Although businesses across various industries have benefited from automation technologies such as robotic process automation (RPA), low-code platforms and chatbots, most are yet to explore the opportunity to automate their end-to-end business processes with powerful AI- and machine learning (ML)-powered tools. RPA, chatbots and low-code platforms are a great start to help cut manual costs, reduce process times and improve customer experience but as business processes get increasingly complex, these technologies fall short of reaping higher efficiencies. They can help you get small wins quickly but when you try increasing the level of automation you can achieve, you hit a wall because of their limitations. The reason these technologies can fall short when handling complex processes is that most businesses need these types of tools to handle unstructured data of some sort. A few examples include: https://hubs.ly/Q01lJJBw0

1. IDP: A Booster Shot for your
RPA, Chatbot and Low Code
Implementations
Although businesses across various industries have benefited from
automation technologies such as robotic process automation (RPA),
low-code platforms and chatbots, most are yet to explore the
opportunity to automate their end-to-end business processes with
powerful AI- and machine learning (ML)-powered tools.
RPA, chatbots and low-code platforms are a great start to help cut
manual costs, reduce process times and improve customer
experience but as business processes get increasingly complex, these
technologies fall short of reaping higher efficiencies. They can help

2. you get small wins quickly but when you try increasing the level of
automation you can achieve, you hit a wall because of their limitations.
The reason these technologies can fall short when handling complex
processes is because most businesses need these types of tools to
handle unstructured data of some sort. A few examples include:
• A customer uploads an expense receipt to its chatbot but it does not know
how to understand it;
• A customer sends an attachment of shipping instructions to an email account
that is being monitored by an RPA engine but it cannot figure out what is
being shipped where;
• You try to move your mortgage application process to a low-code platform
and get stuck on how to read data from the submitted W2 forms.
To solve these issues, manual processing will have to intervene in
order to make sense of the documents received by these automation
tools, and then feed them the data to complete the task. This means
your automation journey is only half way there.
To reap the full benefits of end-to-end automation, IDP platforms can
complement your existing investments in other automation
technologies and further broaden the range of functions that can be
automated.

3. Let’s look at how IDP integrates:
Chatbot + IDP
In the past few years, chatbots have been deployed by businesses
worldwide to answer questions, assist customers and reduce email or
phone interactions. Chatbots are designed to handle conversations in
short bursts and make sense of programmed sentences. Sometimes,
to resolve a customer’s query, the chatbot may ask the user to upload
a document.
If you have a chatbot handling your expense management process,
then you may need the user to take a picture of the expense receipt
and upload it to the chatbot. Since these documents do not follow a
fixed format, chatbots cannot easily extract information from these
receipts such as the nature of the expense, amount, date of
transaction and currency, etc.
An IDP receipt classification and extraction model can complement
the chatbot by extracting the receipt information and making it
available in a structured format. Once the chatbot has this information,
it can further manage the process, i.e., auto approve the expense if it
falls within the pre-approved limits, ask users to provide a justification
if the expense is likely to be rejected, or even request additional
supporting documentation.

4. Low-code platform + IDP
Low-code platforms are another set of automation tools that have
made it easy for businesses to create new solutions as needed. In the
past, enterprises spent months and millions of dollars working with
system integrators to develop tools for handling various business
processes. Some of these business processes can now be handled by
configuring process flows in these low-code platforms. Unlike before,
low-code platforms can do this in a few days or weeks, rather than
months. But as these flows get more complex, they too will need to
handle documents.
Let’s say you configure a low-code platform for the loan origination
process. You get users to enter the application information on forms
put together by the platform. As a part of the process, the loan
applicant is expected to upload proof of income and current assets. All
low-code platforms attach these documents and send them to the
underwriters where they then will need to open these documents and
manually extract this data which slows down the overall mortgage
approval time.
With a complementing IDP platform, you will be able to automate data
extraction from these uploaded documents and present it to the
underwriters in a ready-to-use format. In fact, the low-code platforms
will also be able to make some routing or approval decisions based on
the information present in these documents.
RPA + IDP
Out of all the automation technologies, RPA is most widely used and
deployed. With their orchestration and user simulation capabilities,

5. they can deliver quick efficiency by automating simple manual tasks.
At the core of RPA tools lies their process automation capabilities,
which vary and depend on unstructured data being converted to
structured format and delivered to them as CSV files.
Let’s use an insurance processing back office of a third party
administrator set up on RPA as an example. The RPA bot listens to an
email address for incoming messages for First Notice of Loss (FNOL)
documents. This document does not have a fixed format as every
business has its own layout and set of vocabulary to describe the
incident. As new claim notifications land in this account, the RPA bot
needs to understand the information present in these attachments. In
absence of this information, the only thing the RPA bot can do is grab
these documents and record the email of the sender along with the
date and time. Then it needs to wait for a human to manually read the
document and identify who this information is for and what type of
incident it was.
When RPA is integrated with an IDP platform, the RPA bot can send
this document for understanding and receive a CSV file with all the
relevant information. Based on this information, it can decide where to
route this document and make other business decisions.
Steps to integrate IDP with existing automation tools:
1. Identify data to extract: Before extracting data, the first step is to identify the
document type and required fields from which to extract. AI-led IDP solutions
use document classification models to recognize different document types,
based on OCR capabilities and proprietary machine learning algorithms.

6. 2. Configure and train the IDP solution: IDP solutions are flexible and can be
configured to intelligently capture data from specific fields in a structured
manner. This enables your RPA or bots that were previously struggling to infer
the unstructured data, to easily recognize and process the extracted
information. Once you configure the fields, you train the ML models to process
multiple document variations, and the IDP solution will improve its accuracy as
it becomes exposed to more variations.
3. Integrate with automation tools: Connect the IDP solution with primary
automation tools such as RPA or chatbot. This can be done using APIs. This
enables seamless connection and integration between the RPA and chatbot
tools while the IDP solution allows you to automate processes end-to-end.
4. Continuous feedback: AI- and ML-powered IDP solutions continuously learn
from corrections. When you extract data, IDP solutions assign a confidence
score to the extracted data. This is the solution's ability to know whether or not
the extracted data is accurate. Some of the data may be extracted with a low
confidence score and needs to be routed for manual corrections. IDP
solutions use various AI technologies and learn from each correction so that
automated accuracy is improved for the future extractions.

7. How can IDP boost your automation efficiency?
Intelligent Automation (IA) has two parts in its name - intelligence and
automation. Automation tools like RPA bots, low-code platforms, and
chatbots are the arms and legs of Intelligent Automation. They help
you take action. IDP is the intelligence part - involving understanding
of content by becoming a brain. IDP is the cognitive logic that will
make these arms and legs function better by sending them relevant
instructions as needed. Combining them can help you reap incredible
efficiencies from your automation investments. You can take your
automation journey to new heights and exponentially improve your
business processes by integrating the right IDP solution.