It is not the first time the financial services industry has looked to AI-powered solutions with curiosity and enthusiasm. Before the pandemic and release of OpenAI, financial professionals implemented early chatbots and data analysis tools, however, adoption rates remained low, and the focus shifted towards remote work and digital communication.
Once OpenAI released ChatGPT in late 2022, interest reemerged. According to Goldman Sachs, the financial industry is among the sectors most likely to embrace the change due to advancements in the natural language processing technology – their white paper from mid-2024 predicts the usage to double to 10% by 2025. Moreover, the perspectives of leveraging natural language processing technology in the financial industry are very promising, especially if the capabilities of large language models are combined with more conventional, structured analytical tools.
Large language models (LLMs) excel at interpreting user input and translating the output of financial models, significantly democratising access to professional analytics for employees and clients alike. At Kidbrooke®, we have developed Kate, a GenAI-powered solution that enhances financial institutions’ capabilities by automating internal processes, streamlining compliance and customer support, and elevating client-facing journeys. In this blog, we explore how financial institutions can leverage all KidbrookeONE capabilities through Kate, address common risks associated with modern large language models, and showcase how our customers employ this augmented solution.
Meet Kate: LLM for communication, KidbrookeONE for calculations
Kate by Kidbrooke® offers seamless access to structured financial analytics through natural language interactions. By integrating a large language model (LLM) with the KidbrookeONE platform, Kate enables financial institutions to address employee and customer queries using reliable, model-driven calculations. Utilising context-aware memory, it retains pertinent financial data, ensuring conversations remain consistent and compliant. This approach captures complex relationships between financial variables without restricting user expression to predefined commands. Consequently, Kate adeptly handles traditional knowledge-based searches and more complex tasks involving the evaluation, analysis, and processing of financial data.
The analytics of KidbrookeONE reduces the chances of hallucinations that often render GenAI solutions unreliable for process automation in finance. However, a few more safeguards are in place to mitigate risks of faulty responses. When the user’s input is perceived as ambiguous, Kate would reach out to confirm their intentions. Moreover, Kate provides an auditable track of calculations and the underpinning assumptions next to each of the responses for transparency and compliance.
One important advantage of Kate is the versatility of tasks the platform can perform. The combination of balance sheet-level analytics, data management and processing capabilities of KidbrookeONE with LLMs empower your employees to streamline administrative, compliance and even client-facing processes within your organisation without developer skills.
Empowering a life insurer with cutting-edge customer support
Customer support teams in financial institutions manage a high volume of inquiries, often relying on manual searches through databases, policy documents, and historical cases. This process can be slow, inconsistent, and resource intensive.
A leading UAE-based life insurer has recently leveraged Kate by Kidbrooke to streamline its customer support operations, replacing manual ticket resolution with instant, AI-powered information retrieval and processing. Thanks to Kate’s contextual memory and analytics, responses are both prompt and accurate—reducing resolution times and the risk of conflicting information. Its ability to understand financial context and process structured data alongside policy documentation allows for faster, more precise ticket resolution, making support more efficient, personalised and scalable.
By automating the resolution of customer queries and ensuring consistency across responses, Kate reduces processing times while freeing up human agents to focus on complex cases. This enables financial institutions to improve customer satisfaction, reduce operational costs, and enhance the reliability of their support processes—a critical advantage in a highly regulated industry.
AI-powered compliance and quality control: enhancing efficiency with Kate
Kate by Kidbrooke® also enhances compliance by analysing all documentation at scale, moving beyond traditional random sampling. This ensures firms identify inconsistencies more effectively, reducing risks and inefficiencies. By ranking documents based on quality and highlighting those requiring human review, Kate streamlines compliance workflows and prioritises resources where they are needed most.
This targeted approach reduces oversight risks, improves quality control, and minimises administrative burdens. As a result, compliance teams operate more efficiently, enhancing regulatory adherence in a highly controlled environment.
Kate by Kidbrooke® – The next trend in engaging financial experiences
While many in the industry remain cautious about allowing GenAI-powered tools to analyse customers’ financial situations, Kate is designed to support decision-making rather than replace human oversight. Kate by Kidbrooke® enhances both adviser-led and client-driven financial planning by integrating real-time analytics with a natural, conversational interface.
For financial advisers, Kate provides instant access to financial modelling, internal data and investment projections—without the need for manual data gathering. This enables faster; tailored recommendations aligned to client goals in real-time.
For end-users, Kate transforms financial planning into an interactive experience. Instead of navigating rigid forms or static dashboards, clients can engage in a fluid, AI-driven dialogue, where Kate proactively asks relevant questions, generates real-time projections, and evaluates investment scenarios. This dynamic approach ensures that users receive personalised, high-quality guidance while making informed financial decisions.
By bridging the gap between robust financial analytics and seamless, intuitive interactions, Kate can redefine how financial institutions engage clients, enhance advisory services, and drive better financial outcomes at scale.
AI in finance – The road ahead
The financial services industry is at a pivotal moment in adopting generative AI. Unlike previous AI trends hindered by technical and regulatory challenges, current advancements offer tangible business cases and efficiency gains. With adoption rates doubling and AI-driven cost savings projected to reach hundreds of billions of dollars, firms integrating AI effectively will gain a significant competitive edge.
Yet, financial institutions are approaching AI with a balanced mix of ambition and caution. Industry leaders recognise the risks of AI-generated inaccuracies, data security concerns, and the need for strong regulatory compliance. As a result, the focus has shifted from uncontrolled experimentation to responsible AI implementation—deploying GenAI in areas where it can enhance human expertise, improve decision-making, and optimise operational efficiency without compromising trust and compliance.
Kate by Kidbrooke® enhances AI in finance by augmenting, not replacing, human oversight. It combines natural language processing with financial analytics to ensure reliability, transparency, and compliance. From automating customer support to streamlining compliance and financial planning, Kate helps institutions harness AI while maintaining control and accuracy. As AI adoption grows, firms using scalable, compliant solutions like Kate will lead the future of financial intelligence.
Discover how Kate can transform your operations—get in touch today to learn more or book a demo!
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