IDP Helps Banks Do More With Their Data—And Do It Faster

Traditional banks have lagged behind other industries when it comes to the adoption of digital strategies and automation, with 92% of the top 100 banks in the world still relying on legacy systems. 

However, banks are beginning to adapt their processes and adopt a more digital approach. The result is a significant increase in the amount of data streaming in.

Of the data banks have in their possession, 80% of it is unstructured. It comes in various formats, such as online forms, emails, scanned documents, and even selfies taken for identity verification. 

Being able to ensure all these formats are digitized and that the required information can be captured from them requires the use of Intelligent Document Processing (IDP) technology.

What Is IDP?

IDP is software that is programmed to be able to pull relevant information from documents based on context, rather than the position in which they are located on the document. This allows IDP to read information from forms, emails, and other documents in much the same way a human would.

Multiple documents can be read, and data pulled from them, in mere seconds, rather than the hours it would take a human to perform the same task. This data is then automatically uploaded to the bank’s information portals.

How IDP Works

IDP is software that is programmed to be able to pull relevant information from documents based on context, rather than the position in which they are located on the document. This allows IDP to read information from f

IDP uses artificial intelligence (AI) to detect unstructured data, capture it, and turn it into a usable format. In banking, examples of unstructured data sources include:

  •  A loan application form a customer filled out by hand
  •  A selfie a customer sent in to verify their identity
  •  Scanned verification documents
  •  Audio of conversations with a customer
  • Email conversations with a customer

With Machine Learning (ML), Optical Character Recognition (OCR), and Natural Language Processing (NLP), IDP can “read” over, capture and segregate relevant data from multiple formats and enter that data into the bank’s portals. This results in full data integration that has a wide range of uses in the banking industry.

IDP Banking Use Cases

There are many ways in which a bank can make use of IDP to capture and utilize data and keep processes running smoothly. Here are three use cases that show the power of IDP in banking.

Processing mortgage applications

The number of mortgage applications being filed has been on the rise in the U.S., Canada and the UK. This means banks and other lending institutions have had to scale their processes to keep up with demand.

This level of scaling is difficult to do when all the loan information must be manually captured and entered into the bank system. IDP can make this type of scaling easy to accomplish because it automates the collection and verification of information from all the various documentation submitted by the applicant.

This collected data is automatically inputted into the bank’s system. This can be done within a few minutes, leaving bank staff free to focus on customer communication and relationships and to deal with any red flags that come up.

Reducing fraudulent transactions

The number of digital fraud attempts in the banking industry worldwide increased by 149% from the end of 2020 to the beginning of 2021. The use of IDP can significantly reduce the number of fraudulent transactions because it can search through an immense amount of historical customer data quickly and accurately.

This allows the IDP to identify patterns in behavior, which makes it possible for it to determine in real-time whether a transaction represents the normal pattern of behavior for a customer. This makes it possible to stop a suspicious transaction from going through and flag it for investigation.

Enhanced risk-profiling

Know Your Customer/Client (KYC) is part of the Anti-Money Laundering policy of a bank. KYC involves performing a thorough check of every customer whenever they open an account and on occasions when they make transactions. The goal of KYC is to be certain the customer is who they claim to be.

KYC involves acquiring two forms of official ID, along with other documentation. These are used to verify a customer’s identity and address. Going through this documentation manually takes time and is also prone to error. It can be easy to mis-verify the documentation presented.

IDP can read the documentation submitted and scour the internet for sources that can confirm the identity of the customer. It can then create a risk score for that customer, helping the bank meet their KYC obligations.

Implementing IDP

The implementation of IDP requires banks to:

  • Determine what types of unstructured data they have and the sources of that data
  • Capture and consolidate that data in digital format
  • Integrate the digital data from all bank systems to make it easy to view all structured and unstructured data in one location

Embrace IDP and Transform Your Data and Information Management

Ampliforce is a global automation leader, powered by an experienced team of automation experts. We can help you determine your data and information management needs and develop an IDP solution that is tailored to your unique situation.

Book a discovery call today and find out how to get started on your IDP journey.