In an era of unprecedented competition and customer expectations, banks and credit unions are understandably looking at smart automation as a way to improve core processes, enhance productivity, and advance digital transformation initiatives.
Whether or not they succeed will have a lot to do with how they evolve their technology stack.
The finance technology or FinTech toolkit has different options to choose from when it comes to automation in banking. Robotic process automation (RPA) and AI/machine learning have gained traction and greatly expanded the scope of automation within banks and credit unions.
But each of these technologies has specific strengths and weaknesses. And IT departments are now hitting the kind of ceiling they experienced with earlier automation technologies such as optical character recognition (OCR). Consider that:
These challenges are frustrating enough. When these technologies are isolated in siloed projects, they run the risk of being used for a while—then discarded.
The reality is that no one technology can address every bank’s or credit union’s needs. The key to success with automation in banking is weaving them together into the right solution.
Increasingly, banks and credit unions are integrating technologies such as AI/ML (machine learning), RPA, and more to create unique automation solutions that address specific use cases. Research from McKinsey shows that those organizations seeing success in automation are using a number of tools that include ML, RPA, and natural language processing (NLP).
The question is how best to combine these technologies and make the whole greater than the sum of its parts.
To achieve genuine and enduring success, banks and credit unions must combine these technologies in an environment that integrates with core banking systems, accesses multiple data sources, and provides low- and no-code development tools that allow “citizen developers,” or everyday business users, to build solutions.
By doing so, financial institutions can gain the ability to create automated solutions to complex financial processes—not just simple repeatable tasks.
The shortest path to integration is to deliver these tools and technologies as part of a platform. And an intelligent document processing (IDP) platform makes for the ideal synthesis.
IDP as a concept is rapidly becoming more widely known and adopted within the financial services world. The essential value of IDP is identifying, classifying, and extracting data from important business documents. In the case of banks and credit unions, of course, that means account applications, loans, and supporting materials.
IDP platforms offer capabilities, features, and functionalities that banks and credit unions can deploy as out-of-the box solutions using pre-built modules, or as custom solutions. What’s more, banks and credit unions can pick and choose what they want to deploy. They can leverage the comprehensive solution, or they may use parts of it.
An intelligent document processing platform provides an effective foundation for automation. This is especially true for those institutions closer to the beginning or the middle of their digital transformation journey. An IDP platform can ensure that documents are consistently received (regardless of the channel), processed (automatically classified and information extracted), logged and stored in an orderly and trackable way.
Banks and credit unions that embrace IDP can eliminate manual data entry, process bottlenecks and delays. They also can streamline the flow of data across the institution, and better meet compliance requirements.
Understanding what modern-day IDP is and what it can do can help you reap the benefits of RPA and AI. Download our free guide, The Onramp to Automation for Banks and Credit Unions, for a deeper dive into IDP.