Join us on this week's episode of the Slice of Finance podcast, hosted by Jared S. Taylor!

Our Guest: Edward Maslaveckas, Co-Founder & CEO at Bud.

What you’ll get out of this episode:

• Why Banks Struggle with Data – Despite having vast amounts of transaction data, most banks lack the ability to effectively process and leverage it for personalization.

• Improving Customer Experience – Bud Financial helps banks reduce customer confusion over unidentified transactions, saving them millions in customer service costs.

• What Real Personalization Looks Like – Ed explains how AI-driven insights can help banks better serve their customers, offering timely nudges and financial advice.

• Lessons from Scaling a Fintech Business – From early missteps to finding product-market fit, Ed reflects on Bud’s journey to profitability.

• The Future of AI in Banking – Bud Financial is integrating more advanced AI models to enhance financial management for both institutions and consumers.

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The Problem: Banks and Their Data Blind Spots

Many people assume their bank knows everything about their spending habits. After all, banks have access to transaction data, right? Yet, customers often receive irrelevant product offers, and many struggle to recognize transactions on their statements.

According to Ed, this is because most banks lack the infrastructure to process transaction data effectively. Bud Financial steps in to bridge this gap, using AI to help banks interpret financial data and provide meaningful insights to customers.

Solving the Mystery of Unknown Transactions

One of the biggest issues banks face is handling customer complaints about unrecognized transactions. These inquiries cost banks anywhere from hundreds of thousands to tens of millions of dollars each year. Bud’s AI-powered insights allow banks to:

• Identify merchants and transaction patterns more accurately.

• Provide customers with clearer spending records.

• Reduce the volume of unnecessary fraud claims and customer service calls.

What Good Personalization Looks Like

Financial institutions talk a lot about personalization, but true personalization means knowing a customer better than they know themselves. Bud’s AI-driven approach enables banks to:

• Alert customers when they may not have enough funds for an upcoming bill.

• Identify opportunities to consolidate loans for better financial management.

• Provide relevant, timely financial product recommendations based on actual spending behavior.

Lessons Learned: The Challenges of Building a Fintech Business

Bud Financial has been on a 10-year journey, and the road to product-market fit has been anything but smooth.

• Early Missteps – The company initially helped large banks launch challenger banking apps, only to see those projects scrapped when banks decided to take control in-house.

• Scaling Challenges – Unlike the rapid-growth SaaS businesses often celebrated on social media, Bud’s path has required years of refining its AI models and data accuracy.

• Cultural Learnings – The company experimented with flattening hierarchy and granting full autonomy, only to find that too much freedom can create inefficiencies.

The Future: AI-Driven Banking & Agentic Models

Looking ahead, Bud Financial is exploring agentic AI models, which will allow financial institutions to:

• Automate complex financial processes internally.

• Enhance customer interactions with AI-driven financial advisors.

• Optimize money management, making financial decision-making easier for individuals.

With banks historically being slow adopters of new technology, Bud is taking a strategic approach to integrating AI in a way that balances innovation with risk management.

Final Thoughts

Bud Financial is at the forefront of AI-driven banking insights, helping financial institutions transform their customer experience and improve operational efficiency. As the company moves toward profitability and further develops its AI capabilities, the future of banking looks increasingly data-driven and customer-centric.

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