Key takeaways
- Finder’s positivity index decreased by 6.7% in February 2025 to 110.92 points.
- The drop in the index was mainly due to a decline in savings and the average amount saved during the month.
The index decline was primarily influenced by the savings category, with the average cash savings decreasing by 19% and the average amount saved during the month decreased by 13%.
In the Housing category, mortgage stress decreased by 5%, while rent payment stress rose by 7%.
In Australia's economic outlook, the number of people expecting a pay rise in the next 12 months has fallen by 14%, while those anticipating a recession has dropped by 11%. Confidence in the near future has also declined, with positivity about salary and job security down 4%, optimism about affording a home down 7%, and sentiment around monthly living costs down 2%.
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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