Someone inserting their bank card into an ATM machine.

Finance operations

Hit the accuracy bulls eye

A large security company improved efficiency and accuracy on a highly manual bank reconciliation process using robotic and Watson technologies

A woman sitting on the floor of a library reading a book.

Finance operations

Automate at scale

A leading global digital education company automated a complex inter-company reconciliation process across 520 client subsidiaries, improving speed by 5x

A warehouse full of building materials.

Sales & inventory

Lead the pack with efficiency

A global building materials company improved sales and inventory reconciliation by automating time-consuming and error-prone processes

What is Process Automation?

More companies are using automation to take front- and back-office operations to the next level. While adoption of automating simple, repetitive processes through robotic process automation (RPA) is becoming more common, many organizations are still challenged with where to start and how to maximize potential. IBM Process Automation Services can help.

The IBM approach to transformation reflects a broad spectrum of business needs including basic task automation through RPA to intelligent automation with extended analytic and cognitive technologies. Digital labor strategy, change management and continuous improvement principles are the basis of how IBM drives transformation to maximize and sustain measurable business benefits for your enterprise.

Basic robotic process automation

Basic robotic process automation

Fueled by bots, RPA provides automation for repetitive and rules-based tasks that involve structured data. IBM uses business process management (BPM) libraries with select robotic process automation alliances for faster implementation to help you realize benefits more quickly.

Complex process automation

Complex process automation

IBM cognitive technologies enhance automation solutions in ways that few competitors can match. Robotics, coupled with machine learning, natural language processing and analytics, extends the reach and range of areas previously unfit for automation. This approach can create higher levels of productivity across your workforce.

Intelligent automation

Intelligent automation

The IBM automation technology ecosystem helps create the next generation of process designs and new ways of working. Cognitive self-learning capabilities drive continuous process improvements and learned orchestration that can help transform your business and adapt to the changing marketplace.

Process examples

Processes we can automate

An icon of a bank for banking.

Financial services

  • Account reconciliation
  • Fraud, regulatory, compliance
  • Mortgage approval
An icon of an umbrella for insurance coverage.

Insurance

  • Payment or funds transfer
  • Policy document transfer
  • Compliance reporting
An icon of a medic bag for healthcare.

Healthcare

  • Patient documentation
  • Claim administration
  • Member management
An icon of a satellite dish for telecommunications.

Telecommunications

  • Contract registration
  • Network automation
  • Policy management

Resources

Automate processes in 7 days

Accelerate design-to-deploy automation through reusable component models

Video transcript

[ MUSIC ]

REYNOLDS: There's been a plethora of tools come up over the last several years where they are calling themselves robotic process automation and it's really focused on how do I look at my business process and how do I actually automate tasks.

And primarily where people start initially is they start on a spot of things that are very redundant. So, you could think of something in like accounts payable, invoice processing, right?

So, a lot of people today, they try to do OCR scanning; most times, OCR scanning is anywhere from 30 to about 80 percent accurate. It depends upon your paper quality, the image quality, all those things. And as you do that, you still have to check it. So, you've got people there inputting all that thing, doing all the checking and then they're going to push it off.

So, imagine a case where you can actually now have further technologies you could use. There's technology up there like Datcap IBM has, Cloudtray that does editable PDFs, that you could pull in and now you could actually have robots actually do that. So, you improve the overall quality because the robot can actually take the information and actually then input it into the system.

And you can do that via either standard screen scraping or you could do it through VDI, using VDI input. Or, you could actually go through APIs. There are several other things you can think about things in the area of general ledger, you could think about things in HR employee data management where people need to change their address, phone number, maybe change some things with their healthcare and things like that.

So, things that where...that's where you're starting to start now looking at things that are a little bit more complex, things that are more unstructured data where you're going to need a different type of a rules technology to maybe do that.

We've got a rules technology within IBM that we've taken out of IBM Research called Watson Policy Manager. It enables you to actually write the rules in a business kind of format content. We then actually map it via a template into a set of rules and we apply it. So it enables us now to actually go and have a little bit more of a thought process around what we want to do.

And then lastly, it's really starting to think about where you really get to that cognitive automation where you start really having a sense of learning. So, as you're going through and the robot is learning, it's becoming more advanced.

And as it becomes more advanced, it enables us to take more advanced decision making in the process that's involved. And we actually are...have the ability to deploy the robots in the cloud, because what we found is that even makes it even easier to monitor and it gives us the ability to use the robots and schedule them so that a robot in theory may run one script because it runs 12, 15 hours a day, or it may run six or eight scripts because they run on a shorter period, length of time.

As we've worked with the various clients ‑‑ and sometimes the clients are all a little unique ‑‑ but we've built those modules and tried to build them in discrete units as possible which enables us then to reuse them.

And so what we've done as part of that reuse is we've got today somewhere around ‑‑ it's going to blow your mind here ‑‑ 3,000 components. You're going to continue to see this as we go more and more to cognitive and having those components and having a center of excellence is going to be key to being successful long term in my opinion.

Because of our component architecture and the way we've approached this, we've actually been able to build one as fast as seven days. So, it's really important that as you go through this process of how you set it up creating that center of excellence, creating having the development team thinking through the way you're going to do it, how you're going to run those projects...

And again, thinking about a different paradigm so that you're not either reinventing those scripts or you've got them larger so that as you grow your robotic process automation across your business can you get the reuse so you get faster time to value.

[ MUSIC ] [END OF SEGMENT]