Intelligent Process Automation (IPA) enables the enterprise to automate workflows that depend on the analysis of unstructured content – documents, text, forms, emails, images, etc. – that drive critical business processes. For the first time, this unstructured content can be leveraged and analyzed with artificial intelligence, and Indico IPA software delivers this capability with 99.9% less training data than traditional machine-learning-based approaches and delivers ROI in just a matter of weeks.

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Intelligent Process Automation: Key Benefits

image shows that Indico's intelligent process automation can lead to an 85% reduction in process cycle time

85% Reduction

Process Cycle Time

image shows that indico's intelligent process automation can lead to a 4 times increase in process capacity

4x Increase

Process Capacity

image shows that indico's intelligent process automation can lead to an 80% reduction in the amount of total resources required

80% Reduction

Resources Required

Bringing Value to Stakeholders Throughout the Enterprise

Line of Business Executive

  • Bring AI to bear on practical business problems – with no AI expertise required
  • Automate workflows involving document review and analysis, substantially reducing long turn-around times.
  • Increase profitability by improving business efficiency, including those involving large teams
  • Enable subject matter experts to focus on higher value tasks
  • Automate responses to customer emails

Process Professionals

  • Enable automated, scalable human-like decisioning
  • Improve process accuracy and eliminate risk by removing potential for human error
  • Streamline workflows to drive process efficiency and lower the cost of operations
  • Increase process workflow capacity by up to 4x
  • Create summaries of unstructured data

AI & IA Professionals

  • No hype – real AI driving real business outcomes
  • Explainable AI – understand why and how your AI makes its decisions
  • Complete data security – your data is yours, always
  • No expensive compute power needed – deploys on a single GPU
  • Process data coming from electronic databases, Excel spreadsheets, "know your customer" data and more

Intelligent Process Automation Explained

unstructured content processes including PDF, excel and other documents, flowing

Enabling the enterprise to automate unstructured content processes

Indico’s Intelligent Process Automation (IPA) enables organizations to automate processes that involve unstructured content, including text and images. It does so without requiring rule-based decision-making or huge training data sets that are out of reach for 95% of enterprises.

Indico’s approach builds on the artificial intelligence concept of transfer learning, where a model trained on one task is used for another, related task.

Transfer learning addresses one of the key challenges in any AI solution: the time required to learn exceptions. An IPA solution would normally have to understand thousands of use cases before it could be used in production to automate an actual process. Transfer learning changes that equation.

Indico created a base model consisting of more than 500 million labeled data points, enough to enable the model to understand human language and context. Applying transfer learning enables users to then create custom models for downstream tasks using a fraction of the data normally required – 100x to 1000x less as compared to traditional approaches.

Rather than training the model on hundreds of thousands of examples, Indico’s workflow automation tool enables you to start with its base model and train on just 50 or so examples of the process you want to automate. In just an hour or so, you’ll have a complete workflow automation model.

Indico’s Intelligent Process Automation (IPA) enables organizations to automate processes that involve unstructured content, including text and images. It does so without requiring rule-based decision-making or huge training data sets that are out of reach for 95% of enterprises.

Indico’s approach builds on the artificial intelligence concept of transfer learning, where a model trained on one task is used for another, related task.

Transfer learning addresses one of the key challenges in any AI solution: the time required to learn exceptions. An IPA solution would normally have to understand thousands of use cases before it could be used in production to automate an actual process. Transfer learning changes that equation.

Indico created a base model consisting of more than 500 million labeled data points, enough to enable the model to understand human language and context. Applying transfer learning enables users to then create custom models for downstream tasks using a fraction of the data normally required – 100x to 1000x less as compared to traditional approaches.

Rather than training the model on hundreds of thousands of examples, Indico’s workflow automation tool enables you to start with its base model and train on just 50 or so examples of the process you want to automate. In just an hour or so, you’ll have a complete workflow automation model.

Intelligent Process Automation is built for document-to enable workflow automation for common document-based processes in enterprise business, including contract analysis, customer on-boarding, commercial underwriting, financial document analysis, mortgage processing, billing form reviews, insurance claims analysis and much more. With its cognitive intelligence capabilities, IPA can understand the text, images, documents and other unstructured data that are fundamental to so many business processes – and make accurate judgments based on surrounding context.

In short, Intelligent Process Automation enables the enterprise to overcome many of the common barriers to adopting artificial intelligence solutions:

Huge data sets

Up to 1000x less data required

Massive computing power

IPA needs only a single GPU

Data science expertise

Purpose built for business use

knowledge workers automating manual document-based workflows

Built for Business People to Address Business Issues

Automate complex business processes without data science expertise

The process through which companies use Intelligent Process Automation to build data models is simple and highly effective. Business subject matter experts label the data points they deem most important to whatever process they’re looking to automate. As they apply labels, the model is updated on the fly and will start to show predictions on subsequent datasets. Once you’re comfortable with the predicted results, you’re done building your model.

The beauty of this approach is that the people who understand the business problem and the desired results – those on the business side of the house – are the ones who train the model. There’s no need to try to explain to a data scientist what you’re after and then hope you get the appropriate results.

And it’s not a complex process. Everything is in plain English and you can have a fully working model in an hour. Intelligent Process Automation is just that simple.

The process through which companies use Intelligent Process Automation to build data models is simple and highly effective. Business subject matter experts label the data points they deem most important to whatever process they’re looking to automate. As they apply labels, the model is updated on the fly and will start to show predictions on subsequent datasets. Once you’re comfortable with the predicted results, you’re done building your model.

The beauty of this approach is that the people who understand the business problem and the desired results – those on the business side of the house – are the ones who train the model. There’s no need to try to explain to a data scientist what you’re after and then hope you get the appropriate results.

And it’s not a complex process. Everything is in plain English and you can have a fully working model in an hour. Intelligent Process Automation is just that simple.

Intelligent Process Automation: Sample Use Cases

How IPA is being used in Insurance, Banking & Financial Services

image shows that indico's intelligent process automation is a strong fit for insurance company use cases

Insurance

Claims analysis

IPA can be used to automate the classification and annotation of a new claim, and route it to the appropriate SME for evaluation and processing. The result is faster turnaround time and improved accuracy in claims processing, which drives improved customer satisfaction and organizational efficiency.

Commercial underwriting

Major commercial underwriting processes often involve thousands of pages of documentation. Insurance workflow automation can dramatically improve the process by creating underwriting criteria that IPA solutions automatically recognize, enabling them to quickly come up with a “score” for each potential customer. The result is a major reduction in response times to customers as well as improved accuracy, satisfaction, organizational efficiency and profit.

image shows that indico's intelligent process automation is a strong fit for banking and finance use cases

Banking

Customer onboarding

IPA can be used to automatically classify and extract relevant unstructured data from customer onboarding documents into the bank’s digital management system. This results in improved accuracy and speed for onboarding a new customer, driving improved customer satisfaction and faster time to revenue for the bank.

Loan underwriting

Banks with detailed processes for appraising and approving mortgages, including data extraction and image recognition, can use intelligent automation tools to automate the process of extracting relevant unstructured data from onboarding documents, as well as to analyze images. IPA can be used to bring workflow automation to the mortgage approval process, allowing it to become far more efficient and consistent.

image shows that indico's intelligent process automation is a strong fit for investment management firms

Investment ManAGEment

Financial document analysis

Investment firms can use IPA to analyze the financial health of companies before deciding whether to invest in them. Instead of poring over thousands of financial statements and manually extracting relevant data from each of them, IPA enables financial firms to automate the process, pulling out relevant data and normalizing it for insertion into data processing tools. The result is a dramatic improvement in speed and efficiency.

Trade processing automation

Investment firms receiving trade processing documentation via email and PDF formats can use artificial intelligence automation tools to extract relevant unstructured data from these trade documents and compile it into a normalized format that can then be integrated with the firm’s digital management system. IPA enables companies to eliminate untold hours of manual data processing. Other industries where IPA is being applied include legal services and marketing (CRM).

CASE STUDY: CHATHAM FINANCIAL

Chatham Financial, an interest rate and foreign exchange risk management advisory company headquartered in Pennsylvania, illustrates the value of Intelligent Process Automation. As of 2017-2018, it had an annual revenue of $11.4 million and an employee count of 105. Chatham Financial's clients include banking, real estate, pension funds, NBFCs and insurance firms.

Problem:

The company works with a variety of clients across industries, including banking, real estate, insurance and pension funds, and deals with thousands of documents pertaining to loan negotiation and derivatives structuring. It required many employees to process these sometimes complex documents. Chatham Financial tried automating part of its document processing operations through scripting technology, with only limited success. It wanted a more intelligent automation solution capable of: Processing a wide variety of documents; Learning across templates covering different processes, with minimal training; Achieving processing scale with increased variety, without adding extra employees.

Solution:

Indico’s AI-based intelligent automation solution, Intelligent Process Automation (IPA), can be implemented either on-premises or in the cloud. Because some Chatham executives were concerned about making their proprietary models and training templates available to the cloud, Indico recommended its IPA solution be integrated into Chatham's technology architecture as an on-premise installation. Chatham tested the solution multiple times across hundreds of documents in multiple fields. Following the successful tests, Chatham's internal team and system integrators implemented the solution in a phased manner.

Impact:

In the first phase, Chatham Financial employed Indico's IPA in document processing involving interest rate cap transactions, which has led to cost savings. In the second stage, Chatham plans to automate the second layer of checking and redeploy FTEs to other tasks.

Benefits of Intelligent Process Automation

Driving efficiency gains for the enterprise

It's easy to see how intelligent automation technology saves time and money. From our experience, here’s what you can expect from the effective use of IPA solutions:

85% reduction in process cycle times

Drive customer satisfaction and quicker time to market for new initiatives

4x increase in process capacity

Scale critical processes without increasing expenses, for more cost-efficient back office functions

80% reduction in human resources

Free up critical resources to work on higher value-add projects rather than repetitive low-value tasks

Ease of use

No data science expertise required

1000x less training data required

As compared to traditional artificial intelligence solutions

Built for unstructured content

Works with text, documents and images to automate almost any business process

The Third Wave of Automation

How IPA differs from BPM and RPA

Intelligent process automation builds upon existing technologies that also sought to streamline business processes, namely business process management (BPM) and robotic process automation (RPA).

Business Process Management

BPM is focused on improving an existing business process. That often involves automating some steps in the process, although that’s not necessarily a requirement. It’s more about optimizing a process to make it more effective and efficient, often by using methodologies such as Six Sigma and Lean.

Robotic Process Automation

As its name implies, RPA does involve process automation and works well with repetitive, deterministic business processes involving structured data – where there is no judgment involved. Tell it exactly what you need it to do and RPA can do it better, faster and cheaper than a human.

If a task comes along that deviates from the pre-defined task, RPA will not be able to automate it. It cannot make judgments about information or learn and improve with experience. In that sense, RPA is different from machine learning, and IPA.

For the same reason, RPA is ineffective with workflows involving unstructured content – those that require some level of cognitive ability. And this type of data makes up over 80% of the data in most enterprises today.

Because of IPA’s cognitive ability, it is very well-suited to work with business processes involving unstructured content and data – all the text, documents, and images that drive many enterprise business processes today.

IPA does not replace or compete with RPA. It complements it, handling the unstructured content, with the output being structured content that can be re-inserted back into a business process that RPA can then address.

The combination of IPA and RPA enables the enterprise to realize true digital transformation.

 

Intelligent process automation builds upon existing technologies that also sought to streamline business processes, namely business process management (BPM) and robotic process automation (RPA).

Business Process Management

BPM is focused on improving an existing business process. That often involves automating some steps in the process, although that’s not necessarily a requirement. It’s more about optimizing a process to make it more effective and efficient, often by using methodologies such as Six Sigma and Lean.

Robotic Process Automation

As its name implies, RPA does involve process automation and works well with repetitive, deterministic business processes involving structured data – where there is no judgment involved. Tell it exactly what you need it to do and RPA can do it better, faster and cheaper than a human.

If a task comes along that deviates from the pre-defined task, RPA will not be able to automate it. It cannot make judgments about information or learn and improve with experience. In that sense, RPA is different from machine learning, and IPA.

For the same reason, RPA is ineffective with workflows involving unstructured content – those that require some level of cognitive ability. And this type of data makes up over 80% of the data in most enterprises today.

Because of IPA’s cognitive ability, it is very well-suited to work with business processes involving unstructured content and data – all the text, documents, and images that drive many enterprise business processes today.

IPA does not replace or compete with RPA. It complements it, handling the unstructured content, with the output being structured content that can be re-inserted back into a business process that RPA can then address.

The combination of IPA and RPA enables the enterprise to realize true digital transformation.

 

Download our Intelligent Process Automation best practice guide

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