For many companies, the biggest challenge with data is not acquiring it – some even have an abundance. The real obstacle lies in leveraging the available data to drive growth.

With limited human resources, processing huge amounts of data in different formats from various sources is a burden. But thanks to the advent of artificial intelligence and its machine learning algorithms, Intelligent Document Processing (IDP) is able to read and understand documents, helping humans take advantage of unstructured data.

New to IDP? Don’t worry, in this blog we walk you through 5 of the most frequently asked questions about IDP. Soon you will understand why this technology is gaining popularity cross-sector, and how it is helping companies streamline their business processes by leaps and bounds.

1. What is Intelligent Document Processing?

While data volume is growing exponentially and this data is becoming an increasingly valuable asset for businesses, 80% of it is still unstructured, locked in emails, PDFs, scanned documents, etc. This creates a bottleneck in data analysis and day-to-day operations. IDP is a solution that can be powerful in helping to solve this problem. IDP uses technologies including subsets of AI to analyse data, then turn unstructured and semi-structured data into a structured format that is machine-readable.

2. Which technologies are applied to develop IDP solutions?

IDP solutions are empowered by:

• Optical character recognition (OCR): An OCR engine can recognise and convert both handwritten and printed characters into a machine-readable, digital data format.
• Machine learning (ML): A technology that gives machines the ability to read, understand and derive meaning from human languages.
• Natural language processing (NLP): An application of AI that provides systems the ability to access data and use it to automatically learn and improve from experience without being explicitly programmed.
• Human in the loop (HITL): A framework in which humans intervene to create a continuous feedback loop, allowing the AI model to learn and constantly improve its accuracy.

3. 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, thus containing different types of information. Through this step, they are classified into groups so that the machine can better know which relevant information to be extracted.
• Extraction: This step involves OCR to recognise and convert 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, data goes through a series of predefined business rules for validation. Also, the HITL framework applied here can further validate the data and allow the model to continuously learn and improve its accuracy over time.

4. What are Intelligent Document Processing applications?

IDP adoption helps businesses streamline their business processes and improve operational efficiency. Many workplaces that have largely depended on humans to manually process huge amounts of paperwork are benefiting the most from IDP. Some of the most popular use cases of IDP include application digitisation, client onboarding and mortgage lending.

• Application digitisation: Because application forms that need processing contain a huge amount of data and are in several formats, many errors such as missing information, invalid input, etc. may occur. That 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, while 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 by accurately extracting and seamlessly integrating output data into existing systems.

5. Why is Intelligent Document Processing gaining popularity?

Since the data era has been shifting from creation to storage to readiness, organisations have moved their focus from how to collect data to how to actually leverage it. When 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 benefits of reducing risk, saving costs, boosting efficiency and ensuring compliance, IDP is increasingly attractive to managers across different industries.

You can take a look at Nexus Intelligent Document Processing while considering adopting an IDP solution to enhance your business processes, or check out our whitepaper The Impact of Intelligent Document Processing on the Data Value Chain if you are eager for exploring IDP’s full capabilities.