AI-Powered Automation for Debt Market Data Processing

The objective was to streamline the processing and organisation of debt market information from various global geographies and currencies. The data, sourced from multiple stock exchanges and central bank publications, needed to be converted into a consistent and comparable format.​

Our customer is a leading UK-based provider of financial market data and information services, delivering timely, structured insights across multiple asset classes to a global audience.

Historically, the customer relied on fragmented, semi-automated processes to collate and compile debt market data. This, predominantly manual approach, created challenges around data quality, accuracy, and delivery speed. This impacted downstream services relied upon by end users requiring timely, reliable market intelligence.

Following consultation with Arrk, a multi-stage delivery approach was adopted to deliver value and benefits at the earliest opportunity.

Stage 1: Document Ingestion and Table Recognition:

• Arrk developed AI and LLM-enabled document analytics tools, capable of parsing multiple document formats including PDF, Word, Excel, and XBRL.
• Particular attention was placed on accurately recognising tabular data, which had previously presented on-going challenges.
• To maintain data integrity, automated and manual verification steps were embedded within the processing pipeline.
• Once verified, the extracted data was integrated into live analytical systems while maintaining compliance with internal data governance policies.

Stage 2: Automating Data Updates:

• The next phase focused on automating the retrieval of updated market data directly from source providers.
• Due to regulatory and legislative constraints full automation was complex even where API’s were available.
• Arrk supported a semi-automated solution whereby crawling and data extraction were scheduled outside of trading hours to optimise resource consumption and ensure adherence to content usage guidelines.

This phase of the project successfully:

• Delivered a reliable framework for time-sensitive financial data processing.
• Reduced manual intervention through the introduction of a scalable automated solution.

The Customer plans on further enhance the solution by:

• Incorporating image recognition capabilities to extract data embedded within graphical formats.
• Enabling end-to-end automation of data updates from host websites.
• Enhancing crawler intelligence to address access challenges such as CAPTCHA and other security mechanisms.

Arrk continues to work closely with the Customer as the solution develops further.

By partnering with Arrk, the customer overcame significant challenges in collecting debt market data consistently, accurately and efficiently while maintaining a compliant and secure process.