AI Banking Hackathon: What Once Took 3 Days Now Takes 10 Minutes
Personetics brought together various teams from across the organization for an AI hackathon focused on helping banks implement new technology. Here’s what they found.
By Roy Harel, Chief Delivery Officer, Personetics
Eighteen teams. Six hours. One challenge: find faster ways to help banks implement new technology.
When we launched our recent hackathon at Personetics, we brought together teams from across our organization – primarily professional services with additional expertise from R&D and support. After all, who better understands what banks need than the specialists who help them build better digital services?
As a company whose AI-powered insights already help one million customers save over $200 million monthly through assistive technologies that summarize content and reduce manual labor, we’re always looking for ways AI can make banking work better. This hackathon let us put that idea to the test.
The response surpassed our expectations. Eighteen teams formed, ranging from two to seven people, bringing together professionals from across our organization – primarily professional services with additional expertise from R&D and support. Each team brought fresh ideas about making technology implementation simpler and faster, using their first-hand experience with banks’ implementation challenges.
Key Takeaways for Improving Tech Implementation
One of our winning teams showed the incredible power of AI in banking technology: they developed an AI-powered approach to SDK integration that finished a project in 10 minutes that usually takes three days or more. The current SDK integration process typically involves extensive documentation review and multiple consultation sessions with our team – a complex process that can sometimes"stretch beyond a week. When banks add new features to their mobile or web applications, they often get stuck on technical details that slow everything down. This dramatic improvement in speed shows how AI can help banks bring new services to their customers sooner.
Another innovative team tackled a different challenge: creating synthetic data that mimics customer information for testing purposes. This addresses a significant pain point for banks, as generating realistic test data has traditionally been a time-consuming process that can delay implementation.
The hackathon taught us three important lessons about implementing banking technology:
First, AI is particularly good at handling complex technical tasks automatically. This frees up banks’ technical teams and Personetics’ Professional Services teams to focus on what makes their services unique instead of getting bogged down in basic setup work. The automation of these processes not only increases efficiency but also improves quality across the board.
Learn more:
- Why AI Agents May Be the Tech to Finally Deliver on Personalization
- AI and the Future of Financial Services: The View from Davos
- Personalization and Accessibility: Are Banking Apps Doing Enough?
Second, the best solutions come when people who understand banking work closely with technical experts. Together, they create practical solutions that actually work in the real world. The diversity of perspectives – from those working directly with banks to those developing the underlying technology – leads to more comprehensive and effective solutions. As we discovered, some of the brightest ideas came from our people on the ground, those who deal with implementation challenges daily.
Third, AI can significantly speed up work without cutting corners on quality. This means banks can respond more quickly when their customers need something new. The dramatic reduction in SDK integration time proves that AI can change traditionally complex, time-consuming processes into streamlined operations.
For banks choosing new technology partners, this matters because faster implementation means they can improve their services sooner. Banks that can quickly add new features have a real advantage in serving their customers better.
The hackathon revealed something else valuable: the power of group brainstorming and diverse thinking in driving innovation. When we brought together teams with different perspectives and experiences, we saw how collaborative problem-solving could lead to breakthrough solutions. The teams from Professional Services brought their deep understanding of banks’ implementation challenges, while R&D contributors added their technical expertise. The combination proved to be exactly what we needed to solve real problems.
The future belongs to banks that can both create useful features and get them working quickly. AI is making this possible by simplifying complex technical work, helping banks spend less time on setup and more time on serving customers. Our hackathon showed that when you combine AI’s capabilities with the insights of those who work directly with banks, you can achieve dramatic improvements in efficiency and implementation speed – transforming what once took days into a matter of minutes.
