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7 min read
14th Jan 2025
The financial services industry has always relied on trust, speed, and personalisation. Today, those qualities are being tested like never before. Customers want solutions at the speed of thought, whether it’s a quick query about their account balance or advice on where to invest. At the same time, fintech start-ups are shaking up the industry with digital-first experiences.
Enter conversational AI. Applied correctly, it can turn reactive customer service into proactive engagement, slash operational costs, and even act as a defense against fraud. The deployment of conversational AI in financial services means overcoming some hurdles—from making sure your technology meshes nicely with legacy systems to navigating treacherous regulatory waters.
This guide is less about the hype and more about the reality. What’s working? What’s next? And how can you use conversational AI most effectively?
Today’s conversational AI uses natural language processing (NLP), machine learning, and generative AI to simulate human conversations with incredible nuance. Coupled with technology like retrieval augmented generation (RAG), it can know your business inside and out, and provide real-time insights to your employees and customers.
For the financial sector, this means tools that don’t just answer, “What’s my balance?” but can also analyse spending patterns, suggest smarter saving options, or flag suspicious activity—instantly.
This shift towards greater automation and more advanced AI agents signifies a revolution in the financial services industry. For example, Gartner believes in 2025, 85% of customer service leaders will be exploring conversational GenAI.
There are several key hallmarks of conversational AI that make it unique:
Such AI assistants have a range of applications across numerous industries and these features make them incredibly versatile.
The applications for AI in the financial world are only just starting to be explored, with some unique and exciting use cases already in place:
Financial institutions get bombarded with repetitive inquiries:
Conversational AI automates these, freeing up human agents to handle more complex cases. In a separate article, we’ve explored how you can calculate your Customer Satisfaction Score (CSAT) and how AI assistants can help you improve it.
Fraud doesn’t sleep, and neither should your response system. Conversational AI can monitor transactions in real time, flagging anything suspicious and notifying customers instantly. A well-trained AI doesn’t just spot issues faster—it does so with fewer false alarms, making sure human agents are only looped in when matters need their urgent attention.
With conversational AI now affordably available for all financiers, access to financial advice is no longer exclusive to wealthier clients. Robo-advisers powered by conversational AI can analyse anyone’s risk profile and goals alongside market trends to offer tailored investment strategies for all. It’s like having a personal financial planner—without the price tag.
Nobody enjoys filling out loan applications or waiting weeks for an answer. Conversational AI speeds up the process by automating eligibility checks and document verification. For example, customers can upload documents via chat, receive real-time feedback, and track their application status—all through talking with an AI assistant.
It’s not just about customers. Internal AI-powered chatbots can guide employees through compliance protocols, answer HR-related queries, and improve onboarding experiences. Using AI tools can help uncover new efficiencies, freeing up the time of human employees to focus on higher-value tasks.
Legal & General (L&G) faced a significant challenge when customer enquiries skyrocketed during the pandemic. Overwhelmed by the volume of calls, they needed an AI assistant that could handle complex, personalised conversations while adhering with strict regulatory and security standards.
Solution: L&G worked with us to launch the SmartHelp AI assistant, which was trained to manage 95% of routine insurance queries with minimal human intervention. The AI assistant seamlessly integrated with their policy systems to provide instant answers to requests like policy renewals, claims processing, and cancellations.
Results:
Notably, L&G also gained deeper insights into customer behavior through the analysis of their AI assistant data, allowing them to quickly adapt services, such as providing insurance information for garden offices during the remote-work boom, and improve customer satisfaction with speedier, more relevant responses.
This example shows how conversational AI not only improves operational efficiency but also helps businesses adapt in real time to shifting customer needs.
Getting started with your conversational AI is pretty straightforward. With AI Studio, you can get up and running with your AI assistant in less than 10 minutes, but before you finalise your AI plans, consider these factors:
Every tech investment needs a business case, but you won’t get a return on investment using GenAI alone. The most sensible approach is to start with your pain points:
Pinpoint the problem, then articulate how conversational AI can help solve it.
Introducing AI has the potential to be challenging when teams don’t agree early. Pull in IT, compliance, customer support, marketing and sales, and all senior leadership from the start. Speak their language—show how AI improves their specific priorities, whether it’s cost savings, better compliance reporting, or automating lead capture.
If you’re in financial services, there’s no cutting corners. From GDPR to the EU AI Act, your AI assistant must have robust security and information management. Use an AI assistant provider with proven experience in protecting your customer and company data, and expert knowledge of compliance and regulation standards you’ll need to meet.
Don’t try to boil the ocean. Start small—maybe with automating FAQs—and iterate. Pilot programmes can help you iron out integration kinks before rolling out at scale.
Conversational AI isn’t “set it and forget it”. Use feedback loops and key performance metrics (like customer satisfaction or response accuracy) to continually refine your system to meet key goals. Make sure you have a human in the loop to monitor AI performance and review suggestions, so your conversational AI is always performing at the top of its game.
Financial institutions that adopt conversational AI today will have a leading edge tomorrow. The future lies in human-AI collaboration, where technology handles the heavy lifting and humans focus on high-value, relationship-driven tasks.
Stay curious. Large language model (LLM) innovations and generative AI are transforming the way businesses operate, AI telephony is starting to fix expensive, broken phone systems, and AI agents are about to disrupt the future of work in ways we can’t yet even comprehend.
One thing is certain, the pace of change isn’t slowing down.
Conversational AI isn’t just a tech trend—it gives you a strategic advantage. Whether it’s helping customers manage their finances or safeguarding customers against fraud, AI assistants are changing the game in financial services. The key is to approach the technology with clear objectives, a focus on compliance, and a willingness to adapt.
Any conversational AI platform you use must have enterprise-grade security with robust security measures, otherwise you’re putting your own data and customer data at risk. The platform must also comply with regulations like GDPR and meet accessibility standards, plus provide an audit trail for transparency and protection ― the costs and commitment involved to produce a reliable AI platform are far higher and more involved than you might ever consider, especially for protecting sensitive financial exchanges, so choose wisely.
A smart AI assistant or AI agent can take on tasks and processes that have traditionally been completed by human agents. These are often repetitive and monotonous tasks, but also complex requests that are time-consuming, which can hold businesses back from focusing on growth. With AI and human agents working closely together, business leaders can achieve more, faster, and free up time for their human agents to work on more profitable, rewarding, and challenging tasks that push for progress and increase key metrics. There will be new roles created by AI at the same time as some functions are lost, and humans will always be needed for the sensitive or complicated situations that benefit from their attention and expertise ― something AI won’t replace any time soon.
Yes, advanced conversational AI platforms can support multiple languages ― AI Studio supports 130+ languages. One of the oldest AI assistants around, Stina, for Stena Line ferries, has been helping passengers in multiple European languages for decades. In global financial services, where customers may speak different languages, need help across time zones, and situations can be as urgent as can be, you’ll need a reliable AI assistant that’s multilingual with a high success rate in handling customer requests without human help. The Stena Line AI assistant reaches a 99.88% success rate.
It’s common for financial services companies to have legacy systems they’re not yet ready or able to replace, or want to keep running alongside new AI-driven services. Choose an experienced provider with extensive data management experience who’s been working in AI for longer than the launch of ChatGPT in 2022, and you’ll be able to rely on them to support, change or adapt your legacy systems to work alongside or be effectively replaced by AI.
Human oversight is crucial for allowing conversational AI to operate effectively and ethically. It involves reviewing the AI assistant’s performance, managing the use of LLM, or GenAI, input securely to provide accurate and consistent messaging ‒ always, and updating training data to improve responses over time. A “human in the loop” approach means your brand voice and reputation are protected at all times.