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How Robotic Process Automation is Changing Finance & Accounting

Posted by Tim Clark on Dec 5, 2019 10:40:00 AM

How Robotic Process Automation is Changing Finance & Accounting

By now, just about every industry has found a way to incorporate robotic process automation (RPA) into its workflow, but so far, banks are leading the way. Why? Because succeeding in today’s global financial markets requires “unprecedented levels of speed, accuracy, and cost efficiency beyond what a human workforce can provide.”

Financial services jobs increasingly involve digesting and analyzing huge amounts of data, ensuring compliance with complex regulations worldwide, and handling an overload of repetitive, rules-driven work—all of which make RPA and finance a perfect match. (For a detailed explanation of RPA, check out this article.)

Below are four practical examples of RPA in accounting and finance, as well as a few specific RPA use cases for several companies that have already begun implementation.

4 Use Cases For RPA In Accounting & Finance

1. Property Tax Appeals

It isn’t unheard of for an appraiser to incorrectly assess the value of a business property; this outcome is typically due to the appraiser having imperfect or inaccurate data.

Most organizations use a combination of people, enterprise software (e.g., SAP), third-party software, and home-grown spreadsheets to manage their data. Despite the number of systems involved (or maybe because of it), heavy manual effort goes into reviewing data and uploading it between software applications. These disjointed efforts result in data that is far from ideal for appraising.

Adding to this challenge is the limited time organizations have to appeal an appraisal. To effectively identify and address an area of appeal requires significant human effort, including gathering, consolidating, and analyzing a large amount of data across multiple sources. RPA can quickly handle the first two parts—gathering and consolidating—which typically consume most of the time allotted to prepare an appeal. The right RPA solution effectively deployed can generate a single, unified document that provides all the information needed for a tax team’s analysis. (Tweet this!)

This gives tax practitioners more time to focus on exploring dispute opportunities and refining their strategies. As a result, they are better able to not only provide a timely response to property appraisers but also generate potentially huge savings in tax bills.

See how easy it is for your property tax team to start using RPA—schedule a free demo of CrowdReason software today.

2. Mortgage Lending

Currently, the back offices of mortgage lenders are inundated with documents related to loan origination. Borrowers are required to send a number of documents electronically, which then must be verified by lending teams.

The verification process includes many repetitive elements, such as reviewing and confirming the accuracy of data on everything from identity to income to assets. Given the formulaic nature of these documents, there is a prime opportunity for automation.

Through capabilities such as optical character recognition (OCR), screen scraping, data entry, and rules application, software robots are able to perform most of the review and verification process. They can also handle the task of alerting borrowers about the receipt and verification of their documents.

RPA enables the lending team to focus on handling exceptions, such as when documents are unrecognized or are of poor quality. Human intervention can then provide the quality assurance required to approve the document, including contacting the borrower.

3. Bank Reconciliation

Any business that keeps good books knows the headache of reconciling accounts. Whether performed daily, monthly, or annually, reconciliation can be a tedious and error-prone process when done manually.

This isn’t surprising given the complexities involved:

  • Multiple locations or business entities
  • Numerous payment methods
  • Vendor payments made at different times using varied payment methods

Accountants spend days matching transactions and hunting for discrepancies, with no guarantee they’ve found them all.

RPA can make the reconciliation process seamless, significantly reducing the need for manual intervention. While humans can only process a few transactions per minute, software robots can process thousands. Thus, a process that usually takes days is reduced to minutes. Accountants are then free to fully address transaction exceptions that are presented by the RPA system, including partially matched transactions and unmatched transactions (i.e., transactions present on the bank statement but not in the general ledger).

In addition, they are able to provide greater value to the business in terms of real-time support and analysis, strategic advisement, and forecasting.

How To Find The Best RPA Use Cases

Although most experts predict that RPA will achieve high adoption rates in the near future (with some outlets predicting it will reach near-universal adoption at some point in 2023), many financial firms still struggle with the best way to implement the technology. For one thing, it takes time to review current processes and identify areas where RPA can be of best use; others simply don’t have a “culture of innovation” that would drive them toward change.

To start, look for simple tasks that can represent an “easy win.” For example, CB&S Bank first decided to automate small, specific tasks, like data entry; it also applied bots to loan document retrieval, and moving data points from those documents to various other systems. The bank estimates that automation of small tasks like these and several others saved its employees about 800 hours per year. Having achieved a win—and also learned more about RPA—the bank now plans to take a “big leap” and apply RPA to more challenging financial processes, like identifying cases of fraud.

In evaluating processes for possible RPA application, consider the following:

  • Is the task:
    • Repetitive?
    • High volume?
    • Rule-based?
    • Prone to human error?
  • Is the task performed more than once per week?
  • Is it a time-sensitive task for which there are limited staffing resources?

If the answer to the above questions is “yes,” then the task you’ve identified is likely a good candidate for RPA. Avoid applying RPA to tasks that require significant decision-making, infrequent or intermittent tasks, or overly complex processes.

4. Fraud Prevention

Banks continue to experience increasing levels of fraud loss through identity theft, card not present fraud, cyber attacks, account takeovers, and more. In addition, they continue to spend more money on fraud tools: A recent report predicts that, by 2022, financial services organizations and merchants combined will spend as much as $9.3 billion annually to combat the problem.

Part of the issue is the complexity of banking processes, many of which rely on data housed in a variety of sophisticated systems. Rather than depending on humans to find and pull the appropriate data, RPA software can quickly comb through massive datasets from different channels (credit, debit, loan, mortgage, etc.) and build valuable financial profiles that can be used to identify fraud patterns or trigger fraud alerts. Software bots can also be “trained” using machine learning to help gather evidence of fraudulent activity, which can be a tedious, time-consuming task.

Not only can RPA accomplish the task of data-gathering more quickly (and therefore more cost-efficiently) than humans, it also eliminates the risk of human error in the process.

Companies Using Robotic Process Automation

The RPA use cases listed above only represent a select few of the opportunities where this technology could potentially be applied. But which companies are using RPA in accounting and finance right now—and what benefits are they experiencing as a result?

  • Sumitomo Mitsui Financial Group is currently experimenting with an advanced technology solution called AOR that automates data processing of unstructured documents, such as handwritten and non-standard documents, that typically require manual processing. Proof-of-concept testing has shown that manual data entry was reduced by approximately 80% since the tool has been implemented.
  • Comcast uses RPA-enabled property tax software to automate data extraction from tax documents. Prior to implementing the software, Comcast needed 20 people for compliance activities; now compliance can be managed with just six people, with the remaining team members working on tasks that have greater financial impact.
  • Ernst & Young is a unique example in that it provides RPA in accounting services for its clients. In one instance, its Shanghai tax services team developed an RPA solution that would automate the tedious value-added tax returns process for a financial technology client in China. The new, automated process was reduced to 280 hours (compared to the previous time of 1,400 hours); morale at the Chinese company improved as a result.
  • First National Bank of Wynne began using RPA as part of its acquisitions process, to help with migrating customer and account information from banks it has acquired to its own system. The task is able to be completed in much less time with RPA; the new system is also better at reporting errors and validating data. Reports say that the RPA process has reduced the bank’s conversion costs by 70%.

Transform Your Finance Function with RPA

Wondering if you should implement RPA at your accounting or finance firm? To stay competitive, the question isn’t whether you should embark on the RPA journey; it’s deciding on the best way for your firm to implement it. The efficiency gains and productivity boosts generated by your initial efforts are likely just the beginning of the benefits robotic process automation has to offer finance companies like yours down the road.

Tim Clark is a software developer, technician, and seasoned project manager. In a career spanning three decades, he has delivered solutions for start-ups, non-profits, and the largest Fortune 500 companies. In his position as Senior Manager at IPD Solutions, Tim focuses on leveraging technology to streamline operations for his clients in the insurance and financial sectors.

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Topics: Automation in finance, Automation