How to automate backoffice tasks with OCR and machine learning

How to automate backoffice tasks with OCR and machine learning

Over the past 20 years, back office outsourcing has been the go-to solution for large enterprises looking to save costs on repetitive, labour-intensive work. Next to cost reductions, a big benefit of moving the back office to low wage countries used to be the availability of a large labour force that allowed easy scaling. Countries like the Philippines, Indonesia and India used to be very popular countries to go to.

As with everything, technology is now catching up with traditional ways of back office outsourcing. The new norm is not to simply oursource, but to actually automate back office tasks using modern technologies like RPA, OCR and machine learning. 

Automating allows for even higher cost reductions, faster turnaround times, lower organisational complexity and fewer compliance risks. In this blog, we will explain how you can automate your back office and what the benefits of back office automation are.

Jump to:

What is back office automation?
Why is back office automation a good alternative to back office outsourcing?
What are the benefits of back office automation?
What use cases can be automated?
Loyalty and cashback processing
Accounts payable automation
KYC automation
How does it work?
Human-in-the-loop automation to handle dropouts
Automating your back office with Klippa


What is back office automation?

To answer that question, let’s first determine what back office tasks are. Back office tasks are all administrative tasks within an organisation. These tasks usually arise from legal (contract processing), customer onboarding (KYC), compliance, HR (employee onboarding) or financial procedures (accounts payable). Think about tasks like data entry, document sorting, approvals and fraud or compliance checks. 

A back office task every company will know is invoice processing, usually done by the finance department. Of course, at low volumes it’s totally fine to have a finance employee manually processing 50 invoices per month. But what happens if you need to process and approve a million invoices per month? Will you scale your finance team from 1 to 100 people, or will you try to automate this task? 

This is where back office automation comes in. Back office automation is applying software to automate repetitive tasks that administrative employees are now performing manually.


Why is back office automation a good alternative to back office outsourcing?

Even though back office outsourcing can deliver big cost- and scalability benefits, it also has a few downsides. One of the major drawbacks is compliance risk. Offshoring back office data to countries like India or the Philippines comes with (privacy) risks. Are the employees trained well? Do you have permission from your customers and local authorities to share their data (GDPR)? How do you prevent a data breach? These are some of the challenges you might face while outsourcing. 

The cost of processing back office work in a low wage country is of course lower than in Europe or the US, but what if it could be even cheaper? And from a scalability perspective you could theoretically try to infinitely scale an outsourced team of people, but is this manageable in reality? And can you speed up the turnaround time towards real time processing by training people? Probably not. 

So to solve these issues you have to look for an alternative to back office outsourcing: back office automation. In the next paragraph we will highlight why you don’t have these issues with a back office automation solution and show that it’s a good alternative to back office outsourcing.


What are the benefits of back office automation?

With automation you can take the human factor and foreign regulations out of the equation. This has benefits from the perspective of cost, turnaround time, organization complexity, scalability and control:

100% control

If you choose an automated solution over an outsourcing solution, you ensure total control. Automated solutions can be deployed in your own country, under familiar law and within your own IT infrastructure. Therefore, you do not depend on third parties and their local regulations for your business needs and keep 100% control.

Cost savings

While outsourcing might already reduce your cost over local processing, automation can get you an even bigger cost reduction. We see cost reductions in the range of 50 to 70% on average depending on the task complexity, when compared to outsourcing.

Realtime turnaround times

While outsourcing might speed up your processing time, this is mostly due to a bigger workforce. This bigger workforce can simply get more work done within the same timeframe, but does not really do a single task faster. But what if you are looking to reduce your turnaround time to nearly real time? Then, outsourcing is not the way to go. An automated solution can process most administrative tasks within a few seconds, so nearly in real time. Something a large outsourcing crew could never achieve.

Infinitely scaleable

While you could theoretically scale an outsourced back office from 100 to 1000 or even 100.000 back office workers, the operational complexity that arises with scale makes it very hard in reality. An automated solution, on the other hand, can automatically scale its servers on demand without any additional recruitment, office space, contracts and so on.

No compliance risks

Outsourcing your privacy-sensitive data to a low-wage country may remove your business from compliance to, for example, GDPR regulations. When extending these tasks outside of your control, you can never be sure if your data is handled securely. With back office automation, you are always in the driver’s seat. Servers on which data is processed can be placed locally and data that you send to those servers are never saved, but simply returned to you. This is a form of safety and security that an outsourcing company could never guarantee.


What use cases can be automated?

By default any high-volume repetitive task that includes data entry, document sorting, data verification or approving could be automated. We will highlight a few use cases to inspire you to start looking for similar procedures that could be automated within your own organization. 

Loyalty and cashback processing

Many loyalty and cashback campaigns require participants to send in a proof of purchase (receipt or invoice) in return for some kind of reward. But how do companies determine that the sent in proof of purchase is valid, falls within the campaign’s date range, that enough money was spent or that the required products have been bought? Many loyalty companies have outsourced back offices for this.

Automating loyalty back office tasks is of course the better choice. Rather than using up error-prone human focus, the Klippa OCR API can perform all these checks, including duplicate detection, cheaper and within just a few seconds. Yearly we process millions of proofs of purchase for marketing campaigns.

Accounts payable automation

This is probably the most common process within any company: entering received invoices from your suppliers from your inbox into your accounting or ERP software. A tedious and time-consuming task. Invoices come in many shapes and sizes and it’s easy to make mistakes. At the same time it’s extremely repetitive, because some invoices from certain suppliers might come in multiple times a day or month.

Automating your accounts payable process generally starts with capturing invoice data in a digital format. This involves a form of scanning or capturing method with the help of OCR, such as Klippa’s OCR solution. The text is extracted and processed. The software will then manage the coding and routing of the invoice through the digital workflow, all the way up to your ERP or bookkeeping system, with which it is integrated.

The accounts payable process

KYC automation

Many companies, specifically in the rental, telecom, banking and insurance sector, are obligated to verify the identity of their customers. This is part of KYC regulations. An old school example of this process is going to a physical banking location, presenting your passport and signing some forms. After that, a banking employee will check and enter this data into their systems. A very costly process that is hard to scale. It is also hard to outsource to low wage countries due to privacy regulations and the risk of data leaks. 

Luckily this can also be automated via the Klippa Identity Verification API. Using our Camera SDK, customers can scan their passport from home by taking a picture with their smartphone, combine this with a selfie and a signature and Klippa will do the rest. This also applies to KYC processing with debit or credit cards, tax statements, salary slips, utility bills. We will automatically determine the authenticity of the scans and extract all the data points you need. Automatically processing identity documents is easy with Klippa.


How does it work?

OCR and machine learning are at the base of many automation solutions. With the help of OCR, it is possible to identify the text in documents and images. As soon as you have the text, you can start gaining an understanding. By using machine learning, it’s possible to identify data points that are interesting within text and you can mimic human behaviour by learning from previous examples. 

Let’s take a look at an example of what OCR can do for you:

Through OCR, the pixels that contain text are identified and extracted into digital text. The act of manual data copying is replaced directly with OCR. With an accuracy of more than 95%, all text is extracted, whereas manual data copying would have a significantly lower accuracy and costs much more time. 

Now let’s take a look at an example of what machine learning can do for you:

Machine learning grows in effectiveness when fed with more and more examples. An AI is trained with numerous examples of documents and specified data sets so that it can automatically localize and identify specific text on a specific position on the document. Over time, a machine learning model can therefore only get better. All data is automatically contextualized and converted to a JSON-format.

Now it’s clear how automation can work, let’s discuss what the process of implementing a solution looks like in four steps:

Looking at current procedures

Identifying the steps taken in the current back office workflow is the start of any innovation process. What documents are you processing, who is doing the processing, what are the steps they take at what stage? These are all relevant questions at the start of your journey towards automation with OCR and machine learning. Once you’ve identified the taken steps, you can start determining which steps can be replaced with automation.

Gathering data and data annotations

It is important to gather as many and various examples of processed documents as possible. In these example documents, specific segments are all annotated with contextual information to identify what each segment contains. The more examples are annotated, the merrier you will be with the outcome. You’ll create an enormous dataset full of valuable information, which is imperative for the training of a model.

Training an automated solution

With the aid of a framework such as Yolo, the dataset can be quickly fed to a machine learning model, so that it is trained with all possible examples. The model learns how to interpret data thanks to the annotation performed in the previous step. With enough training, such a model can perform data contextualization by itself without the need of human involvement. When the model proves accurate and quick enough, it can go live and can be implemented in a solution.

Implementing the solution

The trained model is now ready for deployment in a solution, such as Klippa’s OCR API. You send a request to the API, the API deploys the trained model to automatically identify the information on a document and quickly and accurately returns the desired data for further processing or application. With this API, you have your automation solution ready to be implemented.

Instead of setting up and implementing an entirely new tool yourself, you may prefer to integrate these technologies into your existing workflows. Many enterprises are already using RPA vendors like AutomationAnywhere, UiPath, BluePrism, Mendix or others to automate certain workflows. From a workflow perspective these solutions are all good. But what you will often see if you look at their OCR and ML capabilities is that their built-in solutions are not adaptable enough to reach a high degree of automation for your niche use case. 

That’s why Klippa offers its technologies as plugins for all major RPA vendors, such as Automation Anywhere, UiPath, or Mendix. Simply switch on our plugin and integrate it into your workflows. Our solutions can be used for classification, data entry and verification on many different use cases. A few examples are automated receipt processing, automatically reading identity documents and accounts payable automation

There might be cases, however, where you can’t fully automate your processes at this moment in time. When this is the case, we’ll have to look at a best-of-both-worlds approach.


Human-in-the-loop automation to handle dropouts

Of course, technology is not always perfect. Even though it evolves very rapidly, you might have certain back office tasks that can not be automated 100% (yet). Luckily, there are solutions for this as well. By combining software with the power of humans you can create a best of both worlds scenario, also called human-in-the-loop automation. 

With a human-in-the-loop solution you can automate a large portion of the procedure and then have a human review and complete the work. Meanwhile, the system will learn from any human-made changes and with that improve over time. So while you might start at 70% automation, which is already great, the human-in-the-loop processing will get you as close to 100% automation as possible. Below you can see a workflow with a human in the loop:

Here you can see an example of one of our data entry interfaces that your back office team can use to process the dropout in a human in the loop setup. This interface by itself can already greatly improve your current data entry procedures, because it has error prevention and automated suggestions built in:

Automating data entry tasks is but an example of one form of many back office tasks. In the end, you can automate any back office task in one way or another. That’s why it is important to make sure you explore your options when it comes to automation. And that’s where Klippa can definitely help you out.


Automating your back office with Klippa

You can opt for setting up a training model and feeding it numerous annotated data examples yourself. But why do so, if Klippa can already offer you a ready-to-implement and proven solution? Make sure to contact us at [email protected] or to book a demo below, if you’re looking into how automation can serve your business.

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