mortgage loans will more above 1% of portfolio, given the uptick in stress we are seeing at the moment.

Our May 2017 data showed that across the nation, more than 794,000 households are now in mortgage stress (last month 767,000) with 30,000 of these in severe stress. This equates to 24.8% of households, up from 23.4% last month. We also estimate that nearly 55,000 households risk default in the next 12 months.

However, it got too late last night to try and explain our analysis in 140 characters. So here is more detail on our approach to mortgage stress, and importantly a chart which slows the relationship between stress data and mortgage non-performance.

Our analysis uses our 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 May 2017.

We also make an estimate of predicated 30 day defaults in the year ahead (PD30) based on our stress data, and an economic overlay including expected mortgage rates, inflation, income growth and underemployment, at a post code level.

Here is the mapping between stress and non-performance of loans.

The red line is the data from the regulators on non-performing mortgage loans. In 2016 it sat around 0.7%. There was a peak following the 2007/8 financial crisis, after which interest rates and mortgage rates came down.

We show three additional lines on the chart. The first is our severe stress measure, the blue line, which is higher than the default rate, but follows the non-performance line quite well. The second line is the PD30 estimate, our prediction at the time of the expected level of default, in the year ahead. This is shown by the dotted yellow line, and tends to lead the actual level of defaults. Again there is a reasonable correlation.

The final line shows the mild stress household data. This is plotted on the right hand scale, and has a lower level of correlation, but nevertheless a reasonable level of shaping. After the GFC, rates cuts, plus the cash splash, helped households get out of trouble by in large, but since then the size of mortgages have grown, income in real terms is falling, living cost are rising as is underemployment. Plus mortgage rates have been rising, and the net impact in the past six months, with the RBA cash rate cut on one hand, and out of cycle rises by the banks on the other, is that mortgage repayments are higher today, than they were, for both owner occupied borrowers and investors. Interest only investors are the hardest hit.

Households are responding by cutting back on their spending, seeking to refinance and restructure their loans, and generally hunkering down. All not good for broader economic growth!

So, given the severe stress, mild stress and our PD30 estimates are all currently rising, we expect non-performing loans to rise above 1% of portfolio during 2018. Unless the RBA cuts, and the mortgage rates follow.

Mortgage Growth In Greater Perth

We continue our series on mortgage growth plotting the relative change in volumes of loans between 2015 and 2017, by post code, drawing data from our core market models, and geo-mapping the results.

Here is the Greater Perth picture.

Of course this is just one of the many potential views available from the 140+ fields which are contained in our Core Market Model.

Next time we will look at Adelaide and Hobart.

Mortgage Growth In Greater Brisbane

We continue our series on mortgage growth plotting the relative change in volumes of loans between 2015 and 2017, by post code, drawing data from our core market models, and geo-mapping the results.

Here is the Greater Brisbane picture.

Of course this is just one of the many potential views available from the 140+ fields which are contained in our Core Market Model.

Next time we will look at Perth.

Tracking Mortgage Growth In Great Melbourne

We continue our series on mortgage growth, plotting the relative change in volumes of loans between 2015 and 2017, by post code, drawing data from our core market models, and geo-mapping the results.

Here is the Greater Melbourne picture.

Of course this is just one of the many potential views available from the 140+ fields which are contained in our Core Market Model.

Next time we will look at Brisbane.

Where Is The Mortgage Growth In Greater Sydney?

One of the measures contained in the Digital Finance Analytics household surveys is the number of households with a mortgage in each post code across the country. By comparing our data from 2015, with 2017 we can spot some interesting growth trends, especially when we geo-map the data. Today we begin with Greater Sydney.

The yellow shades show the areas with the largest growth in the number of mortgages, the red shades show a relative fall in volumes. We see significant growth in western Sydney, where there has been significant residential development over this period. You can click on the map to view full screen. This is a picture of mortgage counts, not value, we may look at this later.

Of course this is just one of the many potential views available from the 140+ fields which are contained in our Core Market Model.

Next time we will look at Melbourne.