Agentic AI Workflows for Financial Services

Master the design and implementation of advanced agentic workflows, specifically for the financial sector. Using Python and Large Language Models (LLMs), you will build autonomous systems capable of processing SWIFT transactions, detecting fraud, and automating compliance. You will implement agentic workflow patterns including Evaluator-Optimizer, Parallelization, Prompt Chaining, Routing, and Orchestrator-Workers. The course culminates in the "SwiftGuard" project, where you will engineer a complete multi-agent ecosystem to secure international financial messaging against sophisticated threats.

Course

Intermediate
14 hours
Updated: Dec 19, 2025

Subscription · Monthly

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Unlimited access to hundreds of top-rated courses
Hands-on projects with expert feedback
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Program Certificates

Skills you'll learn

11 skills

Sequential Task Decomposition for Prompt Chaining
Agentic Workflow Design & Visualization
Agentic Task Routing Design
Implementing Parallel Agent Workflows
Implementing Sequential Task Prompt Chain Workflows

Prerequisites

4 prerequisites

Prior to enrolling, you should have the following knowledge:

You will also need to be able to communicate fluently and professionally in written and spoken English.

Course Outline

15 lessons
1 project

Agentic AI Workflows for Financial Services

Introduction to Agentic AI Workflows for Financial Services
Learn how AI agents replace rigid rules to detect fraud in SWIFT transactions. Start your journey into adaptive financial workflows.
Understanding Agentic Workflows
Explores what defines a modern AI agent, its core components (Persona, Knowledge, Tools, Interaction), and the different types of agents based on their LLM interaction model.
Agentic Workflow Modeling
Design and visualize agentic workflows. Learn common agent types as building blocks for creating visual workflow diagrams.
Agentic Workflow Implementation for Financial Services
Learn to implement agentic workflows for SWIFT transaction processing using specialized AI agents for validation, fraud detection, risk assessment, and orchestration.
Agentic Workflow Patterns: Prompt Chaining Workflow
Introduces the Prompt Chaining pattern for breaking down complex tasks into a sequence of smaller, dependent steps. It covers strategies for task decomposition, validation, and context management.
Implementing Agentic Prompt Chaining Workflows with Python for Financial Services
Learn to build multi-agent prompt chaining workflows in Python, with each agent sequentially analyzing SWIFT transactions to produce a comprehensive, consensus-based decision.
Agentic Workflow Patterns: Routing
Teaches the Routing pattern, which involves classifying incoming tasks and directing them to the most appropriate specialized agent or processing path.
Implementing Agentic Routing Workflows with Python for Financial Services
Learn to implement agentic routing for SWIFT messages in Python using LLMs to intelligently triage transactions through specialized processing workflows.
Agentic Workflow Patterns: Parallelization
Introduces the Parallelization pattern for executing multiple agent tasks concurrently. It covers strategies for task decomposition (sharding, aspect-based) and result aggregation.
Implementing Agentic Parallelization Workflows with Python for Financial Services
Learn to build scalable multi-agent fraud detection workflows in Python using parallel processing, agent design, and modular aggregation for fast, adaptable SWIFT message analysis.
Agentic Workflow Patterns: Evaluator-Optimizer Workflow
Focuses on the Evaluator-Optimizer pattern, an iterative process of generation, critique, and refinement to improve output quality. It emphasizes clear evaluation criteria and actionable feedback.
Implementing Agentic Evaluator-Optimizer Workflows with Python for Financial Services
Learn to build Python workflows that validate, optimize, and auto-correct SWIFT messages using LLMs for efficient message processing and auditability in financial systems.
Agentic Workflow Patterns Orchestrator-Workers Workflow
Introduces the advanced Orchestrator-Workers pattern, where a central agent dynamically plans, delegates, and synthesizes the work of multiple specialized worker agents.
Implementing Agentic Orchestrator-Workers Pattern in Python for Financial Services
Learn how to implement the agentic Orchestrator-Workers pattern in Python to automate SWIFT post-processing, generating dynamic compliance and audit reports with modular, extensible agents.

Project: SWIFTGuard
Build a multi-agent AI system to validate SWIFT messages, detect fraud, and automate transaction processing using agentic workflow patterns.

Program Instructors

2 instructors

Unlike typical professors, our instructors come from Fortune 500 and Global 2000 companies and have demonstrated leadership and expertise in their professions:

David Pazmino

Peter Kowalchuk

Engagement Director at C3.ai

David Pazmino

Peter Kowalchuk

Engagement Director at C3.ai

About this program

Learn to design agentic AI workflows with compliance checks, regulatory validation, and verifiable audit trails for financial processes.

Subscription · Monthly

Cancel Anytime
Unlimited access to hundreds of top-rated courses
Hands-on projects with expert feedback
Personalized career coaching and interview prep
Program Certificates

Agentic AI Workflows for Financial Services

Skills you'll learn

Prerequisites

Course Outline

Program Instructors

About this program

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