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Using AI and Machine Learning to Automate the Processing of Unstructured Data: A Strategic Guide

Unlocking the Value in Your Unstructured Data

How the Indico Unstructured Data Platform delivers new corporate insights from your troves of unstructured data.


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Industry experts estimate 85% of all data residing in an organization is unstructured, and they expect unstructured data to grow by over 100% in the next few years. All this unstructured data contains valuable insights, but only if you can unlock it. To date, companies are falling short of that unstructured data analytics goal, as only about 2% of it is being used in a meaningful way.

Indico Data can change that dynamic. Our Unstructured Data Platform turns unstructured data into structured data, enabling companies to:

  • Automate document-intensive processes involving unstructured data
  • Analyze unstructured data to glean actionable intelligence
  • Apply unstructured data to mission critical enterprise workflows

What you’ll find in this guide:

  1. Unstructured Data Challenges
  2. Unstructured data vs. structured and semi-structured data
  3. Unstructured Data Use Cases
  4. RPA & Unstructured Data



Download the eBook: The Unstructured Data Imperative. Why Enterprises need to act now.

View eBook Now

Document Variation

makes rule-based workflows and robotic process automation impractical

Intelligent Automation

is needed to understand data context

Unstructured Data Fast Facts

85% of data

in the enterprise is unstructured.

Less than 2%

is leveraged by unstructured data analytics tools

80% reduction

in resources required with AI

Understanding the different data types:

As its name implies, structured data is highly organized, typically in a database or spreadsheet with rows and columns. As a result, each piece of data is mapped to a specific fixed field or location.

Unstructured data comes in many forms, including Word documents, PDFs, emails, images, and videos. In essence, any data that is not in a highly structured format, such as a spreadsheet or database, is unstructured.

Semi-structured data falls somewhere between the two extremes. Consider an email. While the text of the email is wholly unstructured, the header contains structured elements, such as the “to” and “from” fields, date, and time. As a whole then, an email message could be considered semi-structured data. The same goes for digital photos. While the image itself is unstructured, the digital file typically contains structured elements such as date, time, and location.

If you think about the data in your organization, it’s easy to see most of it is unstructured, along with some semi-structured. Contracts, email strings, lease agreements, rent rolls, insurance policies and claims, photographs, PowerPoint presentations, financial statements, mortgage documents, invoices, purchase orders – they’re all examples of unstructured or, at best, semi-structured data.

Why unstructured data is valuable:

All this data is valuable because it holds years’ worth of corporate intelligence. Unlocking this data by transforming it into a structured format and feeding it to an analytics engine is game-changing. Unstructured data analytics makes possible numerous use cases that enable you to extract value from all of your data, including:

Examining news feeds to generate market intelligence, enabling you to react more quickly to opportunities

Analyzing unstructured call center recordings and transcripts to better understand brand loyalty and generate customer sentiment analysis

Applying unstructured data analysis to financial records, emails and more to identify fraud, compliance, and legal risks

Automating data-centric processes to improve efficiency as well as quality

Extracting and analyzing data from insurance claims to inform new, more profitable underwriting models

MetLife is a prime example of an intelligent automation in insurance use case. The company has documents dating back more than 100 years. The Indico Unstructured Data Platform enables MetLife to analyze unstructured data by extracting it from unstructured documents and turning it into a structured format. At that point, the company can apply analytics, such as to better predict mortality and morbidity, says Sean Nicolello, Vice President of Intelligent Automation at MetLife.

“A small adjustment to our actuarial models can result in billions of dollars of savings and revenue generation over the next 5 to 15 years,” he says.

Deal Management

Automate the process of abstracting commercial lease details into deal management systems, reducing the 6-hour process by 60% or more while improving confidence scores.


CAM Reconciliation

Automate compilation of common area maintenance (CAM) allocation rules, coding and keying invoices, and other manual gaps left by MRI, YARDI, and other property management software.

Rent Rolls

Extracting data from rent rolls and converting to a structured format enables you to feed it to an analytics tool to gain insights into cash flow, turnover rates, vacancies, and opportunities as well as speed due diligence checks.

Mortgage Processing

Speed the review of reports on credit worthiness, apply analytics to help make more informed underwriting decisions, and automatically generate all the documents needed for closing. Indico Data can help slash mortgage processing time by 85%.

10Ks, supplemental material, & ESG reports

Various financial analysts, from equities to hedge funds, each need different information from 10Ks, 10Qs and other financial documents. It’s a painstaking process to manually pore through them to find and extract the data they need. With Indico Data, these specialists can reduce that search time, giving them far more time to spend on actual analysis.

ISDA Master Agreements

ISDA Master Agreements, which spell out the terms between two parties regarding over-the-counter (OTC) derivatives transactions, are notoriously complex and lengthy. The latest version, from 2002, is 28 pages long. Yet, it’s common that multiple subject matter experts (SMEs) must examine the documents and confirm terms are correct before executing a trade. Indico Data automates the process, dramatically reducing ISDA Master Agreement processing times.

Anti-money Laundering

Automate the verification and processing of client documents and monitoring of negative information. Indico Data machine learning models can help identify the warning signs of a money laundering risk by comparing to baseline data. You can also extract key data from various documents and feed them to an analytics engine that can identify suspicious activity.

LIBOR Transition

The phasing out of the LIBOR interest rate benchmark has financial services companies scrambling to find contracts and loans that reference the rate. With Indico Data, you can quickly find all the documents that contain LIBOR references, extract pertinent data, and enter it into another downstream tool. Now in one place you’ll have all the loans that may be affected by the LIBOR expiration.

Commercial Underwriting

Reduce turnaround times by automating the processing of the potentially thousands of pages involved in commercial underwriting processes. Apply analytics to assess risk more accurately while giving underwriters more time to focus on analysis and adjusting models.

Loss Run Reports

Get an accurate picture of an applicant’s loss history by automating the processing of loss run reports. Regardless of format, Indico Data can help you summarize loss run reports to speed up underwriting and empower underwriters.


The Indico Unstructured Data Platform can automatically classify and annotate a new claim and route it to the most appropriate SME for evaluation and processing. This results in faster turnaround time and improved accuracy for a processed claim, driving improved customer satisfaction and organizational efficiency.

First Notice of Loss

Save 85% or more on processing of first notice of loss (FNOL) documents, including emails, webforms, ACORD forms, faxes, letters, and images.

Appraisal Processes

Automate processes involving unstructured documents from receipts, purchase and sale agreements, images, and contractor estimates. Reduce processing time by up to 85%.

Regulatory compliance

Extract relevant data from insurance documents and feed it to an analytics engine to identify any areas where you may be running afoul of regulatory requirements. Indico Data can also help index content to simplify and speed responses to regulatory bodies.

Customer Onboarding

Streamline the onboarding process with intelligent document processing, automating the processing of potentially millions of documents each year.

Invoice & Purchase Order Processing

Large companies deal with invoices from many different companies, perhaps hundreds of them, which effectively makes invoices an unstructured data use case. Indico Data provides a template-less way to automate processing of invoices and purchase orders, after labeling just a few dozen documents.

Customer Contract Processing

With Indico Data, you can automate the keying of customer data, payment terms, SLAs and more into CRM, ERP, and deal management systems. Feed the same data to an analytics tool and now you can gain valuable insights that can inform the terms of future contracts.

Corporate Inbox Automation/Digital Mailroom

“Read” incoming emails, discern subject or topic, then route it to an appropriate subject matter expert. Automate responses to routine questions such as change of address or quotes for interest rates. Apply analytics to gauge customer satisfaction and sentiment.

Learn how to unlock
your unstructured data

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Unlock the power of unstructured enterprise data

Unlocking the value in unstructured data requires an unstructured data solution that can ingest unstructured data, regardless of format, extract valuable data, and translate it to a structured format. Now the data can be used for automation, analytics and be applied to enterprise workflows.

That’s exactly what the Indico Unstructured Data platform does. The platform is built on a database of some 500 million labeled data points, enabling it to understand the context behind virtually any kind of content. By taking advantage of artificial intelligence technologies including machine learning, transfer learning, and natural language processing, the platform can read and understand unstructured data just as your employees would. It can also glean data from images – even videos.

Our solution makes it easy for your employees to label documents to identify what sorts of data to extract. Importantly, it’s the employees on the front lines who label the documents, those who know the business requirements best. No IT or data scientists are required.

After labeling about 200 documents, the Indico Data platform builds a model that automates the extraction of relevant data from your unstructured documents. It then translates the data to a structured format, typically JSON or .csv.

At this point, you’re ready to use the data in various ways, including to automate processes, feed it to data analytics tools and apply it to other workflows.

Automate processes involving unstructured data

Many processes in large companies involve documents – lots of documents. To date, companies have had some success automating processing of structured documents using templated approaches that involve robotic process automation (RPA) and optical character recognition (OCR). But such tools hit a wall when it comes to unstructured data processing. They’re simply not intended to handle the variation inherent in unstructured documents.

The Indico Data platform offers a solution because it can read and understand unstructured documents. By automating document processing, customers find they can increase process capacity by 4x while reducing process cycle times by 85%. (Visit our Intelligent Process Automation page to learn more.)

Finally, an unstructured data analytics solution

On their own, traditional business intelligence tools are incompatible with unstructured data. So, while the industry is filled with solutions for exploring and visualizing structured records, treasure troves of unstructured data sit gathering dust in data lakes.

Indico Data enables business intelligence tools to visualize and analyze unstructured data. Once the Indico Data platform converts your unstructured data to a structured format, you can now feed it to tools such as Microsoft Power BI, Tableau and Google’s Looker to perform analytics and uncover actionable insights.

Indico Data essentially turns those platforms into unstructured data analytics tools, enabling them to process unstructured data. Now you can unlock the insights trapped in your collection of enterprise documents, raising the potential for new – and potentially lucrative – business opportunities.

Are business intelligence tools compatible with unstructured data?

Customers also often ask about whether business intelligence (BI) tools can analyze or visualize unstructured data. Here again, the answer is no, for much the same reason as with RPA.

BI analytics and visualization tools require data to be in a structured format, typically JSON, .csv or a proprietary format, before they can process it. There really is no such thing as an unstructured BI or data analytics tool.

By using the Indico Unstructured Data Platform, however, you can convert unstructured data into a structured format that your BI or analytics tool will be able to handle. That’s how you unlock the power of your unstructured enterprise data.



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