AI is transforming nearly every industry in the world. One sector, in particular, that is experiencing significant change is the financial services industry. Financial institutions (FIs) everywhere are using AI/ML to provide differentiated experiences in a market that is only growing more competitive.  

Those that harness the full potential of AI/ML will survive in our current age of disruption. Those that don’t will struggle to keep up with nimble fintech startups disrupting the market and reshaping how consumers are engaged. 

According to one OpenText survey, three out of four banks with more than $100B in assets are already investing in AI initiatives. Nearly half of respondents with under $100B in assets are doing the same. 

To put it bluntly, if you operate in the financial services sector, now is the time to invest in AI.

In this post, we’ll explain several ways that FIs are using AI/ML today in order to help you think about how your enterprise can leverage the technology as well. We’ll touch specifically on how FIs are taking advantage of open banking, improving customer experiences, and optimizing outbound communications through data analytics and machine learning algorithms.

Generating Value From Open Banking With AI

Open banking is a newer concept that describes when FIs use open APIs and their data in combination with third-party and partner data to build unique applications and services around the financial institution. For example, fintechs are using FI data to develop tools that help people manage their finances (e.g., Mint), gain access to new loan opportunities (e.g., Portify), and much more.

While open banking has given consumers better visibility and control over their financial data, it’s created both new opportunities and challenges for FIs. On one hand, open banking has eaten into FI power, as these institutions no longer have a monopoly over financial data. On the other hand, open banking gives FIs access to rich information about their customers. 

For instance, FIs can now see what people are interested in across the broader financial landscape and act accordingly. They can also learn what third-party platforms, services, or products tend to draw customers away and take steps to minimize that churn. 

The best way to glean these insights efficiently and securely is through AI and machine learning algorithms. AI/ML makes the process of analyzing consumer behaviors and interests at scale much less labor intensive, opening up a world of business development opportunities.

So, while FIs have lost 100% ownership over consumer financial data, they now have more insight into what people want. AI/ML is the means by which FIs can study what consumers use in the open banking world and adapt accordingly.

Enhancing In-house Services And Features

FIs are also using AI/ML to dig into their internal data to understand how to best enhance services and features for diverse customer bases. AI/ML is tremendously valuable when it comes to sifting through enormous structured datasets, which is exactly what FIs possess. 

With the right program or algorithm, AI/ML can help:

• Identify entirely new customer segments or sub-niches
• Reduce new customer acquisition costs by connecting specific behaviors to conversions
• Increase recurring revenues for existing products by highlight important features
• Offer new and additional products and services to existing customers

Rather than hypothesize or take action based on limited evidence, FIs can use AI/ML to identify behavioral patterns across nuanced customer segments and develop products in accordance with those findings. 

ML algorithms can also help predict future behavior based on past engagement, which means FIs are able to invest more precisely in innovation and bring products to market that have a high potential for adoption.

Optimizing Outbound Communications

Outbound communications is another area in which FIs are implementing AI/ML capabilities. AI/ML enables FIs to analyze a multitude of messaging channels for the purpose of uncovering factors that tend to lead to higher engagement.

For example, FIs can build AI/ML programs capable of retroactively analyzing all email marketing communications and identify patterns related to subject lines, link placements, total word count, time of day sent, and other variables that may affect engagement. 

FIs can use these insights to develop best practices around consumer messaging that maximize open rates and click-throughs. On top of that, FIs can, again, segment their customers according to demographic data or behavioral patterns and send tailored messaging that ultimately results in a better experience for the individual user. 

Learn More About How FIs Are Using AI/ML Today

Beyond these examples, there are many other ways FIs are using AI/ML today. Daitan has helped FIs all over the world get more value out of their data using AI/ML, as well as participate in the broader movement to open banking.