Five Ways to Use RPA in Finance

The robot then updated the transaction numbers for any trade matches that had been identified in a spreadsheet. We were unable to find any C-level executives with AI experience on the company’s team. Discover how automation can transform age-old practices into cutting-edge processes. Your finance department can easily prepare current financial statements using RPA, even on a daily basis. Your business leaders can make the most informed decisions and act with agility when they have the most up-to-date financial information.

Finance automation got a kick-start in the 1990s, when MIT researchers developed the optical character recognition (OCR) technology for reading the handwritten parts of checks with high speed and accuracy. The tools can manipulate data, trigger responses and communicate with other systems in a way that previously required human interaction. Customer service is a critical function that impacts customer satisfaction, retention, and loyalty. However, customer service also faces many challenges such as high volume, complexity, variability, and expectations of customers.

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Based on the earlier outlined use cases of RPA in banks, you can get an idea of your own stellar case study. Correlate those examples with your company and estimate the investment vs. gains that RPA will bring. Study the RPA requirements in your specific situation and evaluate the time, resources, and efforts necessary for the implementation. Once we have stated the powerful use cases of the technology and techniques, let’s compose the overall picture of the process of RPA deployment in banking and finance.

This was in line with the expectations of organizations at proof of concept or pilot stages, which were targeting just under 20 percent of capacity in their operation. However, among organizations that are already scaling robotics, the average target was as high as 52 percent of capacity. Those implementing at scale believe their digital workforce will exceed their human workforce in terms of delivery capacity, for administrative and repetitive tasks. Banking and financial organizations can use AI capabilities to make RPA automate the complex processes that require decision-making. This further enables employees with smart AI agent assistance while resolving customer queries and enabling smart conversations with instant resolution.

Boost operational efficiency

Finance and Accounting involve long strings of numbers and repetitive, rule-based transactional processes. Upon successful implementation of RPA, financial institutions can accelerate these transactions while enjoying increased efficiency and reliability of data with minimal errors. Natural language processing, (NLP) is one AI technique that’s finding its way into a variety of verticals, but the finance industry is among the most interested in the business applications of NLP. In fact, according to our AI Opportunity Landscape research in banking, approximately 39% of the AI vendors in the banking industry offer solutions that involve NLP. With Document Understanding, robots read invoices that have been processed and are ready for payment, digitizing your payment processing procedures.

Policy violations and data discrepancies can also be intimated to the concerned individuals/departments with the help of automated alerts. Explore how RPA accelerates finance and accounting processes, from faster billing to fraud detection, optimizing reporting & cost savings. RPA empowers finance and accounting professionals to make informed decisions and drive continuous process improvement. Kofax recently announced that the latest version of their Kapow software also leverages AI and machine learning for automated document capture and desktop virtualization. Kofax launched what they call an intelligent screen automation for remote desktop environments. Users can use Kapow to speed up the development of software robots by using a new AI tool that allows the software to automatically identify user interface elements, such as labels and buttons.

Real-World Examples of RPA in Finance

New customers can open new accounts and apply for additional products in minutes with automated Know Your Customer (KYC) validation. RPA technology drives down operational costs by automating the transaction-heavy, manually intensive tasks that require reconciliation. Digital workers can retrieve and compile data from multiple back-office systems, reconcile amounts (say, for invoice payments or billed amounts) and take action to resolve breaks in real-time.

Auditing should undergo automation at a slower pace so you can assess its effectiveness and adapt as needed, but its effect can be impressive. With the right tools, you can streamline many of the most time-consuming tasks in auditing while improving data visibility and process outcomes. RPA bots can handle most activities in tasks such as payroll, record keeping, reporting, and account payable and receivable. “RPA can automate and speed this process up, as well as reduce human errors,” Dean said.

Challenges of implementing RPA in finance

In these organizations, investment is significant and rising, typically in the $2m to $4m range for those with strategic or enterprise-wide initiatives. Of those that have already implemented RPA, 78 percent expect to increase or significantly increase investment in RPA over the next three years. From your business workflows to your IT operations, we’ve got you covered with AI-powered automation.

• Robotic Process Automation is the technology that is currently revolutionizing the operational aspects of businesses.
• To help detect and prevent fraud, financial institutions need the right cybersecurity technology for due-diligence checks, sanctions screening and transaction monitoring and investigation.
• By optimizing your office for data-driven decision making, you’ll be running smoothly, giving your team back time for the work that matters most.
• Robotic Process Automation offers significant benefits in many areas for large and midsize companies.

Particularly time-consuming tasks include manual verifications of identity documents. Know Your Customer (KYC) processes are obligatory and indispensable to the rpa applications in finance onboarding routine. Furthermore, banks can combine automation with artificial intelligence, which allows them to replace even more types of repetitive jobs.

Automated Reporting

The data used in the financial industry is huge and complex, but the regular automated reports prepared by RPA bots help the employees to be better informed and provide par-excellence customer service. The positive value added to enhance the customer experience has significantly transformed the business model. Business leaders in finance who are familiar with RPA might be interested in adding artificial intelligence capabilities to their software robots to optimize their functioning over time. In the next two to five years we expect that business processes involving document digitization (extracting information from non-digital formats like paper) might be automated using intelligent OCR and NLP. We might see RPA platforms leverage machine learning to automatically prompt businesses with insights on improving efficiency. RPA might still be a necessity only for firms with large enough scale of operations where the integration and capital costs are justified by the cost savings achieved through the automation.

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RPA Use Cases in the Banking and Financial Sectors

Accordingly, you can have a lean, cost-efficient team by reducing operational costs while ensuring high compliance standards and minimal human errors. Although automation has affected multiple business processes, many financial tasks have remained manual. The lack of appropriate resources, solutions & organizational uneasiness of placing sensitive functions in the hands of robots is the most significant setback for introducing RPA in finance. The finance department is vitally important in ensuring workflow efficiencies, reducing risk, and becoming a strategic partner to your business. UiPath offers AI-fueled, end-to-end robotic process automation (RPA) that enables finance-driven innovation. It reduces costs, processing times, and risk to increase both accuracy and your team’s capacity to focus on high-value, strategic work.