OnCorps AI Analysis of Errors in Financial Reporting and TSR Compliance

(Read the full report analysis here)

Financial reporting is a cornerstone of investment management, ensuring transparency and accountability. However, reports are often laden with errors and complexities.

Our recent analysis has uncovered significant error rates in financial reporting. With the Securities and Exchange Commission (SEC) mandating Tailored Shareholder Reports (TSRs), it's crucial to understand these changes and prepare accordingly. This blog delves into our findings and how our Pre-trained Financial Reporting Solution can help your firm transition smoothly.

The Culprits Behind Financial Reporting Errors

In a study of over 450 funds, managing $5 trillion in assets, we found that 72% of errors in Annual and Semi-Annual Reports occur within the Notes to Financial Statements and the Schedule of Investments. These errors often stem from inconsistencies and the sheer volume of data handled. The primary areas of concern include:

Schedule of Investments

Nearly half (46.5%) of errors are found here due to the extensive details required.

Financial Statements

Over a quarter (25.8%) of errors occur in this critical section.

Notes to Financial Statements

This section accounts for 14.9% of errors, highlighting challenges in maintaining data accuracy.

So, what's causing these inconsistencies? Our analysis reveals four primary culprits:

• Errors that can be identified due to lack of internal consistency
• Errors that can be identified because the values violate policies
• Errors that can be identified because they drive anomalous movements year-over-year
• Errors that can be identified by inconsistencies with sources of truth

Understanding why errors occur is an important input to designing your TSR review approach. Whether using a manual review approach or a comprehensive review technology, ensuring accurate reporting requires targeted reviews of the reporting process’s most error prone components.

An AI Driven Approach to TSR Accuracy

At OnCorps, we leverage machine learning and automation to conduct these checks swiftly and accurately. One of the most challenging aspects of automating reviews for financial reporting of all kinds is the nature of reviewing PDF drafts. Artificial Intelligence (AI) approaches have advanced in recent years, from optical AI techniques to algorithms to better identify and classify data. Using these techniques enables OnCorps our system to read, ingest, and organize data to rapidly run dozens of important checks across a document.

Our Pre-trained Financial Reporting Solution:

• Cuts review time by 92%.
• Removes a review round.

Read the full report on the 5 Principles of Accurate Tailored Shareholder Reports to learn more.