How AI is Revolutionizing Document-Intensive Processes in the Finance Industry

Documentation in Finance

Financial Services is one of the most data-intensive industries in the world. Vast amounts of information is transferred every day to fulfil transactions from invoices to financial reports and regulatory filings. Manually processing this unstructured, untagged or unorganised data is time-consuming and prone to human error, leading to operational inefficiencies and in extreme cases, regulatory non-compliance. Mounting costs, reduced productivity, and a higher risk of penalties are just a few of the factors driving digital transformation in the industry.

The advent of AI automation has provided faster, more effective ways of managing, processing, integrating and getting more value out of data. Enabling Financial Services organisations to deliver the best possible customer experience and internal efficiencies by freeing employees from mundane data entry tasks. Document automation may not be the most exciting application of AI, but its impact on business operations and growth eclipses that of almost any other productivity software in the market today.

What is Intelligent Document Processing?

Intelligent Document Processing (IDP) leverages artificial intelligence to replicate human capabilities in identifying, contextualizing, and processing documents — regardless of the quality, layout, or file type. This includes the processing of structured data and unstructured data that comes from any document source including scanned images, PDFs, word processing files, and online forms.

To learn more about IDP, check out our recent blog: Intelligent Document Processing (IDP): The Ultimate Guide

The Value in Automating Routine Tasks

The effectiveness of AI in finance lies in the ability to automate the review and extraction of information, reducing the time and cost associated with manual processing while improving data entry accuracy and regulatory compliance.

Recent research by PwC found that even the most rudimentary AI-based extraction techniques can save businesses 30–40% of the hours typically spent on such processes. This time saving allows redistribution of human resources to more strategic, growth-oriented work, while reducing operational costs by up to 20%.

Even the most rudimentary AI-based extraction techniques can save businesses 30–40% of the hours typically spent on such processes.

Intelligent document automation also eliminates the possibility of data entry errors, which inevitably occurs in the transfer of information from PDFs or paper documents into a digital database. A single agent may process 1000’s of documents a day, and within a single function like invoice processing, there can be significant variation in the document layout, legibility and the format of information contained. In addition to the common mistakes made during data entry, misplacing these kinds of documents can lead to missed notifications, delayed responses, and the need for countless extra work hours to resolve the issue.

Beyond productivity and efficiency gains, Intelligent Document Processing presents an advancement in how organizations collect and make sense of data. Reduced turnaround times for document-related processes and automated updates within digital records provides real-time insight to the business. This is especially beneficial for large organizations, with multiple departments dealing with the same customer.

Let’s have a look at the top use cases for Intelligent Document Processing.

Top Use-Cases For Financial Services

1. Know Your Customer (KYC)

KYC processing typically involves data collection, data verification, risk assessment and monitoring. Usually, each of these tasks is done manually by dedicated teams. With IDP, this process can be automated at each step.

• Data Collection: IDP automates the extraction of customer data from documents such as passports, driving licenses, and other identity documents.
• Data Verification: IDP automatically matches customer data with external data sources, reducing the need for manual review while improving the speed and accuracy of the verification process.
• Improve risk assessment: IDP can provide more comprehensive and accurate data for assessing the customer’s risk profile. This can include data from social media, news articles, and other sources that provide insights into the customer’s background and behavior.
• Enhance ongoing monitoring: IDP can help organizations monitor customer activity in real-time, flagging suspicious activity for review and reducing the risk of fraudulent behavior going undetected.

2. Loan Application Processing

Processing loan applications can be a complex and time-consuming process. Verifying the applicant’s identity, assessing their creditworthiness, and ensuring compliance with regulatory requirements requires a lot of data entry and document review. This is where IDP comes into the picture, automating these tasks with 99.5% accuracy — helping financial organizations make faster and more informed lending decisions.

Loan processing is subject to various regulations, such as Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations, which require financial institutions to verify the identity of borrowers and ensure that loans are not being used for illicit purposes. IDP can also automate these compliance processes, ensuring that all required checks are carried out.

3. Invoice Processing

Invoice processing is challenging because each document is different, and there’s no standardized way of dealing with them. Existing digital automation tools like Optical Character Recognition (OCR) underperform with this task because they can only process predefined document types and structures.

IDP solves this problem by using advanced technologies like AI and machine learning to extract data and relevant information regardless of how it’s presented. IDP can learn and adapt to new invoice formats and layouts, making the process of invoice processing more efficient and accurate.

4. Fraud Detection

With the increased digitization of financial transactions, the threat of fraudulent activity is ever more pervasive. IDP combats this by analyzing vast amounts of data to detect patterns and anomalies, such as any transactions that appear unusual in nature, size, or frequency. Based on the detected patterns, IDP can assign a fraud risk score to each transaction or customer, with higher scores indicating a greater likelihood of fraudulent activity. If a risk is identified, IDPs sophisticated system flags the activity as suspicious and alerts the relevant teams to investigate further. With IDPs real-time detection and response capabilities, businesses can be confident that they are taking proactive measures to safeguard against fraud.

In Summary

Intelligent document processing is a game-changer for the finance industry. It’s revolutionizing the way finance companies handle information, making data ingestion faster, more accurate, and more compliant. By automating data processing, finance companies can free up resources to focus on higher-value tasks, such as analysis and decision-making, ultimately leading to increased productivity and profitability. As the volume of information generated, and processed by finance companies continues to grow, business leaders will need to consider AI automation to provide a competitive customer offering and to maintain pace with competitor growth.

Visit our website to learn more or book a demo of our IDP solution supporting over 100 languages including regional dialects.