What is Proxy Readability Score?
A proxy readability score is an NLP-based composite measuring how easily a proxy statement (DEF 14A or business-combination proxy) can be understood by retail shareholders, institutional analysts, and proxy-advisory algorithms. It blends Fog index, sentence complexity, and key-disclosure findability.
Why Proxy Readability Score matters
Proxy materials drive votes that move billions in SPAC trust value, executive compensation, and M&A consideration. ISS and Glass Lewis run automated screens against proxy language before issuing recommendations. Retail shareholders abandon proxies they cannot parse on first reading, biasing votes toward broker-default. Higher proxy readability means more informed votes and lower variance in voting outcomes — both of which align with sponsor and management interests in most situations.
How AxonIR measures it
AxonIR scores proxies before filing using the same NLP engine applied to 10-Ks and 8-Ks, with a proxy-specific weighting that emphasizes business-combination terms (for SPAC proxies) and compensation-discussion narrative (for annual proxies). The score includes a section-level breakdown so issuers can see exactly which page ranges are dragging the composite. AxonIR's proxy reviews typically surface 6–12 specific edits that, if applied, raise the composite by 8–15 points.
For SPAC proxies, the highest-impact section is the business-combination-summary block (typically pages 1–10 of the proxy). Readability scores in this section correlate strongly with retail-vote turnout and inversely with redemption rates.
For annual proxies, the highest-impact section is the CD&A (compensation discussion and analysis). Excessive Fog index here triggers ISS pay-for-performance algorithm flags even when the underlying compensation alignment is sound.
See your company's proxy readability score score
Free for any NYSE/NASDAQ ticker. 5-business-day delivery.
Get Free Algo Score