Westpac Group’s wealth revenues will fall by around $300 million over the next two years, according to Morgan Stanley, following the bank’s restructure and exit from financial advice, via InvestorDaily.
Westpac is still retaining its private wealth, platforms, superannuation and insurance operations, with the new report estimating that wealth will account for less than 10 per cent of revenue in the bank’s consumer division and around 20 per cent in the business division after the restructure.
Morgan Stanley has forecast that Westpac’s wealth revenues will fall from more than $2 billion in FY18 to less than $1.7 billion in FY20, due largely to the non-recurrence of the $144 million Hastings exit fee and the loss of advice revenues.
The report downgraded the bank’s FY19 cash profit by around 2.5 per cent, due to exit and restructuring costs and a $100 million loss from wealth advice.
It has, however, upgraded its prediction for earnings per share by 0.5 per cent in FY20, citing the exit of the loss-making advice business.
Westpac had estimated it would save around $73 million by dropping the advice business and division.
“The exit from wealth advice is a logical response to the changing environment, but we expect ongoing challenges in the remaining wealth business,” Morgan Stanley noted.
Challenges will include the effect of the royal commission’s recommendations on the cross-selling of insurance to banking customers and reduced vertical integration benefits without advice, the report said.
The analysis also eyed other potential impacts such as pricing cuts in the platform market, new technology platform players winning an outsized share of flows and industry super funds growing in both personal and corporate super.
The retained businesses accounted for around 9 per cent of group revenue in FY18, excluding one-off items.
The analysis also forecast Westpac will have accumulated $775 million in customer refunds, remediation and litigation costs across banking and wealth management over FY19 and FY20.
Morgan Stanley has retained its rating of Westpac as underweight, saying it sees lower returns and rising risks in retail banking among other factors, with the analysis warning there could be risk of a further derating.
– This was the video that triggered this comment/reply:
https://www.youtube.com/watch?v=ne-xmAtFc6E
Mr. North,
– First of all I made a one-time donation (I love to watch your videos with Mr. Joe Wilkes.)
– I did additional research (think: GOOGLE maps, Wikipedia, etc.) and I found a few interesting things:
– The postcodes in the Sydney Eastern suburbs (e.g. 2034, 2032, 2024) seem to have each a (comparitively / very) small population (around 2,000 to 3,000 ??) whereas e.g. Liverpool (postcode 2170) has a (MUCH) much larger population. (30,000 ?? 40,000 ??).
– Let’s assume Liverpool (postcode: 2170) has say 20,000 households of which say 2,500 are in mortgage stress and let’s assume postcode 2032 (Kingsford, Daceyville) has only say 1000 households of which say 400 are in mortgage stress. Then it’s clear that in Liverpool (2170) the amount of households in mortgage stress is larger than in postcode 2032 (2,500 versus 400) but on a percentage basis postcode 2170 has less mortgage stress (25%) than postcode 2032 (40%).
Quote: “I have the percentage data – the problem is postcodes with small numbers of households and high stress levels”
– Yes, that’s precisely the point of my comment / question !
– Suggestion: Perhaps you can first “run the data” for mortgage stress on a percentage basis for a limited amount of postcodes. E.g. take first the postcodes for the Greater Sydney Metropolitan area (e.g. postcodes 20xx, 21xx, 22xx, 25xx and 27xx), run the data and see what shows up on the maps. – I also would expect that postcodes with a lot of farms in it also will have high mortgage stress. If that’s indeed the case then I would blame that on the recent drought conditions for that (increased ?) mortgage stress.
– From that point onwards you can decide whether or not you want to expand the modeling to e.g. all postcodes. Add one or more conditions to the mortgage stress model. E.g. minimum population of a postcode, loan-to-income ratios, property values etc. etc. I think the possibilities are only limited to the kind of data you have in your database.
– You also could run the “Negative Equity” model on a percentage basis. In that case I would expect that postcode 2036 (e.g. Chiffly) in the Sydney Eastern Suburbs to show up in dark blue as well.
– I am just throwing out a number of suggestions. It’s up to you to decide whether or not these suggestions would provide a new fresh perspective on the data you already have. I think it’s a matter of trial and error.
Thanks for your support. I will add in a percentage series when I run the March data, in a few days.
Mr. North,
– I have a comment/question not related to this post.
– You publish every now and then maps that show the postcodes with the highest mortgage stress. The metric is the amount of households in mortgage stress. Is it possible to calculate the mortage stress 1) e.g. as a percentage of total amount of households or 2) e.g. as a percentage of the total amount of households with a mortgage ? (I don’t know what kind of data is available or what % metric would be the most sensible.).
– The reason for this request/question is the following: When I look at e.g. Liverpool and Campbelltown then it’s clear that overall mortgage stress is (very) high but in e.g the Eastern Suburbs of Sydney mortgage stress is (surprisingly) low. It surprises me to see that in those Eastern Suburbs the stress is so low. Because in several TV interviews (Thank you YouTube) you have said that in places like Bondi and Gordon there are households that have large mortgages and large debts in general. Those households also should be in (some kind of) mortgage stress. I would expect that those suburbs/postcodes should have stood out on the map in (dark) blue colors as well.
– My suspicion is that the postcodes of e.g. Bondi and Gordon contain houses/dwellings that are situated on large plots of land and that as result of that, each of those postcodes have a (comparitively) small amount of houses/dwellings. The result is that then amount of households in mortgage stress is also (very) low. But if you would calculate the mortgage stress on a percentage basis then perhaps the postcodes for e.g. Gordon, Bondi and other Eastern Sydney suburbs would show up in dark blue on your maps as well.
– Do you think that (on a percentage basis) postcodes like Gordon and Bondi are having lots of mortgage stress as well ?
I have the percentage data – the problem is postcodes with small numbers of households and high stress levels. But I can map this for the major centres