A Replicable Six-Dimension Rubric for Assessing IFRS 17 Disclosure Quality and Comparability in Life Insurers

Abstract

IFRS 17 has reshaped life insurers’ reporting by replacing IFRS 4 with a stock–flow disclosure package in which users must interpret judgement-intensive constructs (CSM, risk adjustment, insurance finance effects) through audited statements and notes. Early implementation shows wide heterogeneity, yet archival research lacks a transparent issuer–year metric to test learning, determinants, and market relevance. We develop an IFRS-17-native, replicable six-dimension rubric scoring evidence strength (0–2 each) for: (D1) reconciliations/roll-forwards, (D2) actuarial assumptions, (D3) IFRS-17-specific sensitivities, (D4) method/transition transparency, (D5) audit traceability via key audit matters, and (D6) presentation/navigability. Scores aggregate to FLOW (D1–D3; 0–6), STOCK (D4–D6; 0–6), and TOTAL (0–12). Using audited annual reports for 33 life-insurance groups over FY2023–FY2024 (balanced panel, N=66), reliability is high (ω=0.893; α=0.883) and inter-coder agreement is assessed with weighted Cohen’s κ on a double-coded subsample. Disclosure quality improves in year 2 (TOTAL: 9.924→10.740; paired t(32)=4.967; Wilcoxon z=3.724; p<.001). In pooled OLS determinants, leverage is the only significant correlate (B=15.385; p<.001). Market tests are proxy-dependent: controlling for size, STOCK is associated with tighter bid–ask spreads (B=−0.023; p=.007) while FLOW loads positively (B=+0.016; p=.025); TOTAL is positively related to log Amihud illiquidity (B=0.245; p=.019) and remains detectable with country random intercepts. Implied cost-of-equity models are not significant. The rubric provides a reusable publicly auditable measurement layer for cumulative IFRS 17 disclosure research and for practitioner benchmarking.