4 Ways Financial Services Are Ahead of the Customer Experience Game

Financial Services have an extremely close relationship with two things: money, and data. With enough data, you can do anything — including generating more money. One of the most tested ways of using data to increase revenue is by improving the customer experience (CX) — by doing so, companies see their revenue rise between 10 to 15 percent.

So how are financial services companies leveraging their mountains of data to improve their CX? The short answer is artificial intelligence (AI), and four out of five senior bank executives believe it’ll give them the edge in market share. The long answer is a little more complicated, but fascinating. Here are four ways financial services firms are using AI to improve CX.

1. Identity Protection

Over 250,000 New Zealanders experienced identity theft in 2021. In the United States during the same period, nearly 42 million people suffered the same fate (that’s more than one every second), costing consumers $52 billion in total losses. Little wonder then, that 61% of customers won’t do business with an organisation if they can’t trust how it secures its data.

The most common vulnerabilities for identity theft are through outside hackers, sinister employees, or at times when data is unencrypted, such as when a support ticket is opened. A technique called de-identification is often used for safety, which removes a customer’s personally identifiable information (PII). AI is now being leveraged to control this data even better, with techniques generally unachievable by an average human programmer.

These techniques include edge machine learning and re-identification risk scores, which work by identifying unusual or risky behaviour at the edge — before data is even accessed — and ensuring that only authorised users can see PII. This protects against malicious insiders and outside hackers, while also making sure that your customer’s data is secure.

Without AI, these risks would go unidentified, and customer data — along with a company’s reputation — would be in jeopardy.

2. Quality Management

If every customer call was to be monitored for quality management (QM), a contact centre would have to double the number of their human agents just to keep up. With AI however, companies can use ‘virtual coaches’ — computer software that analyses customer service interactions in real-time to identify coaching opportunities for human employees.

The benefits of AI-driven QM are threefold. Firstly, because it is in real-time, agents can be given insights during the call. Secondly, that real-time analysis also allows supervisors to give in-the-moment coaching to agents when needed. And thirdly, it facilitates the end goal of improving the calls, and therefore general CX, over time.

This technology is not only more accurate than humans at identifying errors, but it’s also more objective. And because it never gets tired, the virtual coach can provide feedback around the clock. This allows agents to spend more time on tasks that only humans can do, like relationship building, and less time on the tedious task of QM.

3. Sentiment Analysis

If you’ve ever had to wade through a sea of online complaints to find a single insightful review, you know how important sentiment analysis is. AI can help by taking all that data and turning it into insights that can be used to make changes that’ll improve the customer experience.

One major way sentiment analysis is used is to more accurately understand the root cause of customer complaints. This is done by analysing the natural language in customer service interactions to identify patterns in customer behaviour. These insights can then be used to make changes that’ll address the underlying issue, rather than just treating the symptoms. One innovative bank in Europe used this AI technique to achieve a category accuracy score of 95 percent, dramatically reducing customer churn.

4. Response Times

It appears that in terms of customer reluctance, financial services are right up there with car salespeople and real estate agents — one study found that people who had negative experiences with financial institutions would rather go to the dentist than engage with a financial service provider again.

A big part of that hair-pulling frustration comes down to response times during customer service interactions. In a world where we can order a pizza and have it delivered to our doorstep in 30 minutes or less, the slow pace of financial services can be maddening.

This is where AI comes in, by routing customers to the best available agent and automating simple tasks, like resetting a password. This frees up human agents to deal with more complex issues, and cuts down on response times. As a result, customers are more likely to stay loyal and continue doing business with a financial institution that values their time.

What’s next for AI in CX?

We are far from an AI overthrow of human-based CX, with the majority of banks feeling that the dangers and difficulties that come with AI projects involving personal data generally surpass any potential customer experience benefits. But in time, that will change as the financial service sector, regulators, and ultimately customers become more comfortable with the security of their data under AI oversight.

When that happens, we can expect to see even more amazing things from AI in customer experience, including virtual assistants that can handle simple tasks like booking appointments, more accurate fraud detection, and more personalised products and services. So whatever you think about it, AI is here to stay — and it’s only going to make the customer experience better.

If you’d like to learn more about how AI, machine learning, and cloud centre contact solutions can help improve your CX execution, please contact us. We’d be more than happy to help you find out how your contact centre operations can be improved for bottom-line-boosting CX.