AI Analysis: Credit liabilities of households

Executive Summary

Canadian household credit liabilities have grown dramatically over 36 years, reaching a peak of $3.24 trillion CAD in February 2026, with mortgage-related categories dominating the landscape. The data is highly right-skewed, with a small number of very large categories — particularly total credit and residential mortgages — pulling the mean ($197,622M) far above the median ($23,836M). Strong positive correlations across all credit categories suggest that common macroeconomic forces such as interest rates, income growth, and housing market conditions drive household debt broadly and simultaneously.

Key Findings

• Canadian household credit liabilities reached an all-time high of $3,242,052 million CAD ($3.24 trillion) in February 2026, reflecting sustained long-term growth across all major credit categories since 1990.
• The dataset covers 434 monthly periods across 24 distinct credit categories, with values ranging from $0 to over $3.24 trillion, producing a heavily right-skewed distribution where the mean ($197,622M) is more than eight times the median ($23,836M).
• Mortgage-related categories — including 'Mortgage loans' and 'Residential mortgages' — consistently rank among the top credit liability segments, underscoring the central role of housing debt in Canadian household finances.
• Nearly all credit liability categories exhibit strong positive correlations with one another, indicating that household debt across segments such as auto loans, credit cards, lines of credit, and mortgages tends to expand and contract together.
• A dramatic outlier was detected in the 'Government' category, which recorded a 609.5% year-over-year spike in September 2001 — more than 3 standard deviations above the mean — suggesting a structural reclassification event rather than organic credit growth.
• The middle 50% of all recorded values spans a wide range of over $166,000M CAD (25th percentile: $3,636M; 75th percentile: $169,988M), reflecting the vast scale differences between granular subcategories and broad aggregate totals.
• Outside of the 2001 Government anomaly, the dataset shows no other extreme statistical outliers, with all major credit categories displaying relatively smooth, consistent long-term upward growth trends from 1990 through 2026.