It’s no secret that FinTech disruptors are putting a great deal of pressure on incumbent financial services firms.
And yet, traditional financial services companies continue to lag behind with digital innovation. The problem isn’t necessarily that financial services firms aren’t present in digital channels. In fact, studies show that mobile banking adoption, for example, has consistently grown in recent years.
However, incumbent financial services firms are struggling in terms of digital customer experience. The abandon rate for mobile banking apps has risen to over 97%, a problem that can potentially cost up to 20% of annual revenue.
If financial services firms want to keep up with digital natives, they must improve customer experience. But they should not simply look at generic vendor solutions to improve digital customer experience—they should also examine how vendors employ machine learning technology and how it is impacting digital financial services.
Learning from the More Dynamic Retail Industry
The retail industry has traditionally been more dependent on consumer behavior than financial services. As such, retailers have been pushed to react much more quickly to digital transformation trends—and machine learning is no exception.
While there are obvious limitations when trying to satisfy consumers on a personal level, there is increasing demand to do so. This is why retail has been an early mover in machine learning. By leveraging vast amounts of digital customer data, retailers can connect with us in a much more scalable way (think of how Amazon’s home page is custom-made for your shopping habits).
We’ve reached the point that machine learning is no longer just for early movers in retail. Studies show that about half of consumers will interact with applications and services based on machine learning by 2018.
These won’t just be interaction with retailers—machine learning will permeate every industry (more than it already has) including financial services firms and they must be ready for the application of and transformation from this advanced technology.
Advancements are still being made in machine learning technology, but it can already help you improve customer experience in your financial services firm.
How Machine Learning Can Improve Digital Financial Services Experiences
There are many specific use cases for machine learning across all aspects of the financial services industry. Specifically, there are three main categories that machine learning applies to that can improve customer experience for financial services:
- Just-in-Time Customer Service: Forrester research found that 77% of consumers in the United States held valuing the customer’s time as the most important aspect of good service. Machine learning through technology like chatbots gives you the opportunity to address customer concerns immediately and transfer to human representatives when necessary.
- Scalability of Services: Imagine being able to automate the onboarding process for services like opening a bank account or underwriting for an insurance policy. Static systems have a lot of customer experience friction, leaving many digital customers to abandon services. However, machine learning applications can more effectively automate these standard processes, giving you the ability to scale at will.
- Service Personalization: It may seem like greater automation would inherently hinder personalization, but that’s not the case with machine learning. Leveraging big data through machine learning gives you the chance to personalize many digital services. For instance, smart wallets can monitor user spending habits to better-notify them of inconsistencies or saving/investing issues. Even with near real-time services, machine learning can help lower costs.
The bottom line is that as machine learning becomes increasingly prevalent, these three categories will become key differentiators for financial services firms to evolve into digital financial services providers. Technology can quickly become commoditized. But if you can deliver a truly differentiated customer experience, you’ll be able to avoid the disruption that is plaguing incumbents in the industry.
While integrating machine learning into the backbone of your organization can help you keep up with FinTech disruptors, you can’t exactly overhaul the whole business overnight. That’s why it’s important to target specific customer experience friction and prioritize where to innovate.
However, pinpointing customer experience struggles is often a tall task. The UserReplay customer experience analytics solution uses machine learning to help you automatically pinpoint specific areas of customer experience friction so that your team can quickly identify, prioritize and optimize those areas costing you the most with your prospects and customers. If you want to an introduction to how machine learning can impact customer experience in your organization, contact us today for a free demo of UserReplay.