BBVA Deploys ChatGPT Enterprise AI Assistant to Enhance Data Analysis and Efficiency in Internal Audit Operations

BBVA Deploys ChatGPT Enterprise AI Assistant to Enhance Data Analysis and Efficiency in Internal Audit Operations

(IN BRIEF) BBVA has developed an artificial intelligence assistant using ChatGPT Enterprise to support its Internal Audit teams in conducting data-intensive audits more efficiently and consistently. The tool helps auditors analyze large datasets by guiding them through tasks such as validating data quality, designing analytical tests, generating reproducible code in languages like Python and SQL, and interpreting results while maintaining full transparency and traceability. Although the AI system supports the analytical process, final validation and professional judgment remain entirely with human auditors. By standardizing data analysis workflows and reducing manual programming and documentation work, the solution is expected to improve productivity by around 10 percent in audits that require extensive data analysis, allowing auditors to focus more on evaluating anomalies, assessing risks, and strengthening governance across the organization.

(PRESS RELEASE) BILBAO, 10-Mar-2026 — /EuropaWire/ — BBVA has introduced a new artificial intelligence assistant based on ChatGPT Enterprise to support its Internal Audit teams in analyzing large volumes of data more efficiently and consistently. The tool is designed to help auditors manage complex data-driven reviews by assisting with tasks such as validating datasets, designing analytical tests, and interpreting results, while ensuring that human professionals retain full oversight and final decision-making authority.

Internal audit plays a critical role in safeguarding the integrity and reliability of large organizations. In a data-driven financial institution like BBVA, the volume of information generated across operations is substantial, requiring auditors to review and analyze complex datasets while complying with increasingly demanding regulatory, privacy, and governance standards.

Each year, BBVA’s Internal Audit teams conduct hundreds of audits across multiple countries and business units. These reviews often involve combining and evaluating large datasets originating from different systems and formats. Auditors must also design increasingly sophisticated analytical tests, verify data quality, document assumptions and analytical decisions, and maintain full traceability from original datasets to final audit conclusions.

Historically, some of these processes have relied on spreadsheets or custom code developed individually by auditors. While effective, this approach can introduce inefficiencies and make it difficult to maintain consistency across different audits. It may also increase the risk of errors, create reliance on individual expertise, and make it harder to reproduce analyses later.

To address these challenges, BBVA’s Internal Audit department developed a specialized GPT within ChatGPT Enterprise tailored specifically for audit data analysis. Rather than replacing human expertise, the system is designed to support auditors by standardizing analytical processes and incorporating best practices for data validation, testing, and documentation.

The assistant guides auditors step by step throughout the analytical process. It helps verify the integrity of datasets included in an audit, performs quality and consistency checks, and assists in designing complex analytical tests. It can also interpret analytical results and generate reproducible code in programming languages commonly used in audit work, including Python and SQL.

In addition to producing code, the tool provides structured explanations of the analysis performed, enabling auditors to review and document the logic behind each step. The system also records constraints, dataset parameters, and record counts used during analysis, ensuring complete transparency and traceability.

Although the AI assistant automates parts of the analytical workflow, all validation, professional interpretation, and final conclusions remain the responsibility of the auditors. In practice, the tool acts as a supporting framework that helps auditors apply consistent methodologies while retaining full control over the evaluation process.

By systematizing data analysis and reducing the need for manual programming and documentation tasks, the solution is expected to improve productivity in audits that rely heavily on data analysis. BBVA estimates that productivity could increase by approximately 10 percent in such engagements.

Carlos Sanz-Pastor, Global Head of Internal Audit at BBVA, explained that providing auditors with a shared analytical foundation allows them to focus more on professional judgment and risk identification rather than repetitive technical tasks. By reducing time spent on coding and documentation, auditors can devote more attention to interpreting unusual patterns in data and assessing potential risks.

The adoption of artificial intelligence in this context illustrates how advanced technologies can enhance key governance functions within financial institutions. Rather than automating critical decisions, the system strengthens transparency, traceability, and analytical rigor—helping auditors validate the bank’s processes more comprehensively and support the organization’s broader strategic priorities.

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SOURCE: BBVA