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 diverse stock exchanges and central bank publications, needed to be converted into a consistent and comparable format.

Customer

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

Award Winning Company

Corporate Training Solutions

360 Degree Approach

Problem Statement

Historically, the customer relied on several fragmented, semi-automated processes to collate and compile debt market data. This predominantly manual approach posed challenges in terms of data quality, accuracy, and speed of delivery—affecting downstream services for end users who depended on timely, reliable market intelligence.

Information Extraction

Robust System

Data Efficiency

LLM and ChatGPT

Solution Development

Project Delivery Stages

Stage 1: Document Ingestion and Table Recognition

Arrk developed AI and LLM-enabled document analytics tools, designed to parse documents across various formats including PDF, Word, Excel, and XBRL.
Particular attention was given to the accurate recognition of tabular data—an area that posed consistent challenges.
To maintain data integrity, manual verification steps were embedded within the automated pipeline.
Once verified, the extracted data was fed into live analytical systems, while maintaining compliance with internal data governance policies.

Stage 2: Automating Data Updates

The next phase involved automating the retrieval of updated market data directly from source providers.
Due to regulatory and legislative constraints—even in cases where APIs were available—full automation was complex.
Arrk supported a semi-automated workaround: crawling and data extraction were scheduled post-trading hours to manage resource consumption and ensure adherence to content usage guidelines.

AI Driven Tool

Bulk Data Extraction

Cost Effective

Outcomes

Delivered a reliable framework for time-sensitive processing of financial data.
Significantly reduced manual intervention by introducing a scalable and automated solution.

Future Plans

Incorporate image recognition capabilities to extract data embedded within graphical formats.
Achieve end-to-end automation of data updates from host websites.
Enhance crawler intelligence to bypass access challenges such as CAPTCHA and other security mechanisms.