Why the future of finance depends on AI and unstructured data

In 2021, the global economy reached an astonishing GDP of $94 trillion, growing almost 180% over the past 20 years. (At the turn of the millennium, the GDP was only $33.62 trillion.) Economies are unable to expand without support from a healthy financial services sector. And the financial services sector, in turn, has only been able to provide as much support for our economic growth as it has because of the mass digitization of banking and finance operations.

Given the speed of business now — easy online payments, wire transfers, fund validations, and other feats in efficiency — it can be hard to remember a time when banking wasn’t so convenient. Automation technology, and increasingly, artificial intelligence are setting new benchmarks for financial services everyday, but there’s still much more potential to be mined. Much of this potential lies in how we use AI to process unstructured data.

What is unstructured data?

The world is full of information, but the only way we can do anything useful with it is to classify, qualify, or quantify it. Structured data is labeled or measurable, such as names, transaction amounts, purchase dates, and other information you can easily contextualize. It’s also generally ready for analysis as it’s stored in operational databases or warehouses. Unstructured data, sometimes referred to as “dark data,” is unorganized and lacks a predefined data model. In its unstructured form, this data serves no clear purpose, and it’s stored away and inaccessible for actual use. But the right analytics approach (and tools) could convert it into a wealth of useful information that deepens customer, market, and product insights.

Digitization has resulted in an unfathomable amount of data collected daily with roughly 80 to 90% of it unstructured. The total volume of unstructured data in the world is expected to reach 175 billion terabytes by the year 2025.

Every industry has its own structured and unstructured data. For financial services, unstructured data can include information from CRMs, customer service records, earnings transcripts, tax documents, and even survey responses. Making use of all the unstructured data in these documents could give companies an incredible competitive advantage. What’s more, structuring it will provide insight into creating more innovative products and providing better customer service.

How AI processes unstructured data

For more than two decades, the digitization of the financial services sector has improved the convenience and speed of banking, all while amassing a veritable treasure trove of data in the process. Now, using AI to make this information valuable is the key to the future for the entire industry. Here’s how it can help:

Mine insight into changing customer needs

Structured data forms a compelling narrative about customer behavior, but the unexamined patterns in unstructured data can be even more telling. Service providers already collect swaths of customer information from KYC initiatives. Unfortunately, it remains locked as unstructured data in documents that are difficult to process (such as mortgage applications). With AI, users could structure this data to glean more insight into customers’ circumstances.

Improve customer satisfaction

The digital transformation has made it easier than ever for banks to keep records of support tickets, customer service calls, and other customer interactions — but putting it to more valuable use has always been a challenge. AI analyzes this unstructured data to then automatically process common customer requests, such as change of address, policy cancellations, quote requests, and more. This way, customers receive an immediate response and faster service in a fraction of the time it would take for customer service employees to manually handle their requests. 

Unlock the full value of document data

The sheer amount of information companies have about their customers could radically improve convenience, service quality, and relationships, if they could effectively process it. AI accesses all of the disparate information spread out across contracts, policies, transaction records, and other documents for further processing. Patterns in unstructured data could also point to the need for new types of products, such as loans, financial counseling services, discounts, or budgeting tools. This can help companies create entirely new services or tailor existing offerings more specifically to each individual.

What unstructured data means for the future of financial services

As the financial services sector continues to move beyond the limits of its traditional IT infrastructure, AI is helping it break free of the limits of structured data. AI is becoming not only more intelligent but also more practical for solving difficult problems that computers could not handle previously. And with so much currently unused information already sitting in databases, emails, file stores, and other customer communication channels, every company in the industry has a true Midas opportunity to turn their junk data into gold. For those opportunities, Automation Hero is a versatile intelligent document processing platform with AI designed to master every type of unstructured data. Learn more about how it can help your company in a call with our experts.