AI-Powered Wealth Planning Digital Worker
Deploys an enterprise-grade multi-agent AI system with 8 specialized agents executing in a DAG (Directed Acyclic Graph) pattern. Validates client data with Open Banking integration, performs behavioral finance risk assessment, optimizes portfolios using Black-Litterman methodology, models tax efficiency across UK wrappers, runs 10,000 Monte Carlo simulations, validates FCA COBS 9.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Agent Control Room showing completed DAG pipeline with 8/8 agents finished in 31 seconds, processing 47,000 data points, visual workflow diagram displaying agent dependencies from Data Ingestion through Risk Profiling and Market Intelligence (parallel), Portfolio Optimization, Tax Strategy and Monte Carlo (parallel), Compliance, to Report Generation
Pipeline Results Dashboard with Risk Profile analysis showing 68/100 balanced investor score, behavioral biases detected (Recency Bias, Loss Aversion with mitigations), FCA COBS 9.2 Suitability Assessment confirmed with suggested 55-75% equity range and 12.5% target volatility
Monte Carlo Projections tab displaying 10,000 simulation scenarios with 89.3% retirement goal achievement probability, percentile outcome bands showing ยฃ1.49M pessimistic (10th), ยฃ2.46M median (50th), and ยฃ3.88M optimistic (90th) projections over 30+ year timeline
Technical Details view showing advanced architecture with Black-Litterman and Mean-Variance optimization algorithms, 10,000 Monte Carlo paths processed in under 45 seconds, AES-256-GCM encryption, ISO 27001/SOC 2 compliance, 8 specialized AI agents with individual algorithm specifications and complexity analysis
AI Agents
Specialized autonomous agents working in coordination
Data Ingestion Agent
Client financial data arrives from multiple sources (questionnaires, Open Banking, manual entry) with varying quality, requiring validation, enrichment, and normalization.
Core Logic
Validates 47+ personal and financial fields, connects to Open Banking APIs to import 2,800+ transactions, categorizes expenses using ML classification, detects income sources, retrieves credit scores, runs anomaly detection on financial data, and generates data quality scores. Enriches client profiles with derived metrics including net worth and surplus income.
Risk Profiling Agent
Determining appropriate investment risk levels requires sophisticated psychometric analysis, behavioral bias detection, and capacity assessment that goes beyond simple questionnaires.
Core Logic
Analyzes questionnaire responses using behavioral finance principles, computes multi-dimensional risk scores (tolerance, capacity, knowledge, behavioral), detects behavioral biases (recency bias, loss aversion), calculates loss aversion index, determines suggested equity ranges and volatility tolerances, and generates FCA suitability assessment with confidence intervals.
Market Intelligence Agent
Portfolio construction requires current market condition analysis including asset class expectations, correlations, risk factors, and economic indicators.
Core Logic
Fetches real-time market data feeds, computes expected returns and volatilities for 7 asset classes (global equities, UK equities, emerging markets, government bonds, corporate bonds, property, commodities), generates correlation matrices, assesses risk factors (interest rate, geopolitical, inflation, credit), monitors economic indicators, and produces timing signals (overweight/neutral/underweight).
Portfolio Optimization Agent
Constructing optimal portfolios requires sophisticated quantitative methods including efficient frontier calculation, position sizing with constraints, and multi-factor risk analysis.
Core Logic
Loads universe of 5,247 funds, applies investment constraints (maximum single fund allocation, position limits), runs Black-Litterman optimization incorporating market views, computes efficient frontier, calculates comprehensive risk metrics (Sharpe, Sortino, VaR, CVaR, maximum drawdown), analyzes sector and geographic diversification, integrates ESG scores, and generates alternative portfolios (conservative, moderate, aggressive).
Tax Strategy Agent
Optimizing investments across UK tax wrappers (ISA, Pension, GIA) requires knowledge of allowances, tax relief rates, contribution limits, and withdrawal sequencing strategies.
Core Logic
Analyzes current tax position, computes optimal wrapper allocation prioritizing pension tax relief (40%) then ISA tax-free growth, calculates annual and lifetime tax savings, models withdrawal sequencing for retirement, identifies carry-forward pension allowance opportunities, and checks high-earner considerations (personal allowance taper, pension annual allowance taper).
Monte Carlo Simulation Agent
Projecting investment outcomes requires probabilistic modeling that accounts for market uncertainty, sequence of returns risk, and goal achievement probability.
Core Logic
Initializes simulation engine with Latin Hypercube Sampling for variance reduction, generates correlated random returns, runs 10,000 simulations over the client's time horizon, computes percentile distributions (5th through 95th), calculates goal achievement probabilities (retirement income, target wealth, ruin probability), and performs scenario analysis (bull case, base case, bear case, stress test) with convergence validation.
Compliance Agent
Investment recommendations must comply with FCA COBS 9.2 suitability requirements, MiFID II appropriateness tests, Consumer Duty fair value assessments, and AML/KYC regulations.
Core Logic
Executes FCA COBS 9.2 suitability checks, validates MiFID II appropriateness, assesses Consumer Duty fair value and consumer understanding, verifies PROD target market alignment, confirms SFDR sustainability disclosures, runs AML identity verification and sanctions screening, assesses conflicts of interest, and generates risk warnings requiring client acknowledgment.
Report Generation Agent
Producing FCA-compliant suitability reports requires compiling outputs from all agents into a structured document with executive summaries, visualizations, disclosures, and audit trails.
Core Logic
Compiles executive summaries with key findings and recommendations, generates report sections (client profile, risk assessment, recommendations, projections, tax planning, compliance), creates visualizations (allocation charts, projection graphs, risk gauges), adds regulatory disclosures and risk warnings, builds comprehensive audit trails documenting data sources and algorithms, and prepares signature blocks for adviser and client approval.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
8 technologies
Architecture Diagram
System flow visualization