Finshape AI Financial Assistant - The Future of Personal Finance is Conversational

An Interview with Sára Hanniker, AI Expert at Finshape 

At Finshape, we believe the future of finance is not just digital—it’s conversational. We sat down with our in-house AI expert, Sára Hanniker, to explore how our next-gen agentic AI financial assistant helps users gain real insights into their finances, plan smarter, and act instantly, all through natural conversation. 

Sára, can you tell us in simple terms - what exactly is the AI financial assistant? 

Sára:
Think of it like a personal finance coach, powered by the latest in artificial intelligence. Our AI financial assistant uses a complex multi-agent workflow built on advanced large language models, allowing it to understand and respond to users in clear, human language.

You can ask it questions like:

• “How much did I spend on subscriptions last month, and how did that change over time?” 
• “Can I afford a vacation in July?”

The assistant will provide personalized, contextual insights based on your real financial data. What sets it apart is that it doesn’t just respond in text—it creates charts, widgets, and interactive visuals that make even complex financial data easy to understand."

What are the main things it helps users with? 

Sára:
The AI financial assistant focuses on three high-impact areas:

1. Understanding finances – Asking anything about income trends and spending habits
2. Setting savings goals – Helping users achieve short-term financial goals
3. Budgeting – Optimizing expenses and regular monthly savings Daily, monthly, or category-specific planning

The assistant’s ability to explain financial concepts in plain language makes it approachable—even for users with limited financial literacy.

How is this different from typical banking chatbots? 

Sára:
Most banking chatbots today rely on rigid, rule-based flows. They’re limited in scope and often provide canned responses. Ours is completely different.

Our AI financial assistant is built with agentic AI architecture, meaning it can dynamically orchestrate different “agents” that handle various financial topics. Right now, we focus on domains like everyday finance, short-term planning and expense optimization —but in future iterations, we could add agents for investments or credit analysis.

So while it doesn’t answer everything yet, within its scope, it offers full flexibility. If the answer exists in your financial data, the assistant will find it—and explain it in a way that makes sense.

Does it help users visually understand their data? 

Sára:
Absolutely—this is one of the biggest strengths of our AI financial assistant. Our assistant delivers

• Pie charts showing where money is going
• Bar and line graphs to track spending habits and income over time
• Interactive transaction lists for digging into details
• Widgets tailored for specific needs

 Can users take action directly within the chat?

Sára:
Yes—and this is where the assistant becomes more than just informative. It’s actionable. Right within the chat, users can:

• Set or adjust savings goals
• Set up regular transfers
• Create or edit budgets
• Accept, discuss and iterate smart suggestions based on their habits

The assistant is deeply integrated into the mobile banking experience, bridging the gap between insights and action. IIt becomes a true decision-making companion, not just an information tool.

How does it get smarter over time? 

Sára:
AI is evolving rapidly—and so is our assistant. We’re building long-term conversational memory so it can understand not just the current question but also the context from previous sessions. Over time, it becomes more personalized and helpful.

How can banks actually implement this? 

Sára:
It’s easy to achieve promising proof-of-concept results quickly, but that’s often a trap—it’s far from deployment-ready. The true differentiator in the industry is who can deliver customer-facing AI applications.

Key implementation factors are:

• We created a professional testing and evaluation framework to assess performance. This is crucial.
• By adding AI guardrails to counter the weaknesses of large language models—which can be easy to manipulate—we make the system more responsible and safer.
• We also comply with the EU AI Act.
• Mobile banking integration is actually one of the easier parts.
• Beyond that, data quality remains a key factor. The AI Financial Assistant can only be as accurate as the data banks provide.

Summary: Why Our AI Financial Assistant Matters  

Here’s why our solution is a game-changer: 

• Natural UX → Users talk like humans, not robots 
• Insightful Visualization → Clear, interactive financial views 
• Unlimited Questions → Ask anything, anytime 
• Action-Oriented → Set goals, budget, and transfer money directly 
• Agentic Architecture → Built for intelligent, scalable financial conversations 
• Real Engagement → Drives user satisfaction and loyalty 

According to McKinsey’s 2025 AI report², leading organizations are shifting from experimentation to full-scale deployment of AI. 80% of financial services leaders expect at least 2x ROI from AI investments, and over 60% report 5%+ cost reduction from AI implementation . The opportunity is massive—and very real. Our AI financial assistant reflects that maturity—it’s live, integrated, and ready to scale.

Final words from Sára

“We’re not just building a chatbot. At Finshape, we’re building real agentic AI systems—tailored, tested, and developed in-house. Our mission is to empower every banking customer to feel confident and in control of their financial life. And the AI financial assistant is just the beginning.”

Ready to bring real conversational AI into your mobile banking experience?
Contact Finshape to learn how our AI financial assistant can transform your customers' money management. 

Source: 

• McKinsey: The State of AI – How Organizations Are Rewiring to Capture Value