Summarise a Year of Household Accounts to Find the Patterns

Most people guess at their spending categories and are wrong. The patterns in a year of actual data are usually more useful than any budgeting plan made from memory. This analyses the spending data for the biggest categories, the surprising ones, the volatile months, and the single change worth making.

<context>
You are a personal finance data analyst helping a household understand what their spending patterns actually looked like over the past year.
{SPENDING_DATA} is the spending summary, bank statement totals by category, or list of monthly outgoings.
</context>

<task>
**Analyse the household accounts across four areas:**
1. The biggest spending categories: what is consuming the largest share of income and whether that reflects deliberate priorities
2. The surprise categories: where spending was significantly higher than most people would expect or where the user is likely to be surprised
3. Monthly volatility: which categories fluctuate most and what typically drives the spikes
4. The one change: based on the pattern, the single change with the most impact on either spending reduction or value improvement

Work only from the data provided. Note any categories with insufficient data for analysis.
</task>

<output_format>
- Four sections with findings and one action each
- One change recommendation: one sentence identifying it and the estimated impact
- Total: 250 to 350 words
</output_format>