The employees have always sought out more effective methods of accomplishing tasks, but one difference from earlier times is that they now have access to more technology.

Some examples of more recent technologies that are benefiting businesses include natural language processing (NLP), optical character recognition (OCR), and robotic process automation (RPA). How? Read on.

A successful RPA setup is when a business can deploy robots that work well together and free up human workers to perform other tasks. RPA can automate both processes that interact with customers and those that are in the background, but smart implementation is the key to making the technology profitable.


  1. OCR speeds up invoice processing

Characters on paper documents can be read by OCR (Optical Character Recognition) and converted to digital format.

Companies that frequently receive paper invoices and want to upload them to digital databases without spending hours manually entering the data are finding this capability to be extremely helpful.

Employees can use OCR software to scan physical invoices into an interface, which will then use technology to recognize the characters on the page.


  1. NLP enhances hiring practices

Recruiters have a lot of work to do when trying to fill highly competitive positions that can receive hundreds of applications. Some people have discovered that NLP (Natural language processing) could streamline their hiring procedures.

For instance, NLP platforms provide ways to automate the pre-screening questions candidates must answer after being placed on shortlists by HR managers.

The technology can pick up on details that HR personnel might otherwise overlook, like keywords that could point to a candidate’s superior fit for a position.


  1. RPA helps businesses identify potentially risky customers

RPA may not only enable businesses to accomplish more, but it may also be crucial in lowering risk. To assist them in adhering to financial industry regulations regarding anti-fraud and anti-money laundering, many banks have implemented RPA.

Financial institutions risk facing steep fines and other expenses if they don’t take action to identify customers connected to these illegal activities and reduce the risks they pose.

RPA platforms routinely gather and analyze customer data. Although employees are still involved in the screening process, doing so is much simpler with the aid of RPAs than it would have been without it.


  1. NLP aids in measuring client satisfaction

According to research, most people who call customer service numbers don’t get the assistance they require. When this occurs, many people become so frustrated that they choose to give their business to other businesses.

Thankfully, NLP technology could stop people from getting that frustrated. There are programs that measure a person’s voice volume, tone, and words spoken during a conversation, among other things.


  1. OCR & AI for error detection

As software providers combine OCR with AI, optical character recognition tools are undergoing a quiet revolution. Data capture software consequently records data while also comprehending content.

In real life, this translates to automated fault management systems that can check for errors without human intervention.

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