In today’s fast-paced world, the finance sector is undergoing a profound transformation, driven by technological advancements. Among these, Intelligent automation (IA), Automation, and Robotic Process Automation (RPA) stand out as game-changers, revolutionizing how financial services operate. From improving efficiency to enhancing customer experience, the use cases of IA, Automation, and RPA in finance services are diverse and impactful.
Table of Contents
What Is Automation in the Finance Industry?
In the finance industry, manual data processing poses a significant risk of human error, leading to costly rework and potential financial losses. To combat this challenge, financial firms are turning to Robotic Process Automation (RPA) as a solution. RPA streamlines operations by automating repetitive tasks with speed and precision, reducing errors and saving costs.
A recent Gartner research shows that about 80% of financial firms have either implemented or are planning to implement robotic process automation in their business processes. The global RPA market is experiencing substantial growth, with projections indicating a Compound Annual Growth Rate (CAGR) of 39.9% from 2023 to 2030. This trend underscores the increasing importance of RPA in improving operational efficiency and driving innovation in the finance industry. As financial institutions continue to leverage RPA’s capabilities, they can expect to see further enhancements in productivity, accuracy, and cost savings, ultimately delivering greater value to their stakeholders.
Some Common Use Cases of RPA in Financial Service
The financial services require accuracy, resiliency, security, and quality, but in the era of quickly evolving technology and expectations, many are also looking to improve efficiency, customer experience, employee satisfaction, and connectivity.
We’ve mentioned the numerous benefits of RPA and IA in financial services. Now, let’s talk about how you can make that happen in more detail.
PO Processing
Fintech firms frequently manage significant cash transactions, including generating purchase orders for various clients. However, this repetitive task, along with seeking approvals manually, is not only tedious but also prone to errors.
Implementing RPA combined with AI can eradicate potential mistakes and intelligently capture data. Through this automated system, an approval matrix can be established and sent for approvals seamlessly, without the need for human involvement. The advantages of RPA in finance and accounting for purchase order processing are evident: simplicity, efficiency, speed, and cost-effectiveness.
Invoice Processing
Invoice processing can be arduous, especially with invoices arriving in various formats. Financial organizations strive to meet client needs promptly by issuing accurate invoices. However, the approval process often involves significant rework to correct formats and data.
Automation offers a solution by handling this repetitive task efficiently, ensuring accuracy, and swiftly forwarding invoices for approval. With automated invoicing software and RPA, accounts payables and receivables can be fully automated. The need for manual verification is minimized as machines can match invoices with relevant purchase orders, streamlining the process.
Accounts Reconciliation
Account reconciliation is a time-consuming process for finance teams, involving meticulous comparisons and navigating multiple systems. Each department or sub-company may have its own processes, complicating standardization efforts. This results in a tedious, error-prone task for the central team.
RPA implementation offers a solution by automating the reconciliation process. RPA bots audit and reconcile data efficiently, ensuring consistency and accuracy while reducing the need for human intervention. Human involvement is only necessary when discrepancies arise, streamlining the process for the central team.
Tax Calculations
Automating tasks such as collating data for tax calculations, creating tax basis, and generating reports using RPA bots minimizes repetitive task redundancies and inaccuracies inherent in manual processes. Precision is crucial, down to decimal places, to prevent discrepancies in reconciliation and data processing.
While many businesses utilize tax processing software, a considerable amount of manual work persists. Leveraging RPA bots can mitigate this manual effort, reducing time and costs while enhancing accuracy and compliance adherence.
Financial Reporting
Tracking daily business transactions and financial performance allows for proactive management, helping to anticipate and address issues before they escalate, thereby preventing losses. Implementing changes based on this information improves business methods and processes.
Banks and financial institutions must generate comprehensive reports reflecting performance, statistics, and trends, involving vast amounts of data. Manual extraction of this data is tedious and unreliable. However, robotic process automation in finance streamlines data gathering from various sources and formats, enabling efficient collation, reporting, and analysis for improved forecasting and planning.
Budget Planning & Forecasting
A key advantage of RPA in finance lies in its ability to streamline budget planning and forecasting processes. By accurately retrieving data from multiple reports and systems, RPA bots facilitate the creation of detailed variance reports, offering diverse perspectives for data analysis. Leveraging historical data and current information, comparisons and trends can be identified, providing effective insights for business forecasting and planning.
RPA in KYC
KYC (Know Your Customer) procedures are essential yet resource-intensive for the BFSI sector. According to a report by Infosys, a bank spends around $52 million every year on KYC compliance, and for some banks, the spending surges approx $384 million. Compliance teams have also expanded significantly, ranging from 150 to over 1,000 full-time employees.
Integrating RPA into finance streamlines KYC processes, cutting errors and resource expenditure. This automation not only accelerates customer onboarding but also enhances overall customer experience.
Payroll Processing
Payroll processing is crucial for businesses, impacting employee satisfaction and overall success. However, managing productivity, attendance, and tax regulations across multiple locations can be time-consuming and error-prone, potentially leading to employee dissatisfaction.
RPA offers a solution by automating the entire process, ensuring timely and accurate calculations. Tasks such as timesheet validations, deductions, tax calculations, and overtime payouts are efficiently handled by RPA bots, eliminating errors and delays. Additionally, RPA bots can perform tasks for extended periods without fatigue, boosting efficiency and employee satisfaction.
How has akaBot solution impacted financial services?
akaBot – the leading automation solution in Vietnam has become widely popular in the financial sector thanks to its ability to automate repetitive and boring tasks, helping to minimize human errors and increase operating efficiency. Some cases where akaBot has brought outstanding results to the financial services sector:
Automated Credit Approval Process For A Global Trading Company Using RPA & IDP
Challenges
- Dealing with an enormous amount of data in different formats, making the process of scanning and evaluating its customers’ performances a labor-intensive and time-consuming task.
- Striving to enhance customer experience and employee productivity
Solution: akaBot implements the steps following a systematic approach:
- Extract customer code
- Scan Financial statements/ Extract Financial information (IDP)
- Fill in Credit Application Form
- Send for Approval
Highlighted results
- Significant time and cost savings – Reduce processing time for credit approval by a whopping 88%.
- Optimize employee productivity by freeing up human efforts for higher value-adding tasks.
- Enhanced accuracy in data extracting and mapping, preventing costly errors.
A Leading Payment Service Provider Saved 30% of Effort With Hyperautomation
Challenges
- Delayed: due to a lack of workflow management and high dependency on human specialists’ timelines.
- Inefficient: unable to track or analyze for identifying bottlenecks.
- Reputationally damaged: as candidates receive no follow-up with their applications.
Solution: Hyperautomation was implemented in recruiting and payroll data validation processes
Highlighted results
- Up to 30% of Job Application processing effort reduced.
- 20% of end-to-end recruitment cycle time can be optimized.
- Optimized operations for empowering growth
Wrap up
The adoption of IA, Automation, and RPA is transforming the finance sector, driving operational efficiency, improving compliance, enhancing customer experience, and facilitating strategic decision-making. As technology continues to evolve, financial service providers must embrace innovation to stay ahead of the curve and meet the evolving needs of customers in the digital age. By harnessing the power of IA, Automation, and RPA, finance institutions can unlock new opportunities for growth, innovation, and value creation.
References
IA and RPA Use Cases in Banking & Financial Services
How to Use RPA in Finance? Use Cases and Real-World Examples
AI and RPA in Banking and Finance: Use Cases & Benefits 2024
