Multi-year financial trend comparison, regression detection, and anomaly flagging for tax planning and audit risk assessment
Analyses multi-year financial data to identify trends, detect anomalies, and flag year-over-year changes that may indicate audit risk, missed deductions, or tax planning opportunities. Uses Xero historical transaction data and analysis results across multiple financial years.
Compare each financial year against the prior year:
| Metric | Calculation | Significance |
|---|---|---|
| Revenue Growth | (Current - Prior) / Prior × 100 | Loss utilisation, GST threshold |
| Expense Ratio | Total Expenses / Total Revenue | ATO benchmark comparison |
| Category Shift | Category % of Total (current vs prior) | Misclassification detection |
| Net Profit Margin | Net Profit / Revenue × 100 | Loss carry-forward trigger |
3-year rolling average smooths one-off anomalies:
| Use Case | Window | Alert If |
|---|---|---|
| Revenue trend | 3 years | Current deviates > 20% from average |
| Expense category | 3 years | Category deviates > 30% from average |
| Deduction claims | 3 years | Claims drop > 50% (may indicate missed deductions) |
| Contractor payments | 3 years | Sudden increase > 40% (contractor deeming risk) |
Flag values that fall outside expected bounds:
| Method | Description | Application |
|---|---|---|
| Z-score | Standard deviations from mean | Expense category outliers |
| IQR (Interquartile Range) | Values beyond Q1-1.5×IQR or Q3+1.5×IQR | Revenue spikes/dips |
| Percentage change threshold | YoY change exceeding configurable threshold | ATO audit risk triggers |
Identify recurring seasonal patterns in cash flow:
| Pattern | Detection | Use |
|---|---|---|
| Quarterly spikes | BAS periods showing consistent revenue peaks | Cash flow forecasting |
| Year-end clustering | Expenses concentrated in June | Prepayment detection (s 82KZM) |
| Holiday dips | Consistent revenue drops (Dec/Jan) | Working capital planning |
| Source | API Endpoint | Fields |
|---|---|---|
| Historical Transactions | /api/audit/cached-transactions | Amount, date, category, account |
| P&L Reports | /api/xero/reports?reportType=ProfitAndLoss | Income, expenses by category |
| Year Comparison | /api/audit/year-comparison | Pre-computed YoY metrics |
| Analysis Results | /api/audit/analysis-results | AI-classified findings per FY |
| Trends | /api/audit/trends | Pre-computed trend data |
| Trend | Criteria | Tax Implication |
|---|---|---|
| Stable Growth | Revenue growing 5-15% YoY consistently | Healthy; normal deduction patterns |
| Rapid Growth | Revenue growing > 30% YoY | May breach SG maximum contribution base; payroll tax threshold risk |
| Decline | Revenue falling > 10% YoY | Loss carry-forward planning; consider COT/SBT |
| Volatile | Revenue swinging > 25% YoY alternating | Cash flow risk; consider PAYG instalment variation |
| Flat | Revenue within ±5% YoY | Stable; check for inflation erosion of real deductions |
| Seasonal | Consistent intra-year pattern | Align BAS reporting with cash flow |
<trend_analysis>
<entity_id>org_456</entity_id>
<analysis_period>FY2020-21 to FY2024-25</analysis_period>
<revenue_trend>
<classification>stable_growth</classification>
<average_yoy_growth>8.3</average_yoy_growth>
<years>
<year fy="FY2020-21" revenue="850000" />
<year fy="FY2021-22" revenue="920000" yoy_change="8.2" />
<year fy="FY2022-23" revenue="1010000" yoy_change="9.8" />
<year fy="FY2023-24" revenue="1080000" yoy_change="6.9" />
<year fy="FY2024-25" revenue="1170000" yoy_change="8.3" />
</years>
</revenue_trend>
<anomalies>
<anomaly>
<category>Motor Vehicle Expenses</category>
<financial_year>FY2023-24</financial_year>
<value>45000</value>
<three_year_average>28000</three_year_average>
<deviation_percentage>60.7</deviation_percentage>
<z_score>2.4</z_score>
<risk>ATO benchmark deviation — motor vehicle expenses unusually high</risk>
<recommendation>Verify classification; may include personal use component</recommendation>
</anomaly>
</anomalies>
<sbt_evidence>
<expense_consistency_score>78</expense_consistency_score>
<top_categories_stable>true</top_categories_stable>
<business_type_consistent>true</business_type_consistent>
<sbt_assessment>likely_satisfied</sbt_assessment>
</sbt_evidence>
</trend_analysis>