In a recent article in The Financial Brand, “Banks are Swimming in Data but Starving for Insights. AI will Make Things Worse,” I saw this: “A new study by Cornerstone Advisors asked bank and credit union respondents to rate themselves on 50 factors spanning five categories — customer data, market data, operational data, transaction data and data governance — to produce a "Data IQ." The results are sobering. For example, only 42% of the sample felt that their organizations treat information as a strategic asset. Only 29% said that key business decisions are made in conjunction with "accurate, timely and actionable data."
That is sobering, indeed.
Today’s banks are, without a doubt, experiencing exponential growth in the volume of data they collect and manage, from front office customer engagement to back office compliance and risk management. Why is unstructured data so important? Unstructured data is critical to functions across the entire banking enterprise; sales and marketing, product development, and customer service, among others. But unstructured data is not easily actionable, and putting it to work for your organization requires an informed, strategic, and measured approach. Let’s start with the understanding that not all data is created equal.
The data evolution
Today’s data arrives at a financial institution from a wide range of sources and in a variety of forms. It was not terribly long ago that data sources were far more limited, and far less dynamic, with data arriving in predictable, structured formats. For banks, this data is numbers and values based, such as the details relating to customer demographics and financial transactions, i.e., names, dates, addresses, credit card numbers, and more. As a result, the traditional data management system is limited to numbers and values-based data.
By contrast, unstructured data, (a.k.a. “big data”), is the data associated with a whole new world of data 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.
Automation: The right approach to bringing structure
Transforming this vast volume of complex data into useful, accessible, and actionable information can revolutionize a financial institution’s data-driven systems and processes. In doing so, it enhances risk management, improves customer experience, identifies market trends, and drives innovation through real-time, better-informed decision making.
But you need to take the right approach. To manage 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 banks extract valuable insights, improve operational efficiency, and grow their share of wallet.
How? With AI-powered automation. Let’s look at some of the types of automation needed and the positive impact they can have on specific banking operations.
Automating for efficient extraction and classification
Automation can take a variety of forms. For bankers, these automations can perform myriad tasks that enable the classification of unstructured data, all with the same critical benefit: the optimization of both resources and data usage.
- Natural Language Processing (NLP) models can analyze and interpret text, allowing for the extraction of key entities, sentiment analysis, and topic modeling. NLP enables banks to sift through massive volumes of text—like contracts, loan agreements, and reports—including scanned or legacy documents. For example, JPMorgan Chase’s COIN system, which has been in use for years, utilizes NLP to review 12,000 commercial agreements and extract 150 key data points in seconds, saving an estimated 360,000 labor hours annually.1
- Optical Character Recognition (OCR) systems are employed to convert scanned documents and images into searchable and editable text, enabling easy extraction of data from various sources. Like NLP, OCR can shave hours and hours off the manual searching and editing of documents.
- Machine Learning (ML) algorithms can be trained to categorize unstructured data based on predefined criteria, enabling rapid sorting and organization. This significantly reduces the time and effort required for manual classification, enabling banks to unlock valuable insights and make data-driven decisions more swiftly, while minimizing human error.
Automating for improved customer experience and cost reduction
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 sentiment, 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. But there’s more to customer experience than advanced technology. Once data becomes insights, the bank’s marketing department must turn those insights into revenue.
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.
Automating for enhanced compliance and risk management
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.
Choosing the right automation solution
In the era of big data, unstructured data can either be an overwhelming burden or a goldmine of opportunities for banks. Together, AI-driven solutions and unstructured data are providing that goldmine of opportunities, transforming the way banks do business by enhancing risk management, improving customer experience, identifying market trends, and driving innovation through real-time, better-informed decision making. After all, the future of banking lies in embracing automation and harnessing the power of data to unlock new avenues of growth and success. And that future is now.
Bank Marketing Center
We’re Bank Marketing Center, the leading, subscription-based provider of automated marketing services to community banks. Our goal is to help bank marketers with topical, compelling communication with customers that builds trust, relationships, and revenue. And we do this through automating critical bank marketing functions, such as content creation, social media management, digital asset management and, of course, content routing. All of which contribute to a community bank’s ability to create and distribute content that drives business, without fear of fines, brand damage, or fleeing customers.
We also want to share what we know—and learn along the way—with all our community banking friends. Whether it’s content focused on the latest on AI technology, suggestions on how to attract and retain top talent, or the importance of data protection, we’re here to make bank marketing the best that it can be..
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.
1ABA Journal. JPMorgan uses tech to save 360,000 hours of annual work by lawyers and loan officers March 2, 2017.