AI Articles and Reports about Process automation

Many large banks and financial institutions are beginning to digitize parts of their business processes to prepare for future initiatives in automation and machine learning. This is particularly true with loan processing. These functions could become faster and more accurate if they use digitized data that is more easily accessible than paper documents.

Financial institutions have challenges around data accessibility. They want to leverage their large amounts of data so their employees, such as customer service agents, can find the information they need quickly.

In this brief overview, we run through several use-cases for voice recognition software in the healthcare industry. Voice recognition software, built on natural language processing (NLP) algorithms, primarily finds a home in the doctor's office. Physicians use it to dictate their notes into their healthcare network's system or update patient electronic medical records (EMR).

Many of the key processes in industries such as banking and insurance are still done on paper. That said, many large enterprises seem to be in the process of digitizing parts of these processes in order to prepare for forays into automation and artificial intelligence. 

There are numerous AI vendors servicing the banking industry, but many of them lack the kind of funding that these five vendors have raised. In this article, we run through the top 5 AI vendors in banking by funding according to information on Owler. We provide an overview of their products and the AI tech that makes them possible.

When it comes to process automation, digital transformation leaders are now navigating the artificial intelligence hype. Although AI can yield some impressive results when it comes to digitizing processes that still involve paper and reducing the time customer service agents spend searching for customer information, leaders are perhaps too excited to jump into AI without knowing the fundamentals of what it entails.

Banks are starting to deploy natural language processing (NLP) to make use of enterprise and customer data in text mining applications ranging from gauging customer sentiments to enterprise search.

Robotic process automation, or RPA, has dominated much of the automation conversation in the insurance industry for several years. RPA is able to capture manual steps that employees take to log into software, search documents, and enter data and replicate them.