Unlock AI power: financial services beyond legacy

In today’s fast-changing financial landscape, organisations face a pivotal choice: continue relying on outdated legacy systems or embrace modern cloud-based data platforms that unlock the full power of AI and analytics. This decision will shape which institutions thrive in the years ahead.

 

The legacy burden: understanding the true cost

 

For decades, financial institutions have built complex webs of legacy technology that are increasingly hard to maintain, integrate and scale. As recently as 2021, 92 per cent of UK financial services companies still relied on legacy systems, with 78 per cent of their data locked in on-premises infrastructure. This dependence creates several pain points:

 

Data silos and integration challenges. Disparate systems trap customer data, transactions and risk assessments in isolated repositories, making it nearly impossible to gain a unified view of operations or customers.

 

Limited scalability. Legacy systems often struggle during peak demand, causing delays or outages, or forcing costly overprovisioning. This inflexibility makes real-time response to market changes difficult.

 

High maintenance costs. Maintaining old infrastructure consumes a growing share of IT budgets. Specialised talent for legacy systems is scarce and expensive, pulling resources away from innovation.

 

Compliance complexity. As regulations evolve, legacy systems require costly, time-consuming updates to stay compliant, increasing operational risk and diverting attention from strategic initiatives.

 

Innovation constraints. Most critically, legacy architectures limit the ability to implement AI and advanced analytics at scale. As competition intensifies from fintech disruptors, this innovation gap threatens long-term market position.

 

The AI data opportunity: beyond the hype

 

While many financial institutions recognize the need for modernization, true transformation requires more than incremental upgrades. The convergence of cloud computing, advanced analytics and AI is creating unprecedented opportunities for those willing to rethink their data architecture.

 

The industry is moving from the “blue sky” promise of AI to practical, value-driven implementations. Leaders are now focused on generating measurable returns from AI, not just experimenting. As Rinesh Patel, Global Head of Financial Services at Snowflake, notes, “It will no longer be enough to say your organisation is merely using AI. Organisations must actually be driving value from their AI implementations.”

 

AI’s real value is found in practical, business-driven applications:

 

Operational efficiency. AI automates routine tasks and enhances decision-making. For example, State Street Alpha achieved a 25-times productivity boost by deploying AI models that reduced false positives by 87 per cent while maintaining 100 per cent detection of true exceptions.

 

Unstructured data analysis. Financial firms generate vast amounts of unstructured data, from loan agreements to call recordings. Modern AI can extract insights from these resources, enabling better segmentation, service and risk assessment.

 

Enhanced risk management. AI and analytics improve pattern recognition and predictive modelling, enabling more accurate fraud detection, credit risk assessment and compliance monitoring.

 

Personalised customer experiences. By analysing customer behaviour, institutions can deliver highly personalised services, improving satisfaction and retention while identifying new revenue opportunities.

 

The modern data architecture solution

 

Addressing these challenges requires more than new technology – it demands a fundamentally different approach to data management. Modern, secure, interoperable platforms provide the foundation for transformation. Migrating to a modern platform offers several distinct advantages:

 

Separation of storage and compute. Decoupling storage and compute lets organisations scale each independently, ensuring optimal performance and cost efficiency.

 

Seamless data sharing. Modern platforms enable secure, governed data sharing across organisational boundaries without duplicating data, facilitating collaboration while maintaining control and compliance.

 

Unified data access. Bringing together structured, semi-structured and unstructured data in a single platform eliminates silos and enables a comprehensive view of business, customers and markets.

 

Built-in security and governance. Advanced security features – end-to-end encryption, role-based access controls and dynamic data masking – protect sensitive information while allowing appropriate access.

 

Elastic scalability. Cloud-native platforms automatically scale to meet demand, ensuring consistent performance without manual intervention or capacity planning.

 

The path forward: practical steps for transformation

 

For financial services organisations looking to break free from legacy constraints and capitalise on the AI revolution, several key steps can help ensure a successful transition:

 

Begin with clear business objectives. Identify specific business challenges or opportunities where data modernisation can deliver the most value – such as enhancing customer experience, improving risk management or streamlining operations.

 

Develop a phased migration strategy. Rather than attempting a complete overhaul, use a staged approach that addresses high-value use cases first, minimising risk and demonstrating early wins.

 

Build a modern data foundation. Implement a unified platform that brings together disparate data sources, provides seamless access across the organisation and supports advanced analytics and AI.

 

Foster a data-driven culture. Technology alone isn’t enough. Invest in training, change management and organisational alignment to build a genuinely data-driven culture.

 

Implement strong governance. As data becomes more accessible and powerful, robust governance is even more critical. Establish clear policies, controls and monitoring to ensure regulatory compliance and ethical use of data.

 

The future is now

 

Financial services organisations face a clear choice: continue struggling with legacy limitations or embrace modern data platforms for innovation, efficiency and growth. The leaders of tomorrow are already making this transition – breaking down data silos, implementing cloud-native architectures and leveraging advanced analytics and AI to transform operations and customer service. In doing so, they’re not just solving today’s challenges – they’re positioning themselves to capitalise on future opportunities their competitors can’t even imagine.

 

The era of AI in financial services has arrived, but its benefits will not be evenly distributed. Organisations that build the right data foundation now will be positioned to thrive in this new landscape, while those that cling to legacy systems risk being left behind. The choice is clear, and the time to act is now.

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Want to learn more about how Snowflake can help your financial services organization break free from legacy constraints and unlock the power of your data? Click here or contact our financial services team today.

 

Ready to dive deeper? Watch the Accelerate Financial Services webinar on demand to see how industry leaders are transforming with Snowflake.

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Felicitas Humphrey, Senior Product Marketing Manager – Financial Services EMEA, Snowflake