Key takeaways
- Finder’s positivity index decreased by 12.7% in September 2025 to 110 points.
- The decrease in the index was mainly due to general economic and savings sentiment.
The index fell mainly due to weaker economic and savings confidence. Optimism about affording a home saw the largest drop at 14%, while sentiment about salary increases declined by 8%. Positive views on household debt fell by 4%, and confidence in job stability dropped by 2%. In the savings category, average cash savings were down 11%, and monthly savings fell by 10%.
In the housing category, the share of people who felt it was a good time to buy property fell by 7%, while the number of those struggling with mortgage repayments rose by 2%.
The share of Australians expecting a recession in the next 12 months rose by 17%. Meanwhile, the number of people who said they couldn't manage their finances without a credit card increased by 4%.
What is the Finder Positivity Index?
Finder's Positivity Index is a monthly measure of Australian consumer sentiment, and a useful way to gauge the financial health of Australian consumers at a glance. It provides a snapshot of how Australians feel about their current capacity to earn a decent income; to spend enough to maintain their standard of living; and to save for the future. The index also provides an insight into where the economy as a whole is going in the short term.
The index is collated from over 50,000 responses to Finder's Consumer Sentiment Tracker since May 2019. It is produced by analysing data collected across five broad categories:
- General economic sentiment (65%)
- Housing (15%)
- Savings (10%)
- Credit card usage (5%)
- Shopping behaviour (5%)
Each category is measured with survey responses on how Australians feel about a recession; their wages; wellbeing; their ability to pay for housing; their living costs; use of buy now pay later; and how much they save per month. The final index is a synthesis of these consumer perspectives into a single index to express current and near-term consumer sentiment. This synthesis involves creating separate indexes for each data point with a baseline of 50, then calculating a weighted sum as a final index.
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