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Client Portfolio RAG

Wealth ManagementPrivate BankingFamily Offices

Build a personalized RAG system over client portfolio documents β€” statements, investment policies, and suitability assessments for advisors.

Recommended RAG Stack

Parser
Unstructured.io
Embedding Model
OpenAI text-embedding-3-large
Vector Database
Weaviate (self-hosted)
RAG Framework
LangChain
LLM
Claude
Evaluation
TruLens

Wealth managers and financial advisors serve clients with complex portfolios spanning multiple accounts, asset classes, and investment vehicles. Client portfolio documents β€” investment policy statements, portfolio statements, suitability assessments, and meeting notes β€” contain the institutional knowledge needed to deliver personalized advice. A RAG system over client portfolio documents enables advisors to instantly retrieve client context, prepare for meetings, and deliver data-driven recommendations.

The Advisor Knowledge Gap

A typical financial advisor manages 100-200 client relationships. Each client generates annual documentation including quarterly statements, rebalancing reports, tax documents, IPS updates, and meeting notes. Without a retrieval system, advisors rely on memory and manual file searches to recall client-specific details. RAG eliminates this friction by making every client document instantly searchable.

Client Documents for Portfolio RAG

  • Investment Policy Statements β€” Risk tolerance, asset allocation targets, rebalancing rules, and investment constraints
  • Portfolio statements β€” Holdings, positions, cash balances, and performance history
  • Suitability assessments β€” Client risk profiles, investment objectives, time horizons, and liquidity needs
  • Meeting notes β€” Discussion summaries, action items, commitments, and client preferences
  • Correspondence β€” Client emails, instructions, and communications regarding portfolio changes

Architecture for Client Portfolio RAG

The recommended architecture uses LangChain for orchestration with OpenAI text-embedding-3-large for general-purpose embedding. Unstructured.io handles parsing of financial PDFs and statements with complex tables.

Client Data Isolation

Client data privacy is paramount. Use namespace isolation in self-hosted Weaviate to create separate vector collections per client. At query time, the advisor's authentication context determines which namespaces are accessible. This ensures that an advisor can only query their own clients' documents and cannot access data from clients assigned to other advisors.

Meeting Preparation Automation

Before client meetings, advisors query the RAG system to instantly retrieve relevant portfolio history, past decisions, client preferences, and outstanding action items. A single query like "What did we discuss with the Johnsons about their fixed income allocation in our last meeting?" retrieves the relevant meeting notes, current fixed income holdings, and any pending rebalancing actions.

Suitability and Compliance

Portfolio RAG systems must maintain compliance with regulatory requirements for client communications. All queries and responses should be logged for audit purposes. When providing investment recommendations through the RAG system, the generated response should cite the specific IPS clause or suitability assessment that supports the recommendation.

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FAQ

How do I ensure client data privacy in portfolio RAG?
Use namespace isolation in your vector database to create separate collections per client. Deploy on-premise to keep all client data within the institution. Implement strict authentication ensuring advisors can only query their own clients.
What client documents work best for portfolio RAG?
Investment policy statements, portfolio statements, suitability assessments, meeting notes, and client correspondence all index well for RAG. Financial statements with complex tables benefit from LlamaParse for accurate extraction.
Can portfolio RAG help with client meeting preparation?
Yes β€” advisors query the RAG system before client meetings to instantly retrieve relevant portfolio history, past decisions, client preferences, and outstanding action items.

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