How to Use RPA in Finance?

Financial team uses RPA to improve the speed, efficiency, accuracy, and scalability of certain financial services and generate values for financial institutions.


Introduction

Defining internal control and governance for finance robotics programs is essential: Clearly delineate responsibilities between bot development, bot operations, and bot outputs to yield full utilization of finance robotics and cost savings. [Joey Mixon- Director, Advisory, Gartner]

RPA is a versatile technique used across several industries as the use of low-code software "bots" to manage the repetitive, time-consuming tasks of human staff such as invoice processing, data entry, compliance reporting, etc.

RPA robots can automate numerous repetitive tasks without human intervention. These robots support employees to diverge on other imperative tasks, including building strong client relationships, interpreting customer data to achieve competitive advantages, and converting great ideas into new financial products.

Being one aspect of hyper-automation, RPA allows businesses to deviate from automation that mimics human behaviors to advance automation that uses data to optimize end-to-end finance operations.

Here’re the possible benefits of implementing RPA for financial services;

  • Allows companies to scale financial operations when required.

  • Cut down expenses and save time.

  • Automate data to deliver higher accuracy and increase efficiency.

  • Minimize IT department interference and ensure no additional infrastructure costs.

  • Reduce business risks and drive sustainable growth.

6 Ways RPA Advances Financial Services

Improving Fraud Detection Capabilities

Using RPA and optimized processes, companies can detect fraudulent activities based on specific usage patterns. Financial institutions require the right cybersecurity technology for due-diligence inspection, sanctions screening, and transaction monitoring and investigation to detect and prevent fraud.

RPA improves the speed and accuracy of fraud detection. RPA bots examine whether the data complies with federal anti-money laundering (AML) regulations or not. By evaluating variations, ML delivers insights on why frauds occurred and flags any possibility of potential fraud.

Optimizing Finance Reporting

Tracking profit and loss on a daily basis is the optimum technique to monitor financial success/performance. Updating Profit & Loss statements manually is tedious and time-consuming. RPA can ease this task by creating flawless reports in real-time. RPA robots make business procedures more transparent while ensuring financial forecasts accuracy. In addition, human errors are widespread in financial procedures. RPA eliminates human inconsistencies and delivers accurate results while allowing companies to compile data for financial reporting more reliably.

Managing Regulatory Compliance

Using RPA, Financial institutions can govern the financial process and narrow the risks associated with regulatory fines and reputational damage. Also, RPA secures from particular sources or documents to reduce the manual business procedures during compliance reporting.

Machine Learning models determine what sort of data an auditor can need for reviewing: identifying and placing it in a convenient location for faster decision-making.

Reviving Customer Experience

From initial onboarding to all account updates, RPA solutions are improving customer experience in their entirety. Today, consumers have more options for financial services and have high expectations for personalized services, fast processing time, and customer support. With automated Know Your Customer (KYC) authorization, new customers can open new accounts and apply for additional services in a few minutes.

RPA can notify stakeholders about specific events, for example, customer complaints regarding mobile banking, positive or negative feedback, and more. RPA robots can analyze similar data of previous complaints/feedback to anticipate opportunities for improvement.

RPA in Accounts Receivable

Companies can automate the accounts receivable section because this is little dependent on external documentation. For instance, an accountant might forget to raise/send an invoice; this affects the cash gap, jeopardizes the order of the cash process, and impacts liquidity.

Adopting RPA bots as companies’ digital workforce, they can automatically send invoices. Automating this task can streamline cash flow without any gap. Apart from the cash gap, RPA assists in data entry, freeing accountants from struggling with different information systems simultaneously.

The accounts receivable tasks that can benefit from RPA solutions are customer data setup and management and extracting their information from different sources, customer credit monitoring, credit risk management, invoice generation, distribution, and follow-ups and reminders.

RPA in Accounts Payable

Accounts payable is when favorable credit terms cause it, but highly risky when the other party doesn't pay bills on time due to inefficiency.

Operational delays in accounts payable are common. Vendor invoices are non-standardized, so are required to double-check purchases before approval. RPA bots can streamline this process. They can also match the purchase order to the invoice, compare them, and flag any discrepancies.

Through this process, invoice processing is accelerated, reducing the risk of costly errors, and preventing financial penalties for late or incomplete payments. RPA can help in accounts payables in many ways, such as vendor verification and setup, purchase order entry, extracting data from invoices and purchase orders, cross-checking invoices with purchase orders, payment validation and reconciliation, and many more.

Key Takeaways

RPA enables finance departments to be lean and cost-effective by handling activities such as payroll, record-keeping, reporting, account payable and receivable, etc. RPA is gaining popularity in the financial department as it effectively manages repetitive, tedious activities. They are readily combined with machine learning models to resolve more complex jobs.

RPA’s benefits include decreasing operational costs and improving compliance by eliminating potential human errors for finance capacity. These benefits allow companies to focus on strategic business planning and investor engagement. Also, automated systems are scalable, allowing businesses to grow with minimal difficulties.

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