5 Ways AI is Transforming Customer Experience in Financial Services

In recent months, generative AI tools like ChatGPT have emerged as a new opportunity for financial services institutions looking to enhance engagement, especially the way they communicate with customers. Organisations are still in the early stages of exploring AI use cases for banking customer service and investment management financial advisors. Many executives are taking a cautious approach, with concerns about accuracy, authenticity and compliance. However, many are excited to explore AI uses for customers as well as employees.

With that in mind, here are five potential customer experience benefits financial service firms are seeing right now, when using generative AI tools.

One of the most significant ways generative AI can be useful in financial services is by offering customers more personalised communications, thereby improving engagement. By leveraging machine learning algorithms, AI can analyse customer data, such as transaction history and demographic information, to generate personalised investment recommendations and offers. For example, an AI-powered chatbot could recommend investment opportunities to a customer based on their risk tolerance, investment goals and other factors. This not only enhances the customer experience, but it can also drive customer loyalty and retention.

Generative AI is having a massive impact on the speed at which content can be created. Customer service representatives and advisors can use AI to jumpstart quicker drafts of correspondence, saving time and improving client engagement.  AI-powered chatbots and virtual assistants are capable of handling routine customer inquiries and requests quickly and accurately, freeing up human agents to focus on more complex customer needs. This not only speeds up response times for both humans and AI, but also reduces wait times and improves overall customer satisfaction.

In a time where financial services organisations are facing more fraud and security threats than ever before, AI is a critical tool that must be used to detect and prevent fraudulent activities. AI can analyse transaction data and user behaviour, and then identify patterns and anomalies that indicate fraudulent activity. This helps financial services organisations quickly detect and prevent fraud, saving both customers and the organisation time and money.

AI is becoming increasingly valuable to help financial advisors understand financial data and make smarter recommendations, helping customers plan for the future. Instead of pouring through financial records and data, advisors will be able to use AI tools to make predictions about future behavior and preferences, supercharging that analysis for them. Based on customer data, AI can predict when customers may need more support so that the company can identify customer issues and proactively reach out. For example, an AI-powered system can predict that a customer is likely to miss a credit card payment and proactively reach out with a reminder, reducing the likelihood of a late payment.

According to McKinsey, 44 percent of organisations that use AI have reported cost savings, and that is certainly no different in financial services. By automating routine tasks and using AI to optimise workflows, organisations can reduce the need for human agents while enabling employees to spend less time on error-prone manual activities and more time on strategic work. Additionally, AI-powered systems can operate 24/7, allowing financial services organisations to provide constant support to customers without incurring additional labor costs.

It must be noted that utilising AI in financial services comes with some potential pitfalls. Unlike most other industries, financial communications are highly regulated. For investment management, for example, firms must create an automated audit trail to prove that their advisors are acting in clients’ best interest. Even though content can be produced faster, financial institutions still need to manage and send communications via a structured, secure software solution that enables compliance controls.

Additionally, answers coming from generative AI tools have shown they can be inaccurate or even biased. It has been shown that machines have trouble balancing diversity and equity factors, so advisors must be aware of what data sets their AI is using to make recommendations, and step in if they detect bias. Tools like ChatGPT will get smarter over time, but their reliance on historical information can be problematic.

The key takeaway: financial institutions need to pilot use of generative AI solutions, while creating some boundaries and parameters for employees. It’s important to view AI as a tool, rather than a replacement for personal customer service delivered by a human. For many companies, the goal is to ultimately drive clients back to face-to-face (or virtual) meetings with a financial advisor for relationship building. AI only helps if it builds more trust in the advisor and the firm. But as AI technology continues to advance, it is sure to be a critical tool for financial services organisations looking to remain competitive in a rapidly evolving industry.