Cognitive Automation vs RPA: Key Difference & Use Cases

The world of automation software is replete with options to optimise your business processes. From cognitive automation to robotic process automation to human analytical automation, there is a lot to grasp.

So, how do you know which automation solution is going to give you the most bang for your buck?

Here, we will break down options for automation in financial services and review the similarities and differences so you can make an informed decision.

Coming Up

1. What is Robotic Process Automation?

2. What is Cognitive Automation?

3. What is the Difference between Robotic Automation vs Cognitive Automation?

4. How to Choose Robotic Automation vs Cognitive Automation?

5. What are the Variations of Cognitive Automation?

6. What are Examples of Cognitive Automation?

7. Closing Thoughts

What is Robotic Process Automation?

Robotic process automation, or RPA, is easily programmable software that can execute basic tasks across applications. It can transform business processes that would otherwise rely on humans to carry out mundane, repetitive, and continuous tasks.

In the case of RPA, people can define a set of instructions or record themselves carrying out the actions, and then, the bots will take over and mimic human-computer interactions. This makes it possible to complete a high-volume of tasks in less time and with less error.

RPA relies on structured data to perform its operations.

What is Cognitive Automation?

If we were to think about automation as a spectrum, you would see robotic process automation on the entry-level end and cognitive automation on the opposite pole.

Cognitive automation, as the name implies, includes cognitive functions due to the use of technologies like natural language processing, speech recognition, and artificial intelligence to handle judgment-based tasks.

As such, cognitive automation imitates how human brains work and can use context to make decisions, perceptions, and judgments. Cognitive automation uses unstructured data and builds relationships between data points in order to create association and make decisions.

This pre-trained solution is able to automate a variety of business processes with less data. This also means that there is no need for IT experts or data scientists to develop complex models for the system to be able to learn and make its own connections.

In essence, cognitive automation can be left without human intervention and accurately perform tasks ad infinitum.

What is the Difference between Robotic Automation vs Cognitive Automation?

As you can likely already see, there are big differences between robotic automation and cognitive automation. There’s also another type of automation that complements robotic process automation, but is not considered to be cognitive automation. We will cover that at the end of this section, too.

To better understand what the differences between your automation options are, we can categorise what you should know into four main ideas, namely:

1. Application Scope

The processes for which you deploy cognitive automation vs. robotic automation differ by nature. Robotic process automation uses structured data to execute processes. Roughly 60% of business processes fall under this scope. For example, in finance, robotic process automation can aid in loan processing, anti-money laundering, know your customer, and a retail branch’s day-to-day activities.

For the most part, RPA is used for back-office and low-level tasks that are repetitive. By using RPA to manage these tasks, it frees up your employees’ time for high-value operations. There’s also a reduction in manual error.

For the remaining processes that require human cognitive abilities, cognitive automation can be used. This is because cognitive automation can work with unstructured data and can make decisions based on context.

For this reason, cognitive automation can be applied to non-routine, analytical, and complex tasks. To exemplify, cognitive automation use cases can include: automated threat intelligence and prevention systems, investigation, and fraud analysis, to name a few.

2. Technology & Methodology

The technology behind both robotic process automation and cognitive automation are vastly different.

Robotic process automation uses basic technologies like macro scripts and workflow automation, which are relatively simple to implement. The rules-based automation rarely requires coding and instead uses an “if-then” processing methodology.

Alternatively, cognitive automation is empowered by complex technologies that provide its ability to mimic a human’s cognitive functions. These technologies include: speech recognition, text analytics, data mining, semantic technology, natural language processing, and machine learning, to name a few.

3. Benefits

Both forms of automation can improve a business’ operations and provide cost savings.

Without having to do much, RPA is a simple way to begin your organisation's automation journey. The benefits are practically immediate as your team will have more time to focus on high value work that requires human cognition and thought.

Cognitive automation can work alongside humans to provide analysis that can aid in their decision-making, or cognitive automation can work without any human intervention. As more data gets added to the system, cognitive automation learns and becomes more powerful over time.

4. Human Analytical Automation

There’s another type of automation that may be talked about less, but it can be extremely valuable to businesses across industries. A human analytical automation solution like SolveXia can perfectly complement robotic process automation to provide business leaders with valuable insights.

While RPA interacts directly with your IT systems to automate tasks, SolveXia ingests data from various systems and can transform it into visual reports and dashboards. Rather than looking at data and numbers across disparate spreadsheets, your team has a transparent look into what the data actually means for your business with dashboards. In turn, decision-making becomes informed, agile, and speedy because you have actionable insights available at your fingertips.

A tool like SolveXia is great for tailor-made processes that involve a lot of data manipulation, as is the case with most finance processes. Like cognitive automation, SolveXia does not require the help of any IT team to deploy.

Instead, process designers can automate data transformations without coding, with the aid of the solution’s drag-and-drop library of actions. A solution like SolveXia is best used for reporting and analytics, or to carry out processes like reconciliations, revenue forecasting, expense analysis, and regulatory reporting.

How to Choose Robotic Automation vs Cognitive Automation?

The choice between robotic automation versus cognitive automation doesn’t have to necessarily come down to one or the other. It may better be framed as a question of when to deploy each within your organisation.

You’ll want to consider your business goals, as well as the processes that help you achieve these goals. Do the processes rely on structured or unstructured data?  If it’s the latter, then cognitive automation will be your best bet. Another obvious consideration is budget and cost.

That being said, many organisations begin automating processes by using robotic process automation because it is relatively low cost and simple to deploy. It’s a good starting point to ensure that your team is aligned and on board with this type of technology.

Once they realise the benefits (which will undoubtedly happen quickly), then you can progress by introducing more capable technologies into the mix. At the same time, you can complement RPA by deploying a more analytical solution like SolveXia’s automation tool.

What are the Variations of Cognitive Automation?

In order for cognitive automation to function, the technologies behind it are a subset of deep learning and machine learning.

Here’s a simple way to match up the technology to the human cognitive function that it mimics:

• Computer vision, or image processing = vision
• Optical character recognition (OCR) = read
• Natural language processing (NLP) = understand
• Sound processing = hear

What are Examples of Cognitive Automation?

Cognitive automation use cases are expansive. Across industries, organisations are investing in cognitive automation to cut costs, increase productivity, and better service their customers.

Some examples of cognitive automation include:

1. Customer Communication and Onboarding

Cognitive automation can be used to execute omnichannel communications with clients. Consider the use of chatbots, for example. Chatbots are able to directly talk to customers and process unstructured data, as if it were human.

In turn, a chatbot can be used to open a new customer banking account without the need for any human intervention. The customer could submit a form to the bot, the bot could then extract the necessary data using optical character recognition (OCR), and process that data to run a credit check. If all looks good, the customer can be added to the CRM as a new client.

2. Claims Processing

The labor-intensive process of claims processing can be managed by cognitive automation tools. The software can pull customer data from previously submitted forms in the system. Or, instead of a human having to enter data from printed forms into the computer, the cognitive automation software can scan, digitise, and pull the required data from these sources to save time and reduce errors.

Closing Thoughts

The various forms of automation solutions exist to make business processes run more smoothly and securely. Depending on your industry, needs, and budget, you can find an automation solution that is well-suited for your business goals.

Cognitive automation is a more complex form of automation that may require a greater investment. As such, most organisations will begin with solutions like robotic process automation and/or human analytical automation like SolveXia to begin transforming their business.

If you’re interested in seeing how SolveXia can help you make better business decisions and transform raw data into valuable insights, we invite you to request a demo.