How to automate banking & financial services processes involving unstructured documents — to increase capacity and reduce costs

Banks and other financial services companies have always dealt with an inordinate number of documents, from 10-Q and annual 10-K forms to customer onboarding documents and statements. Now that we’re firmly in the digital transformation age, the race is on to achieve intelligent document automation for financial services processing.

While they’ve had some success with robotic process automation (RPA) and templated approaches to automation, those solutions will only take them so far for a simple reason: they can only handle highly structured documents. But 85% or so of the documents financial services firms must deal with are full of unstructured content.

Dealing with unstructured documents requires an intelligent document processing platform that can “read” these documents just like seasoned employees do. A good IDP platform can quickly find and extract the relevant terms and data in a document and input them into another downstream system for processing. It all adds up to a tremendous increase in efficiency in dealing with numerous financial services use cases.

The Indico approach to intelligent process automation for financial services is fundamentally different from earlier technologies such as RPA and templated approaches that use optical character recognition (OCR). Such approaches only work with documents that are highly structured, where the same data is in the same place each and every time.

But most financial services documents aren’t like that. Rather, they are unstructured, meaning relevant information and data may appear anywhere in the document. Automating processes involving unstructured documents requires a tool that incorporates artificial intelligence, along with a massive database for the AI technology to draw on.

Indico’s Unstructured Data Platform is based on a model that incorporates 500 million labeled data points, enough to enable it to understand human language and the context behind any document or image. That massive database is crucial to the ability to effectively train models that can automate financial services processes.

Using AI technology known as transfer learning, Indico Data enables financial services firms to build off that database and create their own custom models that can tackle virtually any document-intensive financial services process. The result is that it takes a relatively small number of documents to train the model – usually just a few dozen. What’s more, you don’t need data scientists to make it all work. Rather, business professionals on the front lines train the automation model – those who know the processes best. (For a deeper dive on this point, check out our Intelligent Process Automation page.)

Adopting intelligent process automation doesn’t mean abandoning all your investments in ​​robotic process automation, however. Some financial services processes can benefit from the combination of using RPA to automate deterministic processes and IDP for those that require intelligence to handle unstructured documents.

One example is in the financial document analysis use case, which involves analyzing unstructured documents including quarterly 10-Q and annual 10-K forms. An IDP tool could be used to “read” such documents, identify and extract required data, and convert it into a structured format. At that point, the RPA tool could be employed to take the now-structured data and enter it into a downstream processing or analytics tool.

In this age of digital transformation, financial institutions must take steps to achieve efficiencies wherever they can. The Indico Data intelligent document processing solution helps in that effort while delivering significant benefits, including:

Capacity expansion:
Automation increases employee productivity up to 4x, enabling your company to increase revenue with existing headcount.

Cycle time improvements:
Automating manual processes enables financial services companies to get work done faster, while increasing accuracy.

Increase efficiency:
Take mundane tasks off your employee plates, freeing up time for more rewarding work that’s also more valuable for the institution.

Knowledge capture:
Automation requires companies to codify processes that were performed for years without formal agreement on how the process should happen. It’s an exercise that often uncovers ways to make processes more efficient.

Compete more effectively:
Automation makes organizations more competitive, taking a page out of the book of the nimblest fintech startups.