They say that efficiency is doing better at what is already being done. And as the world advances and AI models (like ChatGPT) make their way into process automation, it’s time to revisit how enterprises automate—and do it better.
The global intelligent process automation market was valued at approximately USD 9.52 billion in 2021, and is expected to grow at a CAGR of 16.50% from 2022 to 2030. This is not surprising given IPA’s ability to streamline business processes, lower costs, and improve operational efficiency.
With the introduction of cutting-edge technologies such as the IoT, generative AI, big data, natural language processing (NLP), robotic process automation (RPA) and machine learning (ML), process automation has become a major competitive advantage. These rule-following applications work tirelessly to ensure consistency and compliance, while building up towards the ultimate goal: end-to-end business process improvement.
The advantage of process automation is that it can be used to elevate both new and existing automation frameworks. So, enterprises can gain the benefits irrespective of their automation maturity. But identifying what and how to automate can be challenging. Leaders must carefully audit their own processes and study successful examples of automation in the market to see what works.
In this regard, the BFSI sector has much to emulate. Among the earliest and most enthusiastic adopters, the BFSI sector’s pro-automation approach has generated a variety of use cases on business process automation. Here are a few from the sector and beyond:
Process automation can automate manual processes, improve decision-making accuracy, and speed, and reduce the risk of errors. One of the most common use cases is invoice processing, where process automation extracts data from invoices, verifies the information, and automates approval and payment processes. It can thus save time and resources while eliminating the risk of errors due to manual data entry.
In a particularly relevant example, Hewlett Packard Enterprise (HPE) used a combination of machine learning modules and optical character recognition to mitigate quality and formatting issues in scanned image invoices. Since the company dealt with a large number of paper invoices every month, this allowed for consistent text formats that accommodated multiple languages, which could then be processed accurately and effectively for streamlined procurement management.
With ML algorithms, process automation can detect fraudulent activities by analyzing huge quanta of data such as transaction history, customer behavior, and geographic location. Process automation can automate customer onboarding by extracting data from identity documents, verifying information, and creating customer profiles. Moreover, it can expedite the loan processing time by analyzing borrowers’ creditworthiness, generating loan agreements, and processing loan applications.
Several UK-based banks complete their daily payments through the use of The Clearing House Automated Payment System (CHAPS), which provides customers with same-day fund transfers—a much faster turnaround time when compared to manual requests. The banks do this through the use of RPA bots which check for fund availability, then perform the transfer and charging process in one seamless flow. The end result: higher efficiency and delighted customers.
Process automation can assist in risk management, compliance, and trading. It can analyze financial data and identify potential risks, such as market volatility and liquidity, and credit risks. Process automation can also automate compliance processes by analyzing regulatory requirements, monitoring transactions, and generating compliance reports, saving employees valuable time and resources. Process automation can also assist traders by analyzing market trends, identifying investment opportunities, and executing trades. It thus improves the accuracy and speed of decision-making.
While trade-allocation processes do possess a degree of process automation, a significant chunk of overall trade volumes are not entire automated. By combining RPA and ML technology, fintech provider Broadridge was able to handle trade allocation requests that were in the form of unstructured data formats. They achieved this by first placing the requests into a structured format and then identifying patterns using ML that leveraged historical data sets to achieve process automation and resolution on a larger scale.
Process automation can be used in the insurance industry for claims processing, underwriting, and customer service. It can analyze claims data, verify the information, and automate processes. It can also analyze customer data, such as demographic information, health history, and lifestyle. This facilitates risk profiling and automation of the underwriting process. Additionally, process automation can improve customer service by automating the customer inquiry process and generating personalized recommendations.
The potential for business process automation in digital insurance is limitless and poised to scale the sector upwards to new heights with unique use cases to leverage. These opportunities were highlighted at the Indian Insurance Summit and Awards 2023. Where we discussed how intelligent process automation can elevate the insurance industry to the next level of performance.
Map your automation journey
IPA has the potential to transform industries through business process automation, improved operational efficiency, reduced costs, and enhanced customer experiences throughout the value chain. While research indicates that by 2024, most organizations will lower their operational costs by 30% through a combination of hyper-automation solutions and redesigned operational processes, true change requires a growth mindset and a hunger for continuous improvement. Though intelligent process automation technology can improve any existing automation setup, enterprise leaders must understand and carefully execute the next steps.
Our Automation Accelerator Workshop is a comprehensive program designed to help you identify opportunities to streamline and automate your existing systems. With a focus on process discovery and optimization, NSEIT comes with a strong partnership ecosystem with the likes of Automation Anywhere, UiPath, Automation Edge, Soroco and also offer open source automation framework based on python. Sign up for this customized workshop to help you scale your automation programs.