The financial technology giant deploys conversational tools within Trade Innovation and Loan IQ, aiming to instantly augment user capability and combat institutional knowledge loss across global banking operations.
The foundation of modern corporate banking —handling complex trade finance and syndicated lending— is facing an unexpected headwind: a critical shortage of specialised, deeply embedded knowledge. As transaction complexity rises, relying on siloed expertise or manual intervention is no longer tenable. Finastra, a software leader servicing over 7,000 institutions, has responded by fundamentally altering the user experience across its lending and trade platforms through two purpose-built AI solutions.
Conversational support: Assist.AI cuts through complexity
The first major shift is the introduction of Assist.AI, an AI assistant seanlessly integrated into Finasta’s Trade Innovation solution, leveraging Microsoft Azure OpenAI Service. This tool moves beyond simple keyword search; it functions as a real-time operational expert. By employing advanced retrieval methods like vector databases and context-aware prompt engineering, Assist.AI delivers precise answers drawn from complex documentation, directly within the user’s workflow.
The objective is to reduce the time banks spend on internal support escalations. By providing prompt-based assistance and guidance on trade processes, Assist.AI accelerates transaction processing and improves overall operational velocity for banks managing international trade flows.
Anastasia McAlpine, Head of Trade and Supply Chain Finance Product Management, Finastra
Anastasia McAlpine, Head of Trade and Supply Chain Finance Product Management, Finastra says: “Trade finance is the backbone of global commerce, yet it’s often slowed by complexity and fragmented expertise. Assist.AI changes that by putting real-time intelligence at every user’s fingertips. We’re helping banks move faster, reduce operational bottlenecks, and deliver a seamless experience for clients engaged in international trade.”
Tackling skills gaps with Academy.AI
While Assist.AI manages real-time queries, Academy.AI targets the systemic problem of skill development. The goal is to swiftly equip users of Finastra’s flagship products, Loan IQ and Trade Innovation, with the necessary domain and product knowledge.
Academy.AI evolves the traditional, slower model of in-person training by offering a flexible mix of instruction-led and self-paced learning supported by a GenAI chatbot, trained specifically on the curriculum. This system not only standardises competency assessment across large user bases but also helps reduce reliance on a few senior subject matter experts within an organisation.
“Loan IQ’s integration with AI-driven learning tools addresses the critical challenge of institutional knowledge loss. By integrating generative AI in training and support, we enable scalable onboarding and standardised competency across large teams. This approach mitigates key-person risk and ensures operational resilience in syndicated lending”, explains Simon Thorogood, Senior Director, Product Management, Corporate and Syndicated Lending, Finastra
Deeper intelligence integration
Finastra’s approximately 200 dedicated AI and R&D staff are focused on transitioning these tools from reactive support to proactive intelligence. The roadmap for 2025 signals a deeper integration of intelligence. Future enhancements will reportedly focus on enabling new capabilities and expanding the use of analytics within trade finance workflows. The overarching vision is to create a dynamic, intelligent environment where the software anticipates user needs and potential risks based on transactional history, solidifying the firm’s leadership in digitizing complex corporate finance.
For successfully simplifying trade finance and lending through its innovative blend of AI and cloud technology, the Corporate Banking and Lending business unit was recently honoured with the Best AI Supply Chain Solution award at The Digital Banker’s Global AI Innovation Awards 2025.
