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OpenAI Agents SDK Setup & Tool Definitions

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Linked challenge: Building an Agentic AML Risk Intelligence Workflow with OpenAI Agents SDK and Galileo

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Linked challenge

Building an Agentic AML Risk Intelligence Workflow with OpenAI Agents SDK and Galileo

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Original prompt text with formatting preserved for inspection.

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Initialize an OpenAI Agents SDK application (`from agents import Agent, Runner, function_tool`) with distinct specialized agents: TransactionInvestigatorAgent and RegulatoryReporterAgent. Define tools for querying transaction history, checking COSMIC blacklist registers, and calculating graph distance to flagged nodes. Ensure all tool parameters are typed with full JSON schema descriptions.

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Linked challenge

Building an Agentic AML Risk Intelligence Workflow with OpenAI Agents SDK and Galileo

In light of MAS guidelines on agentic AI in financial services and the Collaborative Sharing of ML/TF Information & Cases (COSMIC) platform, financial institutions in Singapore are adopting autonomous multi-agent systems to detect money laundering and terrorist financing across inter-bank networks. Regulated financial agents must dynamically inspect complex multi-hop transaction graphs, verify shell company ownership patterns, evaluate cross-border fund flows, and output explainable audit traces while adhering to strict compliance constraints. In this challenge, you will construct a production-ready anti-money laundering (AML) intelligence system using the OpenAI Agents SDK to manage multi-agent orchestration and tool invocation. To ensure continuous governance and strict risk bounds, you will integrate Galileo to evaluate output accuracy, detect hallucinations in risk summaries, and enforce safety guardrails before regulatory handoff. Your solution will consume real-time synthetic banking transaction feeds, query COSMIC inter-bank flag databases via function tools, dynamically isolate suspicious networks, and generate fully structured Suspicious Transaction Report (STR) dossiers complete with human-in-the-loop review triggers.

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