Lancement d'une grande banque australienne dans le secteur de la fintech

The Challenge

A major Australian bank identified Small to Medium Business (SMB) as one of the least supported groups in its customer base. Despite representing a significant portion of the economy, SMB customers were being served with products and experiences originally designed for retail or corporate segments, neither of which matched the way small businesses actually operate. The bank recognised the need for a powerful digital product specifically for SMB needs. They had innovation arms and access to vast internal and external data, but they didn't just want to improve the SMB experience. They wanted to re-imagine it entirely, and needed a partner to drive world-first innovation.

The goal was to completely re-imagine the SMB banking experience using data, machine learning, and cloud infrastructure. The bank needed a next-generation, cloud-native platform with strong focus on secure infrastructure, ease of integration with the bank's partners, and intelligent data capabilities with machine learning. Small business owners typically lack the time and resources to manage complex financial processes, so the platform had to reduce friction and deliver insights proactively rather than requiring users to search for them. This would be one of the bank's first production workloads with customer data securely deployed in AWS, making it a pathfinder for the bank's broader cloud adoption strategy.

The Approach

Kablamo launched a program of deep consultation to comprehensively map the needs of SMBs. Over the course of the two-year engagement, the team conducted over 200 hours of user testing. The research combined quantitative and qualitative methods to build a comprehensive picture of what small business owners actually needed from their bank. Interviews focused on understanding the daily financial workflows of SMB owners: how they tracked invoices, managed cash flow, reconciled accounts, and made decisions about financing and growth.

Unlike traditional design agencies, Kablamo did not let user research slow down build of reusable and flexible solution components. The product principles were established early: Integrate, Simplify, Automate. Within two weeks of kickoff, the team had a working customer landing page in AWS, animation, and mock branding. One discovery during the design process was that if a planned AI component functioned too well, it would confuse the end user, leading to careful calibration of the ML capabilities. The team learned that recommendations had to be transparent, showing the user why a particular action was suggested rather than presenting conclusions without context.

• 200+ hours of user interviews balanced with rapid product development over a two-year engagement
• Intelligent data platform with machine learning capabilities for data-driven insights
• Secure cloud infrastructure deployed in AWS, one of the first production workloads for the bank
• UX testing to hone algorithm outputs and recommendations
• Accounting integration connecting the platform to existing financial tools used by small businesses

The Results

The platform launched into a closed pilot within 12 months of kickoff. The three-month pilot ran with 10 real customers using their actual banking data. Features built included an accounting solution, financing options, ASP integration, and invoice reminders and alerts. Over 500 user interviews were conducted and 200 hours of user testing completed throughout the engagement.

This was one of the bank's first production workloads, including customer data, securely deployed in AWS. It marked a major step for the bank to become cloud-based, agile, and future-ready. The pilot validated that SMB customers responded positively to proactive, data-driven insights integrated directly into their banking experience, rather than having to seek out information through separate reporting tools. The machine learning components provided meaningful recommendations while remaining transparent enough for users to trust and act on. The secure AWS deployment established patterns and governance that the bank could apply to subsequent cloud workloads across its broader technology portfolio.

Looking Forward

The platform delivered new customer value via an intelligent data platform using machine learning and a strong customer experience. The engagement demonstrated that deep user research and rapid product development can run in parallel without one slowing the other.

The approach of running deep user research in parallel with rapid product development proved that a bank could build and test new digital products at startup speed while maintaining the rigorous security and compliance requirements expected of a major financial institution. The engagement established a model for how large banks can approach digital product innovation: combining deep domain understanding (through hundreds of hours of direct customer research) with rapid technical execution (through cloud-native architecture and reusable components). The patterns established during this engagement, particularly around secure AWS deployment and ML-driven customer insights, became reference architectures for the bank's subsequent digital initiatives. For Kablamo, the project demonstrated the value of treating user research not as a phase that precedes engineering, but as a continuous input that shapes the product throughout its development lifecycle.