AI Credit Memo

AI Credit Memo is solution that supports the bank professionals involved in the preparation of the Credit Memo — the structured report summarizing a borrower’s financial profile, risk evaluation, and lending recommendation, which lies at the core of every credit decision. Acting as a digital twin of the credit process, the solution operates as an orchestrator within an ecosystem of AI agents acting as digital coworkers, designed to support each participant in executing their specific tasks and to coordinate their contributions throughout the end-to-end process of producing the final credit memo. Based on domain knowledge and contextual understanding, the orchestrator manages the operational steps, activates the specialized agents, and ensures consistency across all input and output flows.

At its core, the application relies on a network of AI agents, each designed with vertical expertise and a specific objective: the worker AI agents directly assist every human actor involved in the credit process—mirroring real functional domains such as financial analysis, risk evaluation, ESG assessment, sector benchmarking, and forward-looking scenario simulation.

To perform their tasks, worker agents can interact with other specialized AI agents or with analytical and predictive tools, enabling access to structured internal and external data, identification of relevant information — such as counterparty profiles, corporate events, ESG indicators, or market analyses — and execution of simulations and forecasts, generating targeted, explainable analytical outputs that can be easily shared within the collaborative workflow.

For example, the Forward-Looking Analysis Agent enables analysts to simulate best- and worst-case scenarios and interact conversationally with data to explore the impact of economic shifts across strategic pillars, uncover insights, and refine analyses in real time.

The Credit Memo Agent then aggregates the contributions of all other agents—human and digital—into a coherent, auditable memorandum ready for review and approval.

Underlying this system is a foundation layer of large language and reasoning models, dynamically selected based on task complexity to ensure analytical depth, logical consistency, and reliability.