Financial Compliance Assistant for Bank
Scenario Overview
A major bank needs an AI system to help compliance officers navigate complex regulatory requirements and ensure adherence to financial regulations. The system must be able to:
- Handle complex regulatory terminology and requirements
- Provide accurate, up-to-date compliance information
- Ensure consistent interpretation of regulations
- Maintain audit trails and compliance reporting
- Handle high-stakes regulatory queries with appropriate escalation
User Journey
1. Compliance Officer Query
User: "What are the reporting requirements for suspicious transactions over $10,000?"
2. System Response Flow
Step 1: Regulatory Query Understanding
# Regulatory query expansion with compliance terminology
expanded_query = compliance_expander.expand(
query="What are the reporting requirements for suspicious transactions over $10,000?",
domain="financial_compliance",
context={
"user_role": "compliance_officer",
"department": "risk_management",
"regulation_type": "AML",
"transaction_threshold": 10000
}
)
# Results in:
# - "suspicious transactions" → "SAR", "suspicious activity report", "AML", "money laundering"
# - "reporting requirements" → "filing requirements", "regulatory reporting", "compliance obligations"
# - "$10,000" → "threshold", "monetary threshold", "reporting threshold"
Step 2: Regulatory Document Retrieval
# Search regulatory databases and compliance documents
retrieval_results = hybrid_retriever.retrieve(
query=expanded_query,
k=30, # More candidates for complex regulatory queries
filters={
"regulation_type": "AML",
"document_type": "regulatory_guidance",
"jurisdiction": "US",
"last_updated": "2024-01-01"
}
)
Step 3: Compliance Reranking
# Rerank based on regulatory authority and recency
reranked_results = compliance_reranker.rerank(
query=expanded_query,
documents=retrieval_results,
context={
"regulation_authority": "FinCEN",
"regulation_type": "AML",
"compliance_level": "high"
},
top_k=10
)
Step 4: Compliance Response Generation
# Generate compliance-focused response with legal disclaimers
response = compliance_generator.generate(
query=expanded_query,
context=reranked_results,
compliance_level="high",
legal_disclaimers=True
)
3. System Response
# Suspicious Transaction Reporting Requirements (SAR Filing)
## Regulatory Authority
**FinCEN (Financial Crimes Enforcement Network)** - Primary authority for SAR filing requirements
## Reporting Thresholds
- **Mandatory SAR Filing**: Transactions ≥ $5,000 that are suspicious
- **Voluntary SAR Filing**: Transactions < $5,000 that are suspicious
- **Currency Transaction Report (CTR)**: Cash transactions ≥ $10,000 (separate requirement)
## SAR Filing Requirements
### 1. **Timing Requirements**
- **Filing Deadline**: 30 days from date of initial detection
- **Extension**: Up to 60 days with supervisory approval
- **Immediate Notification**: For ongoing violations or imminent harm
### 2. **Required Information**
- **Subject Information**: Name, address, SSN/EIN, date of birth
- **Transaction Details**: Amount, date, method, purpose
- **Suspicious Activity Description**: Detailed narrative of why activity is suspicious
- **Supporting Documentation**: Account statements, transaction records
### 3. **Filing Process**
- **Electronic Filing**: Through FinCEN's BSA E-Filing System
- **Form**: FinCEN Form 111 (SAR)
- **Retention**: 5 years from date of filing
## Compliance Obligations
### 1. **Internal Controls**
- **Suspicious Activity Monitoring**: Automated and manual monitoring systems
- **Employee Training**: Annual AML training for all staff
- **Record Keeping**: Maintain all supporting documentation
### 2. **Reporting Obligations**
- **Quarterly Reports**: Suspicious activity trends and patterns
- **Annual Reports**: AML program effectiveness assessment
- **Ad Hoc Reports**: As requested by regulatory authorities
## Legal Disclaimers
- This information is for general guidance only
- Specific situations may require legal counsel
- Regulations are subject to change
- Always consult with compliance legal team for complex cases
## Escalation Requirements
- **Immediate Escalation**: Transactions ≥ $100,000
- **Legal Review**: All SARs before filing
- **Management Approval**: Required for all SAR filings
Implementation Code
1. Compliance Configuration
# config/compliance_config.py
from packages.rag import HybridRetriever, CrossEncoderReranker
from packages.agents import RAGAgentGraph, AgentConfig
from packages.rag.query_expansion import ComplianceQueryExpander
from packages.observability import MetricsCollector, StructuredLogger
class ComplianceConfig:
def __init__(self):
# Compliance query expansion
self.compliance_expander = ComplianceQueryExpander(
domain="financial_compliance",
regulatory_terminology_file="data/regulatory_terminology.json",
compliance_abbreviations_file="data/compliance_abbreviations.json"
)
# Hybrid retrieval with compliance focus
self.hybrid_retriever = HybridRetriever(
vector_retriever=VectorRetriever(
model_name="text-embedding-3-large",
vector_store=OpenSearchStore(
index_name="compliance_knowledge_base"
)
),
bm25_retriever=BM25Retriever(
index_path="data/compliance_bm25_index"
),
alpha=0.8 # Favor vector search for regulatory terminology
)
# Compliance-specific reranking
self.compliance_reranker = ComplianceReranker(
model_name="cross-encoder/ms-marco-MiniLM-L-6-v2",
regulatory_authority_weight=0.9,
recency_weight=0.8,
compliance_level_weight=0.95
)
# Agent configuration for compliance domain
self.agent_config = AgentConfig(
model_name="gpt-4-turbo-preview",
temperature=0.02, # Very low temperature for regulatory accuracy
max_steps=8,
retrieval_k=30,
rerank_k=10,
enable_web_search=False, # Disable web search for regulatory accuracy
enable_escalation=True,
cost_limit=0.20
)
2. Compliance Knowledge Base
# data/compliance_knowledge_base.json
{
"documents": [
{
"id": "sar_filing_requirements_001",
"title": "SAR Filing Requirements and Procedures",
"content": "Comprehensive guide to SAR filing requirements...",
"metadata": {
"regulation_type": "AML",
"regulatory_authority": "FinCEN",
"document_type": "regulatory_guidance",
"jurisdiction": "US",
"compliance_level": "high",
"last_updated": "2024-01-15",
"source": "FinCEN",
"evidence_level": "official"
}
}
]
}
3. Compliance Agent Implementation
# agents/compliance_agent.py
import asyncio
from typing import Dict, Any, List
from packages.agents import RAGAgentGraph
from packages.observability import MetricsCollector, StructuredLogger
class ComplianceAgent:
def __init__(self, config: ComplianceConfig):
self.config = config
self.agent_graph = RAGAgentGraph(
config=config.agent_config,
tool_registry=config.tool_registry
)
self.metrics = config.metrics_collector
self.logger = StructuredLogger()
async def handle_compliance_query(self, query: str, user_context: Dict[str, Any]) -> Dict[str, Any]:
"""Handle compliance query with full pipeline."""
start_time = time.time()
try:
# Step 1: Compliance query expansion
expanded_query = await self._expand_compliance_query(query, user_context)
# Step 2: Regulatory document retrieval
retrieval_results = await self._retrieve_compliance_documents(expanded_query, user_context)
# Step 3: Compliance reranking
reranked_results = await self._rerank_compliance_documents(expanded_query, retrieval_results, user_context)
# Step 4: Compliance response generation
response = await self.agent_graph.ainvoke({
"query": expanded_query,
"retrieved_docs": retrieval_results,
"reranked_docs": reranked_results,
"user_context": user_context,
"compliance_level": "high"
})
# Step 5: Compliance validation
validated_response = await self._validate_compliance_response(response, user_context)
# Step 6: Audit logging
await self._log_compliance_interaction(query, response, user_context)
return validated_response
except Exception as e:
self.logger.error(f"Compliance query failed: {e}")
return await self._handle_compliance_error(query, e, user_context)
async def _validate_compliance_response(self, response: Dict[str, Any], user_context: Dict[str, Any]) -> Dict[str, Any]:
"""Validate compliance response for accuracy and completeness."""
# Check for required legal disclaimers
if not response.get("legal_disclaimers"):
response["legal_disclaimers"] = self._get_standard_disclaimers()
# Check for regulatory authority citations
if not response.get("regulatory_citations"):
response["regulatory_citations"] = self._extract_regulatory_citations(response)
# Add compliance metadata
response["compliance_metadata"] = {
"user_role": user_context.get("user_role"),
"department": user_context.get("department"),
"query_timestamp": datetime.utcnow().isoformat(),
"compliance_level": "high"
}
return response
Features Demonstrated
1. Response Consistency
- Uniform regulatory interpretation
- Consistent compliance language
- Standardized legal disclaimers
2. Error Handling
- Graceful handling of ambiguous regulatory language
- Fallback responses for unclear requirements
- Escalation for complex regulatory issues
3. Rate Limiting
- Tiered access based on user role and clearance level
- Burst protection for high-stakes queries
- Fair resource allocation
4. Cost Management
- Budget controls for expensive regulatory queries
- Cost tracking per department
- Automatic escalation when cost thresholds exceeded
5. Analytics & BI
- Compliance pattern analysis
- Regulatory query trend monitoring
- Risk assessment and reporting
6. Security & Compliance
- Advanced PII detection and data protection
- Audit trail maintenance
- Compliance reporting and monitoring
Next Steps
- Deploy the compliance system with proper security controls
- Ingest regulatory knowledge base with proper metadata
- Configure compliance policies and validation
- Train compliance staff on the new system
- Monitor compliance accuracy and audit requirements
Related Stories
- IT Support Agent - Similar structure with IT domain
- Medical Knowledge Assistant - Safety-focused implementation
- Government Policy Assistant - Policy-focused implementation
Ready to implement? Start with the compliance knowledge base setup and work through each component step by step! 🏦