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How AI Improved Financial Statement Processing by 600%

Mindex Jun 26, 2026, 8:00:00 AM

AI Customer Stories

How AI Improved Financial Statement Processing by 600%

Mindex helped a financial services client improve financial statement processing by up to 600% using AI-powered document processing on AWS.

Using Amazon Bedrock, the solution automated financial data extraction from complex documents and increased processing capacity from 100 to more than 600 pages.

Business Challenge: Processing Large Financial Statements and Unstructured Documents

To support our client's evolving document processing needs, Mindex focused on five key objectives:

Process Larger Financial Statements

Accelerate access to transaction-level financial data while supporting increasingly large and complex financial documents.

Extract Structured Financial Data

Capture financial information from a wide range of bank and credit card statement formats.

Preserve Critical Data Relationships

Maintain the relationships between account information, balances, and transactions throughout the extraction process.

Transform Unstructured Documents

Convert unstructured financial documents into structured JSON output for analysis and investigation workflows.

Support Scalable Processing

Develop a cloud-based architecture capable of supporting future growth and increasing document volumes.

The Solution: AI-Powered Intelligent Document Processing on AWS

Mindex designed and implemented a serverless Intelligent Document Processing pipeline on AWS that automates document ingestion, classification, and financial data extraction.

Powered by Amazon Bedrock, the solution converts unstructured PDFs into structured data that can be used for downstream analysis and investigation workflows.

Key Capabilities

Automated document ingestion
Intelligent document classification
Transaction-level data extraction
Metadata association and validation
Processing of large financial documents

One of the primary technical challenges involved processing lengthy financial statements while preserving the context between accounts, balances, and transactions.

To address this, Mindex developed an architecture that intelligently segments large documents into manageable processing windows while maintaining data integrity throughout the extraction process. Built on AWS and Amazon Bedrock, the solution delivers reliable processing while preserving the context required for financial investigations.

Results: Faster Processing at Greater Scale

Improve Financial Statement Processing Speed by Up to 600%

The solution improved financial statement processing speeds by up to 600%, significantly reducing the time required to analyze large financial documents.

Increase Processing Capacity from 100 to 600+ Pages

The solution expanded our client's ability to process individual financial statements from approximately 100 pages to more than 600 pages.

Documents exceeding 600 pages can now be processed in approximately two hours.

Extract Data from Non-Standard Documents

Using Amazon Bedrock, the solution transforms non-standard financial statements into structured JSON, enabling consistent transaction-level analysis across a wide variety of document formats.

Establish a Foundation for Future Growth

The solution provides a scalable foundation for future automation initiatives while giving our client greater control over the document extraction process.

Technologies Used

Amazon Bedrock
Amazon Textract
Amazon API Gateway
Amazon S3
AWS Step Functions
Amazon EventBridge
Amazon DynamoDB

Bringing the Benefits of AI-Powered Document Processing to More Organizations

From Intelligent Document Processing to custom AI applications, Mindex helps organizations leverage AWS and generative AI technologies to solve complex business challenges, automate manual processes, and unlock greater value from their data.