Custom-skilled team develops AI-powered automation, transforming bank’s securitisation processes
FDM’s agile approach delivered talent providing scalable data transformation solutions, cutting processing time by over 90%, as outlined in this case study
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- Discover
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Understanding the challenge
Securitisation requires meticulous review and cross-checking of large datasets. Traditionally, operations teams manually browsed multiple websites, copied data, and checked hundreds of fields—a time-consuming and error-prone process. FDM’s Account Management Team engaged with the bank’s Digital and Transformation Team to understand their objectives. The client needed skilled AI talent to integrate automation into securitisation workflows without compromising regulatory standards. FDM was the perfect partner for this delivery, thanks to our agile approach, deep talent pool, and ability to meet niche client demands. Our service model enables us to build capabilities through expert coaching and custom sprints for targeted upskilling on demand.
To address their challenge, FDM proposed a Rapid Automation Squad of five Python Engineers, including a recent AI graduate. Unlike the traditional entry into the bank’s technology division, the Squad would be embedded within the business team, ensuring automation aligned with operational needs and regulatory requirements.
- Design
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The skill sets for transformation
Before their client assignment, the Squad received intensive coaching in FDM’s Data & Analytics Practice. They gained hands-on Python, Unix, and SQL upskilling in the FDM Skills Lab, mastering data cleansing and analysis project building. Adding AI and AI Governance training their Python skills were coupled with CoPilot for the efficient automation of manual processes.
Pro-skills coaching strengthened their communication abilities, enabling effective collaboration globally, while Scrum training improved their project planning and execution.
- Deliver
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Once on client assignment the Squad developed and implemented AI-powered automation using Large Language Models (LLMs), text classification, and Python-based tools to optimise securitisation processes.
Key innovations included:- Python web-scraping and reconciliation tool – 90% faster processing.
- LLM-driven reconciliation process – for automated data extraction.
- Significant improvements – in time, effort, and error rates.
- Providing overseas migration support – rapidly bridging technical gaps.
FDM Consultants were instrumental to the Squad’s success. Their achievements ranged from developing a Python tool that decreased manual effort to creating an automated voucher-checking system that dramatically reduced financial reporting times.
Wider impact and expansionBank-wide AI adoption – The Squad’s success influenced other teams to implement AI-driven automation.
International expansion – Two FDM Consultants were seconded to Taiwan to support new AI projects. Ryan and Richard were also deployed to a major client migration project, where their rapid Python automation capabilities ensured smooth data transformation and reconciliation.
Future talent pipeline – The bank is now onboarding additional FDM Consultants to scale AI initiatives.With FDM’s expertise, the bank successfully automated securitisation processes, setting new industry benchmarks for efficiency, accuracy, and compliance.
The impact of FDM’s AI-driven approach has influenced strategy across the organisation, accelerating AI adoption and driving digital transformation.
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