FINANCIAL SERVICES
AI-powered automation transforms bank’s securitisation processes
At a glance
A leading multinational bank with over 80,000 employees and global revenues exceeding US$80 billion needed to automate its manual, human-based document review and reconciliation at its Hong Kong branch. Simultaneously, they had to meet strict governance standards and regulatory requirements.
In response, FDM assigned five AI-trained Python Engineers with the aim of automating manual tasks within the securitisation process, accelerating AI adoption, and driving digital transformation across the business.
FDM Practices
- Change & Transformation
Industry
Financial Services
Tech stack
Python
Unix
SQL
Microsoft 365 Copilot
Impact
5
AI-trained Python Engineers on boarded
90%
reduction in processing time
With FDM’s expertise, the bank successfully automated critical securitisation processes, setting new industry benchmarks for efficiency, accuracy, and compliance. The bank is now considered a pioneer in utilising AI and Large Language Models (LLMs) to enhance business processes.
Following the success of the initial project, two FDM Consultants were seconded to Taiwan to support new AI projects, before assisting on a client migration project where their rapid Python automation capabilities ensured smooth data transformation and reconciliation.
Developing a job-ready AI squad
FDM’s Account Management Team engaged 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.
To address their challenge, FDM proposed a Rapid Automation Squad of five Python Engineers, including a recent AI graduate.
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.
Embedding AI into business operations
Unlike the traditional entry into the bank’s technology division, the Squad was embedded within the business team, ensuring automation aligned with operational needs and regulatory requirements.
Once onboarded, the Squad developed AI-powered automation using LLMs, text classification, and Python-based tools to optimise securitisation processes.
Solutions included:
Other achievements included developing a Python tool that decreased manual efforts, to the creation of an automated voucher-checking system that dramatically reduced financial reporting times.
“Using Python coupled with CoPilot, the Squad reduced manual processes usually measured in days and hours to automated tasks that now take minutes and seconds.”
Mike McLaren, Chief Finance Officer, FDM Group
Creating an AI pioneer in the banking sector
Prior to the success of the automation project, the bank’s Chief Information Officer had faced resistance to adding technology functions to the business operations. After the Squad delivered these significant outcomes, other departments have now sought to replicate the Squad approach.
The bank is now working with FDM to assign additional consultants across further functions and geographies, with the specific aim of delivering further AI-driven automation.
Despite the strict regulations and governance placed on financial services, this project also highlighted the scale of automation opportunities on routine tasks, which can reduce operation costs while fulfilling compliance requirements.
“Our work has demonstrated how AI-powered automation could transform operations.”
Richard Zhu, Python Engineer and FDM Change & Transformation Consultant
Conclusion
FDM’s commitment to AI training for day one-ready consultant impact enabled this multinational bank to transition away from time-consuming, error-prone manual processes towards efficient task automation.
Now primed to scale AI-powered automation across functions and geographies, the bank has led the way for other financial services to implement AI without compromising on governance and regulation requirements.