Kashvisor is a personal finance application that aggregates U.S. open banking data through Plaid, enabling users to view income, expenses, assets, and liabilities in one place. The platform already offered dashboard-based financial insights, but users still relied on static reports to understand their financial health. Kashvisor wanted to introduce an AI financial advisor that could provide conversational financial guidance, personalized recommendations, and interactive financial analysis.
Problem: Static dashboards limit AI financial advisor adoption
Most personal finance applications present financial information through dashboards, charts, and reports. While these dashboards help users monitor balances and transactions, they do little to explain what the numbers mean or what actions users should take. Kashvisor wanted to replace static financial reports with an AI financial advisor capable of answering questions about spending, income, debt, assets, and financial health in natural language.
The existing experience lacked conversational intelligence, personalized recommendations, and cross-account financial reasoning. Users could not ask questions such as why their monthly spending increased, whether they qualified for a personal loan, or how their liabilities compared with their income. The platform also required absolute numerical accuracy. Every recommendation had to be generated from verified financial calculations while protecting sensitive financial information and maintaining user privacy.
Solution: Conversational AI financial advisor for personalized financial guidance
GoML built an intelligent multi-agent AI financial advisor that transforms financial data into conversational insights, verified calculations, and personalized financial recommendations.
The solution combines Amazon Bedrock, specialized financial agents, and GoML's Agentic AI blueprint to understand user intent, retrieve financial data, perform validated calculations, and generate conversational responses with supporting rationale.
Conversational AI financial advisor
Example query:
Can I afford a personal loan based on my current income and spending?
Key improvements:
- Natural language financial conversations
- Multi-agent financial reasoning
- Context maintained across multiple interactions
- Personalized financial recommendations
- Interactive financial guidance with supporting explanations
Multi-agent financial intelligence
The AI financial advisor uses specialized agents to analyze different areas of a user's financial profile.
Core capabilities:
- Spending insights agent
- Income analysis agent
- Asset and retirement tracking
- Liability and debt analysis
- Orchestration agent for unified financial recommendations
Financial accuracy and recommendation engine
The solution separates financial calculations from LLM reasoning to ensure reliable recommendations.
Key capabilities:
- Verified financial calculations
- Expense aggregation across categories
- Month-over-month financial comparisons
Cash flow analysis
- Debt repayment evaluation
- Personal loan suitability assessment
- Recommendation scoring with financial rationale
Interactive user experience
The AI financial advisor delivers a conversational experience instead of requiring users to navigate multiple dashboards.
Key experience improvements:
- Ask financial questions in natural language
- Conversation history maintained across sessions
- Prompt suggestions for common financial queries
- Real-time response streaming
- Interactive financial insights within the iOS application
Quality assurance
Validation focused on financial accuracy and system reliability:
- 100 percent validation of numerical calculations
- Testing multi-agent orchestration
- Natural language query validation
- Recommendation accuracy verification
- Performance testing for concurrent users
- Security and privacy validation
Impact
- 90% or higher financial query understanding
- 100% numerical accuracy for financial calculations
- Within 5-10 seconds financial recommendations generated
- Conversational AI financial advisor replacing static financial dashboards
- Scalable API architecture for future banking and financial institution integrations
About
Before Gen AI and after Gen AI
"With an AI financial advisor, Kashvisor transformed static financial dashboards into personalized financial conversations that help users understand their finances and make informed financial decisions."
Prashanna Rao, Head of Engineering, GoML.
Key takeaways for personal finance platforms
Common challenges
- Static dashboards reduce user engagement
- Financial data is difficult to interpret
- Delivering accurate AI-powered financial recommendations requires verified calculations
Practical guidance
- Build an AI financial advisor for natural language financial guidance
- Separate financial calculations from LLM reasoning
- Use specialized AI agents for different financial domains
- Maintain conversation context for personalized financial experiences
Ready to build AI financial advisor solutions
Partner with GoML to build secure, scalable AI financial advisor solutions using Gen AI with AI Matic.
