Generative Data Intelligence

RPA Compliance: Everything You Need To Know About Robotic Process Automation in Compliance

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An RPA Center of Expertise (CoE) can generate and standardize data for custom analytics, as well as pull data for internal and external auditors, including automation checks for field completeness, duplicates, and validity, among other things. As a result, internal compliance will no longer have to spend time coordinating and acquiring data.

Bots can assist in automating the data collection and classification stages of the annual risk assessment process. They accomplish this by obtaining early input from participants and identifying key trends. This enables in-person discussions to focus on trend analysis and deep dive into the organization’s concerns.

Bots can help in the processing of data populations during sampling and initial evidence gathering for standard evidence for controls. Not to forget, automated bots can do so more efficiently and precisely than humans. This is very useful when dealing with big populations that require a lot of processing time, such as examining hundreds of statement papers.

Bots can do control testing, especially in standardized sections where tickets and fields are utilized routinely. Internal audit is no longer necessary to complete those routine checkmarks.

Internal compliance experts can receive additional coverage across the organization (more data, transactions, etc.) without increasing the time or FTE required to analyze huge data populations by having a bot manage and drive the whole analytics. RPA also enables teams to identify outliers in data/transactions and focus on them.

RPA is especially beneficial to internal compliance teams that constantly engage and coordinate with the company and external auditors. Internal compliance can shift its attention from supporting external compliance operations like evidence collecting and sample gathering to operational reviews with the business, thanks to audit automation.

Automation in reporting and project tracking enables on-demand visibility into performance – both in terms of the plan and individual KPIs.

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RPA Use Cases for Compliance

Risk monitoring, risk controls, and risk reporting are areas where RPA is used.

The following are some of the specific use cases that are now seeing a lot of RPA adoption across organizations:

Anti Money Laundering (AML) alerts

The majority of the processes for researching and addressing anti-money laundering warnings are manual or semi-automated, making RPA a viable option.

Onboarding of KYC

Connecting diverse data from numerous internal systems and external sources during the know-your-customer onboarding process is a challenging endeavour.

RPA has the potential to be useful in this domain as well. These robots, for example, can collect and retrieve data from regulatory organizations such as the Securities and Exchange Commission (SEC) and law enforcement agencies such as the FBI and Interpol, as well as assist in the onboarding process. In addition, RPA has been used by several banks in the KYC process, such as document gathering and validation.

Internal and External Reporting

The process of obtaining data and preparing internal and external regulatory reports is largely manual in many banks. For example, daily liquidity coverage and delinquency reports are frequently created manually in banks and can be automated using RPA.

Limit Management

Risk officers assess and close limit breaches or violations as part of the limit management process. Because the resolution entails manual data assimilation from several sources and manual analysis to arrive at judgments, cognitive RPA solutions can assist in the limit management process by utilizing RPA for data assimilation and machine-learning approaches to aid decision-making.

Reconciliation

Reconciliations happen at many levels in banking, and they’re also a big part of internal and external management reporting. However, most of the reconciliation operations, particularly in data gathering and preparation, are manual in nature and might benefit from RPA.

Remediation of mortgages

Mortgage lending, in particular, accounts for a significant portion of retail lenders’ revenue.

In these remediation scenarios, both banks and regulators want to guarantee that client interaction are responsibly managed. Now practices such as using the interest rate, calculating fees for overcharging/deductions for late payments or deductions for equated monthly instalments (EMI), or handling customer complaints require lots of hard work and precision.

Also, because of the enormous volume, completing all of the corrective stages, beginning with scoping a client refund or modification, might take months.

RPA can solve these problems by automating all the processes while maintaining precision.


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Methodology to Implement RPA in Internal compliance

1. Make a list of the processes you want to automate.

RPA isn’t appropriate for many business processes. Instead, businesses should devise a strategy for selecting the best processes and then prioritizing them based on factors such as complexity and return on investment. Then, consider how automating these activities will appear, what it will accomplish, the business context in which it will be used, and how it will fit into future business operations or the overall automation journey.

2. Perform a Feasibility Analysis

Perform a feasibility analysis for each process to determine how much can be automated.

This is a two-step process that involves examining the process and determining technical viability. This assessment should be carried out by the operation user, an SME (Subject Matter Expert), and an RPA expert.

3. Make any necessary adjustments

Determine whether procedures are not structured, standardized, optimized, recorded, or implemented as planned based on the feasibility assessment study. Attempt to re-optimize and restructure the process at this point.

4. Collect user testimonials

A user story defines the aspects of an application that will be constructed from the perspective of the end-user. It goes over all of the user needs in great depth. It’s also critical to obtain a thorough description of each operation that will be automated. Develop a process description document with defined RPA processes for the development team based on this information.

5. Begin the development procedure

The development process begins at this step, depending on the RPA workflows that have been generated. Using RPA tools such as UiPath, Blue Prism, and others, the developers generate automated scripts and program code. Because each RPA solution has its own set of capabilities, firms should be very particular when selecting the right tool for their purposes.

6. RPA Process Validation

Conduct extensive testing to examine performance in all possible scenarios and to identify faults when the procedure is run. Send any potential performance or bug issues to the development team for resolution.

7. Double-check and deploy

Once the development teams have corrected the initial tests and problems, double-check the results and deploy the entire RPA solution.

FAQs

What steps should I take to ensure that my RPA systems are compliant?

  1. Move critical data and privileged credentials from scripts and any other vulnerable areas to an encrypted, central location.
  2. Apply the lowest degree of privilege to the RPA bots and only give them privileged access when it’s absolutely necessary to complete a specific task that requires access to a secure application or data source.
  3. Secure access to your RPA technology by using complex credentials that are constantly reviewed by RPA administrators, as well as isolating and monitoring RPA processes for suspicious activity.
  4. Create alerts that will stop all activity if any of these things happen.

What are some challenges in RPA Implementation?

  • Wrong expectations of RPA
  • Using the wrong tools
  • Working with an inexperienced RPA partner
  • Inability to calculate ROI
  • Identifying the wrong processes for RPA implementation
  • Technical and operational issues
  • Stopping short of the full, end-to-end process
  • Lack of support from leadership
  • Shortage of skilled team
  • Preparing the workforce for a shift in workload

What Is the Difference Between RPA and Traditional Automation Solutions?

The “ability to learn” is the main factor that distinguishes robotic process automation from classical automation.

The bot’s learning algorithm minimizes the number of false positives and offers more accurate findings over time. However, the true benefit of Robotic Process Automation comes from the increased efficiency gained as the automation becomes more precise.

What are some Key Considerations before Implementing RPA?

Before you implement RPA, there are a few things that you must keep in your mind, such as:

1. Define the automation vision and strategy in detail. To do this, seek out procedures that:

  • Have a well-defined Return on Investment (ROI) (ROI)
  • Relate to an area where the company faces a significant business
  • Obtain data that is both dependable and of high
  • Are they rule-based and largely consistent throughout
  • Are they time-consuming and prone to human error?

2. Identify the most viable tests and procedures for automation by defining roles, responsibilities, and structures.

3. Develop standardized documentation and processes for approving designs and deployment methodologies. Don’t assume that existing manual procedures are policy-compliant or ready to be automated. Before deploying a new system, some inefficiencies may need to be addressed.

4. Collaborate with your security team to establish bot authentication mechanisms and develop privacy and data security regulations.

5. Clearly define change management processes and procedures.

6. Test and monitor on a regular basis.

Likewise, there are some factors to consider after RPA implementation. Have a look at them all:

  1. Consider metrics and how to track them. For example, how will you calculate ROI over the bot(s)’ lifetime?
  2. Consider establishing a robotic centre of excellence (CoE) for improved governance after successful development and rollout.
  3. Devise a strategy if the bots aren’t performing as intended.

How does RPA help in conducting background checks and preventing fraud?

Anti-money laundering rules require banks to verify that the source of their customers’ funds is legitimate. In addition, assessing the risk of money laundering necessitates regular client monitoring and screening. Regrettably, these required and critical duties can consume a significant amount of time.

You may use RPA bots to swiftly and efficiently execute background, credit, and fraud detection checks on each customer, alerting you to any danger indications. The reports can then be stored in a centralized area so that you can prove compliance when necessary.

What are some consequences of noncompliance?

  • Financial repercussions/penalties: Non-compliance comes at a high price. The average cost of a single noncompliance occurrence is $4 million, while the total cost of noncompliance is $14 million.
  • Audits of compliance: Compliance auditing takes time away from revenue-generating activities for business owners and staff.
  • Suspension or dismissal: A non-compliant corporation may be required to cease operations or shut down entirely, depending on the severity of the violation.

Nanonets online OCR & OCR API have many interesting use cases that could optimize your business performance, save costs and boost growth. Find out how Nanonets’ use cases can apply to your product.


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