Jamie Allsop
Managing Partner Financial Services, HTEC
Technology has always played a pivotal role in banking and insurance. The rapid acceleration of AI capabilities is fundamentally re-shaping how financial institutions serve customers and structure their operations.
Most established financial institutions face the same significant challenge: moving beyond treating AI as merely an efficiency driver.
AI as the strategic core in finance
The legacy approach of spending 70% of IT budgets* on ‘keeping the lights on’ is giving way to a new paradigm where AI forms the backbone of enterprise strategy, enabling entirely new capabilities in product design, service delivery and business model evolution.
This shift demands a rethinking of AI’s role as the central organising principle for modern financial institutions. The opportunity lies in orchestrating intelligent, adaptive systems that learn and evolve across the enterprise.
At HTEC, we’ve seen firsthand how AI-first solutions can offer a transformative path forward. Rather than simply layering new technology onto legacy systems, forward-thinking institutions are using AI to fundamentally reimagine their customer journeys and operational models.
Agentic AI unlocks value from all data
The most forward-thinking institutions are using AI to extract value across both structured and unstructured data sources. By processing everything from transaction records to client communications and market signals, these intelligent systems continuously learn, reason across domains and autonomously take action.
In one financial workflow platform modernisation project, this approach accelerated user registration by 400% and achieved perfect 10/10 stakeholder satisfaction. For another client, it enabled a reduction in integration timelines from eight weeks to three days while cutting mapping effort by 80%. These are tangible examples of AI’s transformative power when applied across data types.
Forward-thinking institutions are using
AI to fundamentally reimagine their
customer journeys and operational models.
Customer expectations redefined by genAI
As consumers grow accustomed to AI-powered, personalised digital experiences in other industries, they now expect the same from their financial services providers. This new standard for digital engagement means institutions must deliver intuitive, conversational interfaces, proactive financial guidance and highly tailored interactions.
HTEC’s AI solutions have responded to this shift. Internal success surveys found that for one customer in tech protection insurance, our solutions achieved 60% faster claims resolution, 30% faster subscriber onboarding and 99.9% system uptime. These are critical metrics for an industry where customer trust depends on reliability and responsiveness. The result isn’t just cost savings; it’s enhanced service quality and the ability to reach previously underserved markets. Similarly, for a major payment processor, we achieved a 50% reduction in processing time, with over $5 billion processed in the first two years.
End-to-end transformation requires a holistic approach
Successful AI transformation spans the full technology and business stack, from model development and process redesign to responsible AI governance and change management. The challenge is clear: how to scale AI responsibly while meeting intensifying regulatory demands and ethical obligations.
For a banking-as-a-service provider, our holistic approach to navigating complex Payment Card Industry Data Security Standard (PCI DSS) requirements while implementing AI systems resulted in $100,000 annual cloud savings and 50% fewer support tickets, according to another user success survey. This demonstrates that compliance can be a business enabler rather than merely a cost centre.
Strategic AI adoption in finance
For financial services leaders, the question is no longer whether to implement AI, but how to do so strategically while managing legacy constraints. The organisations gaining a competitive advantage are taking a three-pronged approach:
- Prioritising high-impact use cases that deliver tangible business value
- Implementing a data infrastructure that can support advanced AI applications
- Developing talent strategies that blend financial expertise with AI capabilities
The financial institutions thriving in this new landscape aren’t necessarily those with the largest technology budgets. Rather, they’re the ones most effectively bridging the gap between customer needs, operational realities and technological possibilities.
*Source: Woollacott, E. 2025. IT Pro. Banks are persisting with the ‘patch and upgrade’ approach to legacy systems – and it’s swallowing up IT budgets.
