What is Intelligent Document Processing?

Intelligent Document Processing (IDP) is a software technology that enables organisations to automate the conversion of unstructured and semi-structured data into structured, usable information. IDP provides end-to-end automation to document-centric business processes. Intelligent Document Processing is a combination of several technologies: Optical Character Recognition (OCR), Machine Learning, Human In The Loop (HITL), and Natural Language Processing, along with other tools, are all used in combination to digitise, extract and analyse the data from various files.

IDP in layman terms…

Today, businesses have limited access to human resources. Consequently, processing huge amounts of data in different formats from various sources becomes a burden to their talent pool. Thankfully, with artificial intelligence and machine learning algorithms, Intelligent Document Processing (IDP) is able to read and understand documents, and as a result, help humans to take advantage of unstructured data and improve productivity.

Data volume is growing exponentially and this data is becoming an increasingly valuable asset for businesses, but 80% of it is still unstructured and locked in emails, PDFs, scanned documents, and so on. In other words, the available data creates a bottleneck in analysis and day-to-day operations. IDP is a solution that can be powerful in helping to solve this problem.

Intelligent Document Processing is a little bit like a good, old-fashioned secretary on steroids. It is a “robot” taking in a number of files at the same time. Then, it goes on to digitise them, organise the data, and prepare it for human analysis. It can decide if the files need additional approvals, and then send them to the right approver or just simply archive them.

Why Is Intelligent Document Processing Beneficial To Companies?

Traditional document processing by humans is tedious, time consuming and prone to error. By embracing IDP, companies will experience a number of benefits:
IDP frees up time for humans to work on value-added tasks, thus also increasing productivity.
Robots don’t tire out and make mistakes. This is why IDP gives greater accuracy.
Since it automates the classification of documents, they become easier to retrieve.
It speeds everything up! Manual entries are limited to a minimum and IDP can handle large volume in a short period of time.
A good IDP system is capable of automatically detecting sensitive information, offering enhanced compliance and security.

AI algorithms can extract keywords, phone numbers, names, customer sentiment, and more key insights that are important to businesses. It can structure it and put it back into your business’s internal system. With all this data now organised, business leaders can make better-informed decisions.

It seems like a no-brainer. If you are a company handling a large volume of documents manually, you should probably consider adopting Intelligent Document Processing.

Is it difficult to implement Intelligent Document Processing?

If you don’t plan for it properly, you might fail. KPMG published a report which found that the three main challenges in implementing IDP are i) not defining a clear strategy and actionable business goal; ii) failing to keep humans in the loop; and iii) misjudging the technological possibilities of IDP. Therefore, we recommend to start any new IDP project with a proper run down of needs and requirements. Companies can work with industry experts to analyse their current processing workflow, identifying the gaps and possibilities where IDP can bring the most value to.

How Does Intelligent Document Processing Work?

By applying types of AI powers, IDP solutions are able to process all types of complex documents, extract critical information, and integrate the output into existing processes. Most IDP solutions function through four thresholds:

Pre-processing

In order to facilitate the extraction when processing documents, this step enhances the quality of input documents by using techniques to rotate them to their proper orientation, correct distortions, reduce noise, etc.

Classification

Documents that need processing can be of different categories,containing different types of information. In this step, they are organised into groups, and as a result, the machine can better know which relevant information to be extracted.

Extraction

Optical Character Recognition (OCR) recognises and converts both handwritten and printed characters into a machine-readable, digital data format. ML is also applied to accurately extract specific data from the documents.

Post-processing

After being extracted, the data goes through a series of predefined business rules for validation. The HITL (Human In The Loop) framework applied here can further validate the data and allow the model to continuously learn and improve its accuracy over time.

Who Needs Intelligent Document Processing?

IDP helps to streamline business processes and improve operational efficiency. Workplaces that have largely depended on humans to manually process huge amounts of paperwork are benefiting the most from IDP. No matter how digitised a company is, there will always be unstructured documents. For instance, order trackings, records, purchase orders, statements, maintenance logs and claims -IDP is here to help!

Some of the most popular use cases of IDP include application digitisation, client onboarding and mortgage lending:

Application Digitisation

Application forms contain a huge amount of data in several formats. This leads to errors such as missing information, invalid input, etc. may occur. Processing this data is time-consuming and inconvenient for both regulatory officers and applicants. With IDP, regulators can spend their time handling anomalies and enhance decision-making capabilities. On the other side, applicants can submit required forms and have them processed seamlessly.

Client Onboarding

During client onboarding, officers have to work with unstructured data scattered to multiple sources. One mistake can lead to several consequences, namely heavy fines, customer dissatisfaction, reputational damage, etc. When adopted, IDP solutions can enhance customer experience and mitigate operational inefficiencies.

Mortgage Lending

Traditionally, officers have to manually drill into and investigate hundreds of data points on a daily basis for risk analysis. This iterative process is labour-intensive and time-consuming. IDP can help financial institutions free-up human resources to focus on complex issues. How? – By accurately extracting and seamlessly integrating output data into existing systems.

IDP Is A Necessity For Data-Driven Businesses

The data era has been shifting from creation to storage to readiness. Throughout, organisations have moved their focus from how to collect data to how to actually leverage it. They realise IDP remarkably helps process automation. By harvesting relevant data, gaining insights from it and making well-informed decisions, the technology becomes a necessity for data-driven businesses. With its multiple benefits, IDP is increasingly attractive to managers across industries.

How Nexus Frontier Can Help You Adapt To IDP

Nexus’s IDP solution takes both structured and unstructured data of various document formats and quality and uses a mixture of AI-powered technologies to capture, extract, validate and integrate this data. We process documents considered unreadable, even when they are folded, shadowed and skewed. The output is a set of precise, structured data which can then be used in various automated workflows. 

Nexus IDP has been extensively deployed in many cases, including bond prospectus analysis, contract management, life insurance claim processing, mortgage sales quality assurance, financial spreading as well as client onboarding or KYC. Get a free data assessment to accelerate your IDP adoption today!