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The Client
The client is an American multinational energy giant, operating across upstream, midstream, and downstream segments in over 180 countries. The company manages large volumes of financial records, audits, contracts, and daily material data requiring rigorous regulatory compliance, financial transparency, and operational efficiency.
Business Challenges
Finance and audit functions are under mounting pressure as they manage growing volumes of structured and unstructured data from across the business. Manual audit checks and traditional data processing methods are slow, resource-intensive, and prone to errors, making it difficult to maintain accuracy and compliance. As organizations work to improve efficiency and decision-making, the ability to manage diverse, high-volume data with consistency and quality has become critical. AI-driven audit automation directly addresses these challenges by streamlining data handling, enhancing accuracy, and reducing dependence on manual processes.
Difficulty in establishing a robust framework
Struggles with eliminating irrelevant information
The existing data extraction engine (DocIntel) has limitations
Solution
Organizations are increasingly seeking automated solutions to improve the quality and reliability of their data management processes. AI in audit automation leverages advanced technologies to streamline data cleaning, reduce manual effort, and ensure that only relevant information is retained for analysis and decision-making.
The AI solution framework leverages Azure OpenAI to automatically detect and remove irrelevant data from Excel and CSV files, using Generative AI to filter and retain only pertinent information. This ensures greater accuracy and integrity in data management.
By automating the data cleaning process, the framework significantly reduces manual effort and optimizes resource utilization. Its ability to efficiently handle large data volumes is supported by Azure’s scalable infrastructure, which guarantees high availability and reliability.
The solution is designed for seamless integration with existing systems and features an intuitive interface, making configuration, monitoring, and management straightforward. Ultimately, this approach aims to enhance data quality, operational efficiency, and decision-making capabilities.
Doc Intel Technical Architecture
Figure 1: Doc Intel Technical Architecture
Tech Stack
| Programming Languages | Python for machine learning models, Azure SDK, scripting, and SQL for database queries and data management. |
| Azure Cloud Platform | Azure Cloud Platform, Azure Blob Storage, Azure Functions, Azure Machine Learning, Azure OpenAI services, Azure SQL Database, Azure AI Search, Azure Key Vault, API Management, and GitHub. |
| IDEs | Visual Studio Code for Python and Azure function development and Azure Machine Learning Studio for building and managing ML models. |
| Other Components | Azure SDKs for Python, Scikit Learn, Azure Cognitive Services API, Azure Logic Apps, or Data Factory. |
Business Benefits
AI-Driven Automation Impact
- Achieved complete (100%) document processing, eliminating the need for sampling.
- Increased audit coverage and accuracy by scaling from 25 documents to 200–1000 documents per audit.
- Minimized manual effort, enabling auditors to concentrate on insights and exceptions rather than routine data extraction.
Key Outcomes realized
- Enhanced audit frequency and depth without expanding team size.
- Improved data accuracy and completeness through comprehensive document analysis.
- Accelerated turnaround times, supporting more agile and responsive audit cycles.
- Strengthened risk detection and decision-making with full data visibility.
Conclusion
By leveraging Azure OpenAI and advanced automation, the proposed framework significantly enhances the efficiency, accuracy, and reliability of data management within finance and audit functions. Generative AI in finance audits automates the detection and removal of irrelevant information, streamlining data processing and empowering organizations to make faster, more informed decisions. Seamless integration and scalability ensure that the solution remains robust as data volumes grow, supporting ongoing compliance and operational excellence.
Testimonial
“Our team’s innovative approach by leveraging GenAI and automation transformed the client’s audit and finance operations, enabling full document coverage and smarter risk analysis. With Audit AI – DocIntel, the client achieved 100% document processing, eliminated manual sampling, and scaled audit coverage, setting a new benchmark for efficiency and accuracy in finance audit automation. This achievement reflects our commitment to delivering practical, future-ready and AI-powered solutions that drive measurable value for supermajor oil & gas companies.” – Assistant Vice President, Energy & Utilities, LTIMindtree
Discover how Audit AI and DocIntel can transform your organization’s data management and audit processes. Connect with us at eugene.comms@ltimindtree.com for a personalized consultation or demonstration
