Throughout my career, I have witnessed several significant fintech advancements. However, none have been as groundbreaking as the current artificial intelligence (AI) revolution and its impact on managing unstructured data. This is much more than just another
tech trend – it redefines how businesses handle information across financial services.
This is an excerpt from The Future of AI in Financial Services
2025 report, which was a special edition for the inaugural Finextra event, NextGen AI. Click here to read the report.
The unstructured data challenge
Organisations within financial services are drowning in unstructured data, in fact,
according to the IDC, 90% of an organisation’s data is unstructured. Prospectuses, loan applications, policy documents, financial planning reports, and transaction records all contain insights, yet their value remains largely untapped. Since this information
is dispersed across various systems and file formats, it becomes incredibly challenging to analyse and leverage effectively.
The consequences of data fragmentation are significant. It hampers risk assessment accuracy, impedes regulatory compliance efforts, presents a risk to both security and privacy, and critically hinders the development of innovative financial products tailored
to market demands. The question then becomes – How can financial institutions transform this unstructured data into strategic gold?
The catalyst for data-driven transformation
Integrating generative AI and large language models (LLMs) into an intelligent content management platform offers a compelling solution. By leveraging advanced natural language processing and machine learning techniques, AI can decode unstructured data,
extract metadata, and deliver precise insights quickly.
In risk management, AI-driven analyses of unstructured data can uncover nuanced risk indicators often missed by traditional methods, enabling more robust risk assessment. This streamlined approach allows businesses to make more informed decisions. AI can
significantly enhance compliance monitoring through the automated processing of regulatory documents. The result is reduced costs and minimised regulatory exposure.
Finally, the greatest value comes from AI-powered automation, which significantly improves operational efficiency, reduces costs and enhances accuracy and speed. This efficiency empowers businesses to strategically allocate resources, prioritising high-value
activities and customer relationships.
The implications of these capabilities are profound. Financial institutions that successfully deploy AI to unlock the value of their unstructured data will optimise their operations, provide a frictionless customer experience, and gain a significant competitive
edge in a data-driven market.
A competitive edge
The impact of AI on unstructured data is much more than an incremental improvement – it is making organisations rethink how they operate. The industry is moving away from the view that data management is a potential bottleneck, with AI now emerging as the
catalyst for data-driven innovation, efficiency, and customer experience. It’s a streamlined approach that provides a competitive edge.
Imagine being able to instantly extract key information from thousands of loan applications, predict market trends with unprecedented accuracy, or identify fraudulent activity before it escalates. This isn’t science fiction — it’s a new reality that advanced
AI tools are beginning to deliver.
More than half of CEOs within financial
services acknowledge that AI will create a competitive advantage, highlighting its growth in the industry’s strategic planning. The message is clear: embracing this technology is key to staying ahead and unlocking new opportunities for growth and innovation.
Supporting the human element
While the technical capabilities of AI are impressive, its real value lies in how it supports financial professionals.
By introducing AI into workflows, businesses can dramatically reduce the time spent on repetitive, data-intensive tasks. This allows valuable human resources to focus on what they do best: building relationships, providing expert advice, and making decisions
that require emotional intelligence and industry expertise.
In wealth management, AI can quickly analyse market trends, client portfolios, and risk factors, providing advisors with comprehensive insights. This empowers advisors to better understand their clients' unique needs and goals and build deeper, more trusting
relationships. Instead of being preoccupied with data, advisors can focus on meaningful conversations, leading to better client outcomes and increased satisfaction.
In lending, AI can handle the initial stages of loan application processing, freeing loan officers to focus on complex cases requiring human judgement. This speeds up the overall process and allows for a more personalised service in challenging situations,
leading to better risk assessment and customer experience. Similarly, in banking, AI-powered virtual data rooms (VDRs) can streamline due diligence by providing insights across complex financial statements, operational documents, employee records, and technology
throughout the lifecycle of a deal – reducing costs, time, and the risks associated with complex transactions.
The insurance sector similarly benefits. With AI handling routine claims and policy analyses, agents can dedicate more time to complex claims, customer education, and developing tailored insurance solutions. A human touch, supported by AI-driven insights,
can significantly enhance a customer’s loyalty and trust.
By adopting AI, financial institutions aren’t replacing their workforce - they’re making it smarter and accelerating business.