Optimizing SEC Comment Letter Analysis with the CLARITY (Comment Letter Automated Retrieval and Intelligent Text Yielding) Process
Year: 2025
Type: article
Abstract: ABSTRACT The CLARITY (Comment Letter Automated Retrieval and Intelligent Text Yielding) process offers a novel, automated approach for retrieving, cleaning, and analyzing U.S. Securities and Exchange Commission (SEC) comment letters. Addressing the challenges of volume, inconsistency, and accessibility, CLARITY retrieves letters from the EDGAR database spanning 2005–2024. Python-based tools ensure standardized data cleaning, robust error handling, and efficient processing. Unlike subscription-based platforms such as Audit Analytics (Audit Analytics 2024) or Intelligize (Intelligize 2024), CLARITY is open access, reproducible, and scalable. The resulting CLARITY dataset supports advanced analyses—such as sentiment analysis and longitudinal studies of regulatory trends—thereby facilitating extensive research on SEC oversight, corporate compliance, and market transparency. This study demonstrates the value of the process through descriptive statistics, methodological transparency, and its potential for integration with external financial datasets, underscoring its contribution to regulatory research and financial reporting quality. Data Availability: Data are available from the authors upon request. JEL Classifications: G14; G18; M41; M48.
Source: Journal of Information Systems
Authors: David H. Olsen, Amira Hassan
Institution: Utah Tech University
Language: English
Subfield: General Social Sciences
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4414155441