Organizations across the globe are working towards becoming more lean and agile in their organisational structure. Cost and process efficiency is driving this change and therefore it has become the need of the hour to adopt various business automation processes in an organization. One such process is Straight Through Processing.
Straight Through Processing (STP) is a process that firms use to reduce the processing time for documents. STP is an end-to-end document automation process that allows firms to streamline and digitize documents efficiently. Organisations are spending millions to improve the document process rates and STP plays a vital role in it.
The role of STP is even more critical for organizations that have a complex process in sectors like telecom, manufacturing, banking and insurance, equity markets and so on. STP has proven to provide an accuracy of 70% on average across different industries.
But let us take a deeper look at what exactly RPA means and how does it help Straight Through Processing become more efficient.
Robotic Process Automation is the culmination use of artificial intelligence and machine learning. Tasks that are repeatable in nature, have quite a high volume of transactions and are mundane activities for humans to perform.
One of the most common misunderstandings about automation is that we keep equating it with RPA. This is not true as traditional automation and RPA are different in nature.
Source : hwinfotech.com
Traditional automation has Application Programming Interfaces (APIs) and tools to integrate with various systems. An RPA developer must have a very thorough understanding of the system.
RPA, on the other hand, mirrors the actions of a user at a User Interface (UI) level. The developer does not need to worry about the complex nature of RPA as long as the bots follow steps in the chronological order that are designed to take.
Importance of RPA in Straight Through Processing
Robotic Process Automation (RPA) also plays a crucial role in Straight Through Processing. With the help of artificial intelligence and machine learning, RPA can help firms to enhance document processing time. Tasks such as transactions, record maintenance, addressing queries, can all be actioned through RPA.
Here is a three-step process that explains how exactly RPA helps to improve Straight through processing:
Step 1: Smart Root Cause Analysis
The very first step to tackle any issue is to identify the root cause of the issue. Investigation of possible causes for inaccuracy or documents falling out of the process is critical at this stage to improve Straight through processing. By extracting various transactional logs, the bots can identify where and why the fallouts are happening.
This process can be carried out by data mining tools. The analysis emphasises the identification of not just the place and reason of fallouts, but also, digs deep into the detail of each document’s fallout. This process is termed can be also termed as RCA.
Step 2: Fallout Automation
Once it is identified where the documents are falling out from the process, it becomes crucial to implement a much more intelligent way to reduce such fallouts. There are many reasons why fallouts may occur. Here we will discuss two such scenarios in detail.
Example 1: Invalid Inputs
Service providers cannot utilize the bot to its fullest potential unless they move on from one transaction to another. Each RPA bot has a unique license. So if in the automation process details in the field are missing, interactive bots can be used to enhance collaboration between the human resource and the technology. STP rate is improved by converting attended fallouts to unattended ones.
With the help of minimal human effort, an interactive bot solution can be adopted by the service provider to create a “no-code” RPA solution. This is a dynamic web form that operates in real-time. Apart from that, it can categorize the unattended fields into suspended ones and then the process can resume without the immediate attention of a human resource. It will pass on to the next stage using any available bot and complete the process.
Expample 2: Poor Images or Handwritten Text
Traditional Optical Character Recognition (OCR) has many challenges when it comes to extracting data from a handwritten and printed text that has different languages and is in different sizes. STP rate drastically goes down as most of these transactions end up being done manually due to high fallout rates. The solution to this issue is by adopting Computer Vision, which can enable automation for processing documents that have a poor resolution or are handwritten.
Step 3: Monitoring Straight Through Processing Rate
With the above two steps, your organisation will achieve the desired Straight Through Processing rate. However, tracking and monitoring the STP rate is as important as achieving it. Continuous tracking can help you make aware of the fallout rates, why it is happening and reduce it. Validation of milestones can be achieved through continuous monitoring. If the fallout percentage exceeds a certain limit, an automation alert notification can be generated and get the immediate attention of the personnel.
Making Document Automation Efficient with KlearStack AI
The full potential of STP can be achieved by collaborating automation business processes with platforms and people. KlearStack AI is a state-of-the-art document automation platform that can help minimize human effort and maximize operational efficiency for your organization and process documents seamlessly. Straight Through Processing adds a level of maturity to the entire process and therefore, end-to-end automation is achieved. If you are looking forward to digitizing your documents or are curious to learn more about KlearStack AI, click here to connect with us.