Let me start this week’s blog by once again thanking The Financial Brand for letting me participate in what I feel was a terrific article: Your Marketing Team Needs New Skills to Succeed Today. Here’s How to Implement Them. Thanks again. And I’m not saying that my participation was what made it terrific; it was terrific because it covered a lot of important ground on the topic of Artificial Intelligence and its myriad number of potential opportunities for community banks.
It also got me thinking a bit more about AI… and not just on the opportunities it presents for creating marketing content rapidly and efficiently, but also on the contributions it can make to data management, which the article also touched upon.
As we marketers know, great content can only come from great consumer insights. As article authors, Maddy Perkins and Ingrid Case, pointed out:
“Banks also have an enormous amount of data already in-house, the result of know-your-customer laws and records of untold numbers of loans and financial transactions. Additional data is easily available for purchase. All that data is a potential gold mine for a marketing department, which could use it to send relevant offers to current and prospective customers who need the products and services the bank offers.”
The authors go on to say: “Unfortunately, bank technology stacks don’t always let users share in-house data.” So true. And, if you’re a member of a community bank’s marketing team, you need to ask yourself: Are they talking about us? Are we one of those banks that can’t efficiently gather, collect, analyze, share and report on the data that is critical to our customer and employee experience, data security, compliance, marketing, risk management, and more?
Sadly, if you are, you are far from alone. In another article that appeared in The Financial Brand, we’re reminded that between 80 and 85 percent of banks lack the process maturity necessary to drive ROI. “Many banks are not able to fully leverage the power of their expansive internal data sets because they lack a scalable and agile data foundation and the appropriate levels of multi-speed data governance.”
A bit of data management history. Not long ago, banks got their data from a few, predictable, structured sources, and so their data management systems were built to handle numbers and values, such as credit card numbers, names, dates and addresses. Today, much of the data banks must manage is unstructured … what is also known as “big data.” This is the data associated with a whole new world of sources that includes social media, image and video files, document scans, webpages, blog posts, call center recordings, emails, analytics, metadata, and more. This data lacks a defined organization or pre-set pattern, can range in size from a few bytes to very large documents and represents, by far, the lion’s share of the data that banks process daily. In fact, 80% of enterprise data is unstructured and growing at an average rate of 65% each year.1
Given the absolute necessity of processing this tremendous volume of data, why is adopting and implementing data management tech solutions so challenging? One explanation, along with potential solutions, is offered by Ricoh USA, a provider of data management automation solutions. In a post, Are you making the most of your data?, the company offers this: “To manage your data effectively, extract value from it, and realize the vast potential that it offers, banks must evolve to a modern data management platform that will eliminate data silos; provide fast and flexible data processing; and ensure easy, secure access. Only then can they extract valuable insights, improve operational efficiency, and grow their share of wallet.”
Why automate your data management processes?
Improved customer experience: Harnessing unstructured data efficiently, and transforming that data into actionable insights, allows banks to gain a more comprehensive understanding of their customers. By automatically capturing and analyzing customer interactions across various channels — such as call logs, emails, and social media — automation can assist in gauging customer satisfaction levels and pain points, as well as responding more promptly to questions or concerns. ML algorithms can, for example, sift through emails, reviews, and other customer interactions to understand the sentiments behind them, thereby helping to predict customer behavior, enhance their experience, drive loyalty, and improve retention rates. All while adding greater efficiency and accuracy to manual, labor-intensive and error-prone, “human-in-the-loop” processes.
Streamlined operations and cost reduction: Manual data processing is not only time-consuming, but also prone to human error. Automation eliminates the need for labor-intensive, repetitive tasks, freeing up valuable resources and enabling staff to focus on more strategic initiatives. The efficiency gained through automation leads to cost reduction, increased productivity, and improved operational performance.
Compliance: Automation efficiently processes and analyzes unstructured data that can assist in identifying potential breaches or inconsistencies. By automating regulatory reporting, banks can reduce the risk of errors, streamline compliance processes, and ensure adherence to legal requirements.
Enhanced risk management and data security: Unstructured data often contains valuable indicators of potential risks, such as fraud, money laundering, or regulatory non-compliance. Automation can analyze unstructured data in real-time, flagging suspicious patterns or anomalies that may indicate fraudulent activities. By leveraging automation to identify and mitigate risks, banks can protect themselves and their customers from financial losses and reputational damage.
Right. But, what is keeping banks from moving forward?
Well, we all know this, right? We all know how important data management is to customer experience, talent acquisition, compliance, marketing, risk management, and more. So, again, what is keeping banks from going there? And why, according to studies, do nearly 90% of banks who implement technology solutions feel that they “didn’t get their money’s worth”?
As a business owner who is constantly on the lookout for solutions that can grow my business, I’ve done a bit of research on the matter and recount just a few of the proposed reasons below:
- Organizations tend to not build the proper consensus around tech adoptions, often failing to include/consult with their entire population of stakeholders.
- The stakeholders participating in the buying process cannot/do not come to an agreement on the measure of success.
- Implementation can be costly, disruptive and time consuming.
- Change leaders get distracted by other “shiny objects” that come their way.
- Vendors are not thoroughly and thoughtfully vetted
Yes, “banks,” as The Financial Brand tells us, “need to invest in analytics-friendly technology.” But, admittedly, it’s not easy. And there are, no doubt, tremendous opportunities in adopting AI-powered solutions; not just for more efficient marketing, but for true, enterprise-wide benefits. For this reason, community banks cannot adopt an AI-powered data management solution soon enough. Those that don’t take advantage of this technology now will quickly find themselves at a competitive disadvantage.
Bank Marketing Center
Here at bankmarketingcenter.com, our goal is to help you with that topical, compelling communication with customers — developed by banking industry marketing professionals — that will help you build trust, relationships, and revenue.
Our web-based platform puts our client partners in complete control of their marketing production process – and for a fraction of traditional marketing costs. We’re also proud of the fact that we currently work with over 300 financial institutions.
Want to learn more about what we can do for your community bank and your marketing efforts? You can start by visiting bankmarketingcenter.com. Then, feel free to contact me directly by phone at 678-528-6688 or via email at nreynolds@bankmarketingcenter.com. As always, I welcome your thoughts.
1CIO Insight. How Businesses Use Unstructured Data for Business Intelligence. February 15, 2023.