Use Of RPA in Fintech 2024: A Complete Guide

Use Of RPA in Fintech 2024: A Complete Guide

Use Of RPA in Fintech 2024: A Complete Guide

Human error is more likely to occur in manual data processing in the finance business, particularly when handling numerical data. Unexpectedly, these mistakes may lead to over 25,000 hours of needless rework, costing over $878,000 a year. Financial institutions naturally wish to stop this trend and reduce their exposure to the possibility of human mistakes. Fortunately, RPA in Fintech shows promise as a solution in this area.

In the financial industry, robotic process automation (RPA) enhances the speed, accuracy, and efficiency of processes. This rapidly developing technology can manage data more effectively than people while saving enormous amounts of money.

Financial institutions have long used RPA for accounting and finance procedures. Approximately 80% of financial institutions have either adopted or plan to integrate robotic process automation into their business operations, according to a recent Gartner study. When it comes to RPA in finance and accounting, hyper-automation won’t seem like an exaggeration because it can accomplish up to 30 times as much work as a person.

Through its interaction with other technologies, the technology has progressed from processing basic individual tasks of automation to processing fully automated reporting, data analysis, and forecasting. Grand View Research estimates that the worldwide RPA market will reach a valuation of $2,322.9 million in 2022 and will expand at a compound annual growth rate (CAGR) of 39.9% between 2023 and 2030.

Which RPA applications are most common in the fintech industry?

RPA has several uses in the financial services industry that free up human resources so they may concentrate on more important work. These are a few noteworthy RPA applications in accounting and finance that are well worth your time and money.

PO Processing

Fintech companies frequently deal extensively with cash inflows and outflows. Writing purchase orders by hand for a number of clients and sending them for approval is repetitive work that is also prone to error.

AI-powered RPA processing of the same will remove all chance of error and intelligently gather the data. Without requiring human participation, an automatic approval matrix may be generated and sent for approval once the automated system is in place. Among the most obvious advantages of RPA in finance and accounting for PO processing are its simplicity, effectiveness, speed, and cost-effectiveness.

Invoice Processing

Processing invoices is also laborious and repetitious, particularly if they are created or received in a variety of forms. Financial firms, being customer-focused, find it difficult to provide accurate bills in the forms requested by their clients on time.

Furthermore, there might be a lot of rework involved in rectifying the formats and data due to the approval matrix and procedure. Automation can quickly take up this time-consuming, repetitive activity, guarantee accuracy, and transmit the bills to the appropriate allowing authority.

In the financial sector, RPA and automated invoicing software allow for total automation of accounts payable and receivable. Since the system can match the bills with the appropriate POs, the maker and checker procedure may be almost eliminated.

Reconciliation of Accounts

Ensuring correct balance comparisons is a crucial business activity that can consume a considerable amount of time for the account team. A close watch is needed while making back-and-forth references and logging into various systems to make sure there were no mistakes and the data was compared correctly. 

An organization with several departments and subsidiary businesses maintains its accounts using various structures and procedures, which helps to better comprehend it. Depending on the demands of the customer and the business requirements, it might not be able to put them all into a uniform processing format. The central team has difficulties when it comes to balancing the books across all divisions and subsidiary businesses. The procedure is laborious, prone to mistakes, and repeated. 

This is where the central team may benefit from the use of RPA. In actuality, this is RPA for accounting’s main advantage. RPA bots speed up and standardize the work by checking and matching the data at every step of the way and needing little help from humans to add the necessary parts. Only when misalignments are reflected in the data is human intervention required?

Journey and Costs

The accounts team’s time is greatly consumed by raising trip requests, reviewing the expenditure category, obtaining necessary approval, obtaining necessary supporting documentation, etc., which might potentially cause a delay in the processing of the same. 

However since RPA was introduced into corporate finance, it has been quicker and easier to create expenditure reports and make sure that the data match the company’s regulations. Additionally, timely reimbursement administration is possible with a financial automation system. Automated alerts can also be used to notify the relevant departments and people of policy infractions and data anomalies.

Tax Estimates

Automating repetitive tasks such as building tax bases, producing reports, and compiling data for tax computations with RPA bots avoids errors and redundancies that may occur when doing the same manually. To prevent discrepancies in data processing and reconciliation, numbers and figures must be precise down to the decimal places. 

Even though the majority of businesses use tax processing software, there is still a significant amount of physical labor required. RPA bots can do the majority of this manual labor, saving time and money while improving accuracy and adhering to regulatory requirements.

Accounting Reporting

Daily record-keeping of company transactions, profit, and loss enables you to plan and detect problems before they become serious. You may avoid losses by controlling and resolving these problems proactively. The adjustments can be made to improve and rectify the current company procedures and methodologies.

Financial organizations, such as banks, are mandated to provide comprehensive reports that showcase their operations, data-driven trends, and statistical information. Manual data extraction will be time-consuming and inaccurate. However, data from many sources and in various formats may be gathered more easily thanks to robotic process automation in accounting and finance. Improved forecasting and planning result from the collection, reporting, and analysis of this data.

Forecasting and Planning of Budgets

Forecasting and budgeting are two of the finest uses of RPA in finance. The variance reports will be created by accurately extracting features from many reports and systems using RPA bots, offering a variety of perspectives for data viewing and analysis. Comparisons and trends that are based on current and historical data may be used to forecast and plan your business in an effective method.

KYC with RPA in Fintech

KYC is an essential and time-consuming procedure that every consumer in the BFSI business must go through. An Infosys analysis states that banks spend around $52 million annually on KYC compliance; for certain institutions, that amount rises to almost $384 million. Apart from the exorbitant expenses, compliance departments in the financial sector have expanded in magnitude, encompassing 150 to more than 1,000 full-time equivalents (FTEs) for compliance teams.

By automating the KYC process using RPA, finance may save time and money by reducing expensive mistakes. RPA will therefore aid in speeding up client onboarding and enhancing the general customer experience in fintech services related to KYC.

Payroll Management

Processing payroll is one of the most important tasks for every company. Efficient and precise handling fosters a more contented workforce, which in turn cultivates a loyal clientele and a prosperous business. 

Since financial institutions are present in many different parts of the world, it is time-consuming and laborious to record production, attendance, and tax laws according to each region. Such data collection and computation are error-prone processes that might make workers unhappy. 

RPA lets you breathe easier since it automates the entire process. Correct and timely computations make workers pleased. RPA bots can handle the laborious duties of validating timesheets, calculating deductions, calculating taxes, paying overtime, and so on with no mistakes or delays. Bots are also capable of doing work for hours in a couple of minutes without growing weary.

Examples of RPA in Fintech in the Real World

Due to its capacity to automate routine and repetitive processes, robotic process automation (RPA) has become incredibly popular in the Fintech industry. This has decreased human error and enhanced operational efficiency. For this reason, over the past several years, the BFSI sector has been seen to welcome RPA innovations with open arms. The following are some actual financial services RPA examples:

Keybank 

Keybank, one of the top commercial banks, adopted RPA early on to boost productivity in a very practical way. Account receivable has been automated; it no longer requires manual labor to generate POs and invoices in many processes. Even though the bank’s primary focus is usually on payments, the whole payment process is seamless and error-free thanks to the automation of accounts receivable.

Radius Financial Group

Obtaining a home loan requires a lot of documentation and proof. The mortgage agent takes too much time coordinating with the customer and the mortgage company to obtain the necessary papers. The entire procedure may be further delayed by a single error made by the client or a bank staff.

The complicated task of finding and confirming the facts from several data sources is taken on by RPA implementation, which cuts the processing time by 80%. Radius Financial Group effectively keeps up its business pace with RPA adoption. The business may continue to make money and be productive even during the pandemic.

Societe Generale Bank, Brazil

By using robotic process automation to speed up time-consuming, repetitive processes, Brazil’s Societe Generale Bank has led the financial services sector. Although the financial industry uses a vast and sophisticated amount of data, the personnel benefit from frequent automated reports generated by RPA bots, which enhance their knowledge and enable them to deliver exceptional customer support. The company model has undergone a substantial transformation due to the positive value contributed that improves the consumer experience.

Zurich Insurance

Due to its extensive global reach, Zurich Insurance faced the primary problem of adhering to geography-specific rules. They could distinguish between standard and generic policies and save a significant amount of time by implementing RPA. There could be enough time for the underwriters to go over more intricate processes. The result was unexpected because they were able to reduce processing costs and time by around 50%.

Leveraging AI and ML’s Potential to Automate the Financial Sector

Automation solutions can use AI and machine learning to interface with internal systems like CRM and ERP. This integration speeds up operations by analyzing data, automating customer answers, and working with other internal systems.

As a result, a more efficient and streamlined workforce can concentrate on improving customer service and the entire customer experience. AI and ML in robotic process automation can help FinTech companies run smoothly.

Being able to get detailed reports, spot trends, look at both old and new data, and give important insights, makes it easier for stakeholders to make smart decisions that are carried out more accurately.

RPA’s potential in the financial services industry is often increased when AI and ML are combined with it. This results in increased productivity, fewer mistakes, better client experiences, and data-driven decision-making.

The Advantages of RPA in Fintech

BBFSI companies must use AI, ML-enabled robotic process automation to overcome workflow bottlenecks, repetitive task issues, and human error. It will also reduce operational inefficiencies that cause poor customer service. In conclusion, robotic process automation has changed the following characteristics of financial institutions:

  • AI and Ml-enabled RPA can tell customers about new financial products and services, improving their experiences.
  • Businesses may analyze customer behavior using RPA bot data and reports, promoting sustainable growth.
  • RPA bots assist in getting real-time data analysis and increase the team’s operational efficiency by automating tedious and repetitive processes.
  • RPA in banking and finance will also lessen financial fraud and alert users to possible theft before it happens.
  • Finally, data compliance is guaranteed throughout the process thanks to robotic process automation in finance. 

Conclusion

Renowned for providing outstanding robotic process automation (RPA) solutions to the financial sector, Appic Softwares is one of the fastest-growing international Fintech App Development Company. With the support of an elite group of over a thousand technology specialists, we provide the finest RPA solutions available for the financial industry, capable of smoothly automating your Fintech company operations. Our staff is there for you every step of the way, from conception to implementation, and is committed to providing innovative solutions that go above and beyond your expectations.

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