The Five Habits of Successful Data-Driven Financial Institutions

Even if your bank or credit union isn't ready to deploy chatbots, virtual assistants, artificial intelligence (AI) or innovations involving the Internet of Things (IoT), the importance of data and advanced analytics capabilities has never been greater.

If you’ve been following the financial services scene lately, chances are high that you’ve seen plenty of talk about chatbots, virtual assistants, and other forms of artificial intelligence (AI). These advanced technologies promise to be a big part of banking going forward, and for good reason: They make the entire process simpler and more intuitive. Who doesn’t want to skip phone trees and get straight to the answer they’re seeking? That’s what chatbots and virtual assistants offer.

Unfortunately, many people mistakenly believe that the path to chatbots and virtual assistants consists solely of offering those products to end users. The belief is that once a chatbot is available, it will immediately be able to answer the majority of a user’s questions. Just plug it in and watch it go to work.

In reality, what gets overlooked is that any product that offers advanced technology is only as good as the foundation of data on which it rests. You can have the smartest chatbot in the world, but if it isn’t built on a structured database it won’t return the right answer. Even simple questions about branch hours and loan rates require the right building blocks.

In the Digital Banking Report, AI in Banking: The Next Frontier of Customer Experience, most financial organizations said their most significant challenge with advanced technology solutions is finding the necessary expertise and personnel. They also cited the right structure of data, and analytics capabilities required to build the solutions. These challenges are significant but not insurmountable.

In most cases, firms will not have the resources internally to address these challenges — especially considering alternative priorities in today’s marketplace. Banks and credit unions will need to evaluate a build/buy/partner decision.

This is a problem facing far more companies than just banks and credit unions. In fact, the Harvard Business Review has shown that only 3% of companies’ data meets basic quality standards, revealing that there’s an enormous business advantage for those companies that can get their data strategy right and effectively execute on it.

Let’s look at five ways to lay the right foundation and most effectively implement the latest advanced technologies.

1. Structure Your Data

The financial industry is already sitting on mountains of data, including loan data, transaction data, credit data, and more. In other words, the problem isn’t obtaining the data. The data is there by default. The problem is in getting the data structured.

To fix this problem, banks and credit unions should first consider hiring professional data analysts who can ensure that the key data components are accurate. Having a range of professional data analysts on your team ensures you’re structuring your data correctly from the get-go.

2. Use Algorithms to Mine for Insights

Once your data is sufficiently structured, the right algorithms can analyze your databases to find insights across your user base. What’s the average credit score of your account holders? What is the average savings rate? How many of your users also have a credit card or a loan with one of your competitors? These are just a few of the answers that are instantly available if your team sets things up correctly.

The key benefit here is that with greater insights into your business you’ll have a greater ability to implement the exact strategies you need to stand apart from your competitors. Best of all, since the data is dynamic, you’ll be able to instantly track how things change in real time and adapt your strategies accordingly.

3. Tailor the Insights for Individual Consumers

This is where artificial intelligence really starts to bring results. Because the data has been fully structured and algorithms are mining for insights, you can tailor those insights for each individual user. In this way, a user who has surplus money in a savings account might get a suggestion to move that money to a term deposit to ensure a higher savings rate, while a user who has a credit card with a competitor will see an offer to switch that card to your institution and get a lower APR.

As each user realizes that their digital experience is being tailored to meet their exact needs, their trust for your institution deepens. Bit by bit, you earn a reputation as a bank or credit union that can actively provide a service that your users didn’t even know they needed — a service along the lines of Amazon’s “Recommended for You” feature.

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4. Use the Data in Ways That Create Added-Value

At this point, there’s an important caveat to make, which is that advanced analytics can actually hurt your cause if you’re not careful. This damage primarily occurs if users get the sense that you’re leveraging their data in ways they don’t approve of.

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To combat this potential problem, it’s critical to never sell user data to third parties — especially without the explicit approval of each individual user. In this same vein, it’s also critical to not create offers that prey on account holders for your short term benefit. Doing this will result in the exact opposite of what you want to accomplish with products like chatbots and virtual assistants, creating distrust and antipathy for your brand. If you’re only concerned about the immediate bottom line, you’ll end up not achieving the long-term loyalty you’re seeking.

5. Make The User Experience Seamless Across Channels

Finally, to truly reap the benefit of advanced analytics, chatbots, and virtual assistants, the entire user experience must be seamless. If someone has a question about your services while using your mobile app, they must be able to get the answer right there. If it turns out that a process gets too complicated for a virtual assistant, the user must be able to contact a live representative get immediate answers that way.

In addition, if someone walks into the branch to get help, your tellers and service representatives should be able to access the same data points and insights that are being leveraged by the chatbots. That way your users can get precise — and consistent — guidance every step of the way no matter the channel they choose.

Data is the Foundation for the Future of Banking

Whether or not your bank or credit union decides to explore advanced technologies such as chatbots, virtual assistants, artificial intelligence or the Internet of Things (IoT), it’s crucial to keep in mind that all future solutions rely on a solid foundation of accurate data. The consumer is expecting you to know them, understand them, and look out for them, and to use data and advanced analytics to provide proactive recommendations.

After all, if a user asks a chatbot how much they’ve spent on coffee this month, and only two of the five coffee transactions have been categorized as coffee transactions, what good is the chatbot? It will return the incorrect answer, even though it’s perfectly following its own logic.

Report on Innovative Technologies and Advanced Analytics

The AI in Banking: The Next Frontier of Customer Experience report, provides insight into the progress being made by financial institutions globally in the area of advanced technologies such as AI, chatbots and virtual assistants. Beyond a review of goals and investments, this report delves deeply into the strategies, effectiveness, challenges and measures around improving the use of data and analytics to improve the customer experience in the banking industry.

The report includes the results of a survey of more than 250 financial services organizations worldwide. The report has 56 pages of analysis and 30 charts/graphs. Most importantly, the cross-tabs by organization size and type allow a comparison of peers. There are also guest articles from industry leaders

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