historical-trend-analysis

name	historical-trend-analysis
description	Multi-year financial trend comparison, regression detection, and anomaly flagging for tax planning and audit risk assessment

Historical Trend Analysis Skill

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.

When to Use

• Comparing income/expense patterns across 3-5 financial years for trend detection
• Identifying anomalous expense categories that deviate from historical norms
• Detecting revenue growth/decline trends for loss carry-forward planning
• Flagging sudden changes in expense ratios that may trigger ATO benchmarking
• Supporting the Similar Business Test (SBT) with historical consistency evidence
• Assessing amendment worthiness by comparing identified opportunities across FYs
• Providing context for Division 7A compliance (loan balance trends)
• Cash flow forecasting based on historical seasonal patterns

Analysis Methods

1. Year-over-Year (YoY) Comparison

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

2. Moving Average

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)

3. Anomaly Detection

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

4. Seasonal Pattern Analysis

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

Data Sources

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 Classification

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

Output Format

<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>

Best Practices

• Minimum 3 years of data required for meaningful trend analysis
• Adjust for inflation when comparing dollar amounts across years (use CPI)
• Exclude one-off items from trend calculations (e.g., asset sales, insurance payouts)
• Normalise for business changes — merger/acquisition/restructure events invalidate YoY comparison
• ATO benchmarks are descriptive — deviations are informational, not normative (AD-6)
• Use Xero account codes for consistent category mapping across years
• Financial year convention: Always use FY format (e.g., FY2024-25), never calendar year