Essential Controls for SOC 2 Processing Integrity

To navigate these challenges and ensure robust processing integrity, here are some essential controls to consider:

Ensuring that every piece of data entering your systems is accurate, complete, and formatted correctly is crucial. This prevents incorrect, incomplete, or malicious data from corrupting your processes. Here are some input validation controls:

• Field Check: Verifies that characters in a field are of the proper type.
• Sign Check: Ensures data in a field has the appropriate sign (positive/negative).
• Limit Check: Tests numerical amounts against a fixed value.
• Range Check: Tests numerical amounts against lower and upper limits.
• Size Check: Ensures input data fits into the field.
• Completeness Check: Verifies that all required data is entered.
• Validity Check: Compares data from a transaction file to that of a master file to verify existence.
• Reasonableness Test: Checks the correctness of the logical relationship between two data items.
• Check Digit Verification: Recalculates check digits to verify data entry errors have not been made.
• Format Check: Ensures that data is in the correct format (e.g., dates should be in MM/DD/YYYY format).
• Consistency Check: Verifies that data values are consistent across related fields (e.g., the state and zip code match).
• Drop-down Lists: Use drop-down lists to limit the input options to predefined values.
• Captcha Verification: Prevents automated systems from submitting data to your system.
• Mandatory Field Check: Ensures that certain fields cannot be left blank.
• Import Validation: When importing data from external sources, ensure that the imported data meets the same validation criteria as manually entered data.
• Reconciliation Checks During Data Entry: Perform reconciliation checks to compare entered data with expected values or totals to detect discrepancies early in the data entry process.

These controls are your first line of defense, preventing bad data from entering your system and corrupting downstream processes.

Once data enters the system, it must be processed accurately, securely and timely. These controls ensure data remains trustworthy throughout its transformation:

• Data Integrity Checks (Hashing/Checksums): Use checksums or hash functions to verify that data remains unaltered during storage, transmission, or processing. Any discrepancies raise an immediate red flag.
• Change Management: Systems evolve, but changes must be controlled. A robust change management process ensures that every modification to your systems or processes is authorized, tested, and documented. This minimizes the risk of unintended consequences that could impact data integrity.
• Access Controls: Role-based access controls (RBAC) ensure that users have the minimum permissions necessary to perform their tasks. This limits the potential for unauthorized changes or accidental data manipulation.
• Logging and Monitoring: Logging and monitoring tools capture system activity, creating an audit trail that can be used to detect anomalies, investigate incidents, and prove compliance. This is your window into the health of your processes.
• Transaction Monitoring: Implementing transaction monitoring helps detect and rectify anomalies in real-time. By continuously tracking transactions, you can identify suspicious activities and address them promptly to prevent potential issues and ensure the accuracy and integrity of transaction data.
• Error Handling and Exception Management: No system is perfect. Error handling and exception management controls ensure that errors are gracefully handled, logged, and, where possible, corrected. This prevents errors from cascading into larger problems that could impact data integrity.
• Data Matching and Reconciliation: Regularly comparing data from different sources (e.g., purchase orders and invoices) helps identify discrepancies and potential errors.

The final stage of data processing involves presenting data accurately and securely. Key output controls include:

Data Verification

• File Labels: Ensure correct and more recent files are being updated, preventing outdated information from corrupting current data.
• Batch Total Recalculation: Compare calculated batch totals after processing to input totals to ensure that all transactions are processed correctly.
• Cross-Footing Balance Test: Ensure that figures add correctly both vertically and horizontally, verifying the accuracy of financial statements.

Data Protection

• Write-Protection Mechanisms: Prevent overwriting data that should not be changed, ensuring the integrity of critical information.
• Database Processing Integrity Procedures: Utilize database administrators, data dictionaries, and concurrent update controls to maintain the integrity of database operations.

Data Review and Reconciliation

• User Review of Output: Examine output carefully for reasonableness and completeness and ensure it is routed to the intended individual.
• Reconciliation Procedures: Compare balances in systems like inventory databases with general ledger accounts.
• External Data Reconciliation: Compare internal records with external data sources, such as payroll files with HR records.

In addition to using encryption to protect the confidentiality of information being transmitted, organizations need controls to minimize the risk of data transmission errors.

• Parity Checking: Ensures data integrity during transmission.
• Message Acknowledgment Techniques: Confirm that messages are received and processed correctly.

Customize Controls to Fit Your Organization: Tailor your controls to match your specific operational needs and context. This customization ensures that controls are both effective and efficient.

Leverage Automation: Utilize automated tools and technologies to enhance control effectiveness and reduce the risk of human error. Automation can streamline validation, reconciliation, and monitoring processes.

Continuous Training and Awareness: Regularly train your team on best practices and the importance of processing integrity. Continuous education helps maintain a strong control environment and ensures that everyone understands their role in achieving compliance.

As an auditor, I’ve seen organizations make several common mistakes that can undermine processing integrity:

• Over-Reliance on Manual Processes: Manual data entry and reconciliation are prone to human error. Automating these processes can significantly reduce the risk of errors.
• Insufficient Testing of Controls: Controls must be rigorously tested on a regular basis to ensure they are functioning as intended.
• Neglecting to Update Controls: As systems and processes evolve, controls must be updated to remain effective.

Regular Reviews: Continuously review and update your controls to adapt to changing environments and regulatory requirements. This proactive approach ensures that controls remain relevant and effective.

Proactive Monitoring: Implement proactive monitoring strategies to identify and address issues before they escalate. Use dashboards, alerts, and regular audits to maintain visibility into your control environment.

Achieving strong processing integrity is crucial for SOC 2 compliance and overall business success. By implementing effective controls and continuously improving them, your organization can ensure data accuracy, build trust with stakeholders, and support long-term growth.

Navigating the complexities of SOC 2 compliance can be challenging, but you don’t have to do it alone. Audit Peak’s experienced auditors can help streamline the process and ensure your organization meets all necessary requirements. Don’t leave your organization’s data integrity to chance. Contact Audit Peak today and embark on a journey toward a more secure, compliant, and resilient future.

WE WILL TAKE YOU TO THE PEAK.