8.3 Internal controls and data quality assurance

Internal controls and data quality assurance are crucial for reliable sustainability reporting. Companies need robust systems to ensure accurate, complete data. This includes preventive, detective, and corrective controls, as well as regular monitoring and assessment.

Data validation, reconciliation, and other quality assurance techniques help maintain data integrity. Error correction processes and internal audits further strengthen sustainability data management. These elements work together to support trustworthy corporate sustainability reporting.

Internal Controls for Sustainability Data

Designing Effective Internal Controls

Top images from around the web for Designing Effective Internal Controls

• 

  Effective Internal Controls by @EricPesik View original

  Is this image relevant?

• 

  Finance Policies And Procedures Manual View original

  Is this image relevant?

• 

  The Control Process | Principles of Management View original

  Is this image relevant?

• 

  Effective Internal Controls by @EricPesik View original

  Is this image relevant?

• 

  Finance Policies And Procedures Manual View original

  Is this image relevant?

1 of 3

Top images from around the web for Designing Effective Internal Controls

• 

  Effective Internal Controls by @EricPesik View original

  Is this image relevant?

• 

  Finance Policies And Procedures Manual View original

  Is this image relevant?

• 

  The Control Process | Principles of Management View original

  Is this image relevant?

• 

  Effective Internal Controls by @EricPesik View original

  Is this image relevant?

• 

  Finance Policies And Procedures Manual View original

  Is this image relevant?

1 of 3

• Internal controls are policies and procedures implemented to provide reasonable assurance regarding the reliability of financial reporting and the preparation of financial statements
• A system of internal controls for sustainability data should include preventive, detective, and corrective controls to address risks related to data accuracy, completeness, and reliability
  • Preventive controls are designed to prevent errors or irregularities from occurring (data input validation, segregation of duties, proper authorization of transactions)
  • Detective controls are designed to identify errors or irregularities that have already occurred (data reconciliations, exception reporting, analytical reviews)
  • Corrective controls are designed to correct errors or irregularities that have been identified (data corrections, reprocessing of transactions, updates to policies and procedures)

Monitoring and Assessing Internal Controls

• The design of internal controls should consider the specific risks associated with sustainability data (complexity of data collection and aggregation, subjectivity of certain metrics, potential for manipulation or bias)
• The effectiveness of internal controls should be regularly monitored and assessed, with deficiencies identified and remediated on a timely basis
• Monitoring activities may include ongoing supervision, periodic evaluations, or a combination of both
• Assessment techniques can include testing of controls, data analysis, and review of policies and procedures
• Results of monitoring and assessment activities should be reported to management and the board of directors, with action plans developed to address identified weaknesses or deficiencies

Data Quality Assurance Techniques

Data Validation and Reconciliation

• Data quality assurance techniques are processes and procedures used to ensure the accuracy, completeness, and reliability of data
• Data validation is the process of checking data against a set of rules or criteria to ensure that it is accurate, complete, and consistent (checks for data type, format, range, consistency with other data sources)
• Data reconciliation is the process of comparing data from different sources to identify and resolve discrepancies (comparing data between systems, departments, or external sources)
• Other data quality assurance techniques include data profiling (analyzing data to identify patterns and anomalies), data cleansing (identifying and correcting errors or inconsistencies), and data standardization (ensuring that data is consistent and follows a standard format)

Evaluating Data Quality Assurance Techniques

• The effectiveness of data quality assurance techniques can be evaluated based on their ability to identify and correct errors, their efficiency in terms of time and resources required, and their impact on the overall quality and reliability of the data
• The selection and implementation of data quality assurance techniques should be based on the specific risks and characteristics of the data being processed, as well as the requirements of stakeholders and regulatory bodies
• Metrics for evaluating data quality assurance techniques may include the number and severity of errors identified, the time required to resolve issues, and the impact on data quality and reporting
• Regular review and refinement of data quality assurance techniques is necessary to ensure their ongoing effectiveness and alignment with evolving business needs and regulatory requirements

Error Correction in Sustainability Data

Identifying and Investigating Errors

• A process for identifying and correcting errors or inconsistencies in sustainability data should be designed to detect and resolve issues in a timely and effective manner
• The process should include clear roles and responsibilities for data owners, data stewards, and data users, as well as procedures for reporting and escalating issues
• Data profiling and data validation techniques can be used to identify potential errors or inconsistencies (missing or incomplete data, outliers, data that does not conform to expected patterns or ranges)
• Data reconciliation can be used to compare sustainability data across different systems or sources to identify discrepancies and ensure consistency

Correcting Errors and Improving Processes

• Once errors or inconsistencies are identified, a process for investigating and correcting them should be established (manual review and correction of data, updates to data collection or processing procedures, changes to systems or controls)
• The root causes of errors or inconsistencies should be analyzed to identify opportunities for process improvement and prevention of future issues
• Corrective actions may include reprocessing of data, updates to data collection or reporting procedures, or enhancements to internal controls
• The effectiveness of the error identification and correction process should be monitored and measured (number and severity of errors identified, time required to resolve issues, impact on data quality and reporting)

Internal Audit for Sustainability Reporting

Role of Internal Audit

• Internal audit is an independent, objective assurance and consulting activity designed to add value and improve an organization's operations by bringing a systematic, disciplined approach to evaluate and improve the effectiveness of risk management, control, and governance processes
• In the context of sustainability reporting, internal audit can play a key role in assessing the integrity of sustainability data and reporting processes
• Internal audit can review the design and operating effectiveness of internal controls over sustainability data collection, processing, and reporting to ensure that they are adequate and functioning as intended
• Internal audit can also assess the accuracy, completeness, and reliability of sustainability data through data validation, reconciliation, and other quality assurance techniques

Scope and Approach of Internal Audit

• Internal audit can evaluate the processes and systems used to collect, aggregate, and report sustainability data to ensure that they are efficient, effective, and aligned with industry standards and best practices (Global Reporting Initiative (GRI), Sustainability Accounting Standards Board (SASB))
• Internal audit can provide assurance to management and the board of directors regarding the integrity of sustainability data and reporting processes, as well as identify opportunities for improvement and risk mitigation
• Internal audit can also assess compliance with internal policies and procedures, as well as external regulations and standards related to sustainability reporting
• The role of internal audit in sustainability reporting should be risk-based and aligned with the organization's overall sustainability strategy and objectives
• Internal audit should have the necessary skills, resources, and independence to effectively assess the integrity of sustainability data and reporting processes