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