Our client is a large institutional bank operating in the APAC region. With a robust presence across 30 markets, the bank serves more than 8.5 million retail and business customers.
The Challenge
The client was struggling with manual inefficiencies in their trade supply chain operations. Cumbersome processes, paper-based documentation, and labor-intensive tasks were severely affecting productivity. The bank wanted to free up valuable bandwidth that was being consumed by repetitive tasks, allowing employees and staff to shift their focus toward customer insights and strategic decision-making, which were critical to drive growth and customer satisfaction.
The Solution
Persistent collaborated with the bank for a transformative journey, leveraging our innovative “text-AI” framework to automate data extraction from structured and unstructured sources, integrate with legacy banking systems, and implement custom rules engines to comply with industry standards. This homegrown solution harnessed the power of AI/machine learning (ML)-based cognitive automation across six distinct functional areas within trade finance. Our algorithms seamlessly process trade supply chain documents, ensuring accuracy and efficiency.
To ensure seamless data exchange, we integrated our solution with the bank’s legacy systems, and designed and implemented custom rules engines tailored to the complex domain rules set forth by the International Chamber of Commerce. These engines ensured compliance, consistency, and adherence to industry standards.
The Outcome
With AI/ML algorithms eliminating human error and enhancing reliability, our solution had a significant impact on the client’s decision-making capabilities. The bank achieved an impressive 92% accuracy in data extraction and decision-making across various functions.
Within a year, the bank experienced a remarkable 40% improvement in productivity, reducing transaction turnaround time from 30-45 minutes to an astonishing 7-8 minutes. By embracing automation, the bank not only optimized processes but fortified their position as a forward-thinking institution in the evolving finance landscape.
Technology Used
- Text.ai (AI/ML)
- Python
- RPA (Automation Anywhere)
- OCR tools
- Rest API Drools
