Category: Blog

Advanced AI Powered OCR

How AI-Powered OCR is Slashing Operational Costs in Banking?

In today’s banking world, there’s no room for inefficiency. With rising competition, customer expectations, and compliance demands, banks need to find ways to do more with less. The traditional paper-heavy workflows that banks have relied on for decades are now a thing of the past. Enter AI-powered OCR (Optical Character Recognition) — a cutting-edge technology that’s revolutionizing document processing and dramatically cutting operational costs. At the forefront of this transformation is AOTM’s Advanced AI-powered OCR, which is enabling banks to streamline operations, reduce human errors, and speed up document-heavy tasks, all while cutting costs. In this blog, we’ll explore how AI-powered OCR, particularly AOTM’s advanced solution, is driving efficiency and transforming the banking industry. The Document Dilemma in Banking From loan applications and KYC forms to bank statements and checks, banks are drowning in documents. Traditionally, this mountain of paperwork required extensive manual effort for data entry, verification, and compliance. But these manual processes come with problems: It’s slow: Customers waiting days for approvals or account openings isn’t ideal. It’s expensive: Paying large teams to handle manual data entry adds to operational expenses. It’s prone to errors: Manual entry introduces mistakes that can lead to financial loss or compliance issues. This is where AOTM’s Advanced AI OCR steps in, automating document processing with unmatched accuracy and speed. What Makes AOTM’s Advanced AI OCR Different? Now, you might be wondering: what makes AOTM’s Advanced AI OCR so special? The answer lies in the “AI” part of OCR.  AI OCR – we have a multi layered AI-Powered OCR.  This is one of the first steps of our complete Intelligent Document Processing (IDP) solution. The AI OCR identifies all the data within the document or image (even complex table data), improves and enhances the image quality, removes ‘noise’ from the image such as watermarks, background patterns and more.  IDP, with re-enforced learning from human feedback and human verification, delivers 99.99% accuracy and the intelligence. Here’s why that’s a big deal: We understand context: Instead of just pulling out raw data, AOTM’s OCR knows what the information means—it can tell the difference between a bank statement and an invoice and extract the right data. We understand unstructured documents: PDFs, scans, images, purchase orders, emails, invoices, statements, forms—any quality, any language We keep learning: With each document AOTM processes, it’s system gets smarter, improving accuracy and efficiency over time. This isn’t just OCR—it’s intelligent OCR. And for banks, that intelligence leads to big savings in time, resources, and money. We connect the dots, AOTM understands the data and relationships. How AOTM’s AI-Driven OCR is Reducing Banking Costs 1. Automating Manual Tasks Think about all the hours your team spends on data entry—extracting numbers from loan applications, filling out forms, verifying checks. Now imagine if all that could happen instantly, with no human intervention. With AOTM’s OCR solution, it can: Less labour required: Automation means fewer employees needed to handle repetitive tasks, which immediately reduces staffing costs. Faster processing: What used to take days can now happen in a matter of minutes, speeding up loan approvals, KYC verification, and more. 2. Error Reduction and Compliance Banking is an industry where mistakes can be costly—not just financially, but also in terms of regulatory compliance. Manual data entry can result in errors that might go unnoticed until it’s too late. With AOTM’s Advanced AI OCR: Error rates drop dramatically: The system ensures data is extracted and verified with near-perfect accuracy. Compliance is streamlined: By automating KYC and other regulatory processes, AOTM’s OCR ensures that no critical steps are missed, reducing the risk of fines or legal issues. 3. Scale Without Extra Costs One of the coolest things about AOTM’s OCR is its ability to scale. Whether you’re processing hundreds of documents or thousands, the system doesn’t break a sweat: No need to expand your team: During peak times, like tax season, banks don’t need to bring on additional staff—AOTM’s OCR can handle it all. Cloud-based scalability: It’s designed to grow with your needs without adding extra infrastructure costs. 4. Faster Customer Onboarding and Better Experiences Customer experience is critical in banking, and delays in document processing can lead to customer dissatisfaction. With AOTM’s OCR solution: KYC and loan approvals happen faster: Customer documents are processed in real-time, cutting onboarding times from days to minutes. Improved customer satisfaction: Faster service means happier customers, and reduced wait times lead to stronger retention. Real-World Use Cases of AOTM’s AI-Driven OCR 1. Loan Processing When banks receive loan applications, they’re flooded with paperwork tax returns, pay stubs, bank statements, the works. AOTM’s OCR automatically extracts and verifies this information, allowing loans to be processed in hours instead of days. The result? Faster approvals, happier customers, and lower labour costs. 2. KYC Compliance Banks need to verify customer identities as part of strict KYC regulations. This involves handling tons of ID documents—passports, driver’s licenses, utility bills, etc. AOTM’s OCR automates the entire process, extracting data and cross-referencing it instantly. This reduces manual labour and ensures compliance. 3. Check Processing Gone are the days of manually verifying checks. AOTM’s AI OCR automates this process, instantly extracting and verifying key data like amounts and account numbers. This speeds up clearing times and cuts down on the time and cost of check processing. Why AOTM’s Advanced AI OCR is the Future of Banking AOTM’s AI-powered OCR isn’t just about digitizing documents—it’s about transforming how banks operate. By automating complex document workflows and integrating seamlessly into existing systems, AOTM’s AI-powered OCR solution offers banks the ability to: Reduce operational costs: Fewer errors, faster processing, and lower staffing requirements mean banks can operate more efficiently. Stay competitive: In a rapidly changing industry, banks that embrace automation and AI will be better equipped to meet customer expectations and regulatory demands. Improve scalability: As document volumes grow, AOTM’s OCR solution scales with them, ensuring that banks can handle peak times without additional investment. Wrapping Up: The AOTM Difference AI-powered OCR is the key to unlocking massive operational efficiencies in banking, and AOTM’s Advanced AI-powered OCR is leading the way. By automating document


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Intelligent Document Processing Solutions

How AOTM is Leading the Regulatory Reporting with IDP and ML?

Regulatory reporting is one of the most demanding tasks in industries like banking, insurance, and finance. Endless paperwork, tight deadlines, and zero tolerance for errors turn it into an exhausting process. A single mistake could lead to costly fines or even damage to a company’s hard-earned reputation. But the days of manual data extraction and error-prone processes are fading. The future of regulatory reporting lies in automation, and companies are now discovering the power of Intelligent Document Processing (IDP) solutions with AI OCR to streamline these tasks. AOTM’s Intelligent Automation Platform is at the forefront of this revolution, offering cutting-edge machine learning models with 99.99% accuracy in data extraction that completely transform how businesses manage regulatory reporting. Let’s take a closer look at how Intelligent Document Processing (IDP) solutions, AI OCR and real-time machine learning models are enabling organizations to reduce costs, improve accuracy, and remain compliantwith ease—all while taking the burden off their shoulders. Why is Regulatory Reporting So Painful? Let’s face it—regulatory reporting has traditionally been a headache. Whether it’s compliance documentation, financial disclosures, or legal reports, there are piles of data to sift through and compile. Add the ever-changing regulations and fast-approaching deadlines to the mix, and you have a recipe for operational chaos. Historically, regulatory reporting has depended on large teams of people manually extracting data from various documents—whether it’s invoices, legal contracts, or financial statements. This method is not only time consuming, but it’s also prone to human error, which can result in compliance issues, fines, or worse. But now, with the rise of Intelligent Document Processing (IDP)with AI OCR and real-time machine learning models, organizations can finally transform how they approach this cumbersome task. What is Intelligent Document Processing, and How Does It Help? Let’s break it down: Intelligent Document Processing (IDP) with AI OCR uses a combination of advanced technologies like AI, Machine Learning (ML), and Natural Language Processing (NLP) to automate the extraction, classification, and validation of data from various types of documents—whether structured, semi-structured, or unstructured. Here’s how IDP is transforming the regulatory reporting game: 1. Real-Time Data ExtractionRegulatory reporting typically involves gathering data from multiple sources and document types—everything from financial statements to legal contracts. AOTM’s IDP and AI OCR solution, powered by real-time machine learning models, makes this process completely automatic: No more manual entry: The system reads and extracts relevant information from documents in real-time, making it available instantly for regulatory reporting. Speed and efficiency: What used to take hours (or even days) can now be done in a matter of minutes with AI-driven automation. 2. Reducing Human Errors and Ensuring ComplianceManual data entry is error-prone, and in the world of regulatory reporting, even the smallest mistake can be costly. AOTM’s Intelligent Automation platform ensure: Fewer errors: Real-time machine learning models continuously learn and improve, resulting in high levels of accuracy and reducing the risk of human error. Better compliance: AOTM’s system flags any missing or incorrect information, ensuring that reports meet regulatory requirements and remain fully compliant. 3. Real-Time Machine Learning for AdaptabilityRegulatory requirements are constantly evolving. What was compliant one year might not be the next. With AOTM’s real-time machine learning models, businesses can adapt quickly: Dynamic learning: AOTM’s system continuously learns from new data and regulations, adapting in real time without requiring manual reprogramming. Faster response to change: As regulations change, AOTM’s platform updates in real-time, so businesses stay compliant with the latest standards. 4. Real-Time Insights and Audit TrailsWhen it comes to regulatory reporting, having a transparent, real-time view is essential. AOTM’s Intelligent Automation Platform offers: Complete audit trails: Every document, data point, and decision is tracked and recorded, offering transparency that can be easily reviewed during audits. Real-time insights: AOTM’s dashboards provide up-to-the-minute reporting and performance metrics, making it easy to monitor compliance status and reporting progress.  AOTM’s Intelligent Automation Platform: The Future of Regulatory Reporting AOTM’s platform is built specifically to tackle these challenges using AI-driven Intelligent Document Processing solutions with AI OCR and real-time machine learning models. Here’s what sets our solution apart: 1. Machine Learning for Document ProcessingTraditional OCR (Optical Character Recognition) technology may help scan and convert documents, but AOTM’s AI OCR and machine learning models take it a step further. Our platform doesn’t just extract data—it understands the context, learns from past interactions, and continuously improves the accuracy of data capture. 2. Customizable Workflows for Every Regulatory NeedEvery industry has its own unique set of regulations and document types. AOTM’s Intelligent Automation Platform allows businesses to build custom workflows to suit their specific regulatory requirements. Whether you’re processing financial statements, invoices, or legal documents, the system is fully adaptable. 3. Unparalleled AccuracyWith real-time machine learning models, AOTM’s IDP platform offers 99.99% accuracy in data extraction and validation. And the best part? The system learns and improves over time, meaning accuracy continues to improve the more it’s used. 4. Time-Saving AutomationTime is of the essence when it comes to regulatory reporting, especially with strict deadlines and evolving regulations. AOTM’s Intelligent Automation Platform automates data extraction and validation in real-time, slashing the time it takes to compile reports. 5. Scalable and Cloud-ReadyWhether you’re processing hundreds or thousands of documents, AOTM’s platform scales to meet your needs. It’s fully cloud-based, ensuring seamless integration and scalability without requiring additional infrastructure. How Real-Time Machine Learning Models Are DrivingRegulatory Reporting at AOTM Let’s talk specifics. Financial institutions that needs to submit quarterly reports to regulatory bodies. Normally, this would involve pulling data from hundreds of documents, validating the information, and compiling it into a report. With AOTM’s real-time machine learning models, this process is completely automated: Automatic data extraction: Relevant information is pulled from documents, checked for accuracy, and validated. Real-time learning: As the system processes more documents, it learns from new data and continuously improves its understanding. Faster, error-free reporting: The final report is ready in a fraction of the time it would take manually—without the risk of human error. With AOTM’s real-time machine learning models working in the background, businesses can now focus on more strategic tasks


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Intelligent Document Processing

How Can Intelligent Document Processing (IDP) Help Organisations Succeed?

Intelligent Document Processing (IDP) converts manual forms into a digital format to integrate these documents into business processes. This technology exists to help organisations to save time, save money, and to reduce errors while processing and digitising documents.  IDP is a viable way for companies to increase the capacity of their existing workforce, allowing them to handle more without increasing the headcount. As almost every organisation is mandated to do more with less, IDP is a critical technology that can help organisations thrive. Although IDP sounds like the latest innovation in the AI space, the IDP industry has evolved over the last 30 years. In the early days, it used Optical Character Recognition (OCR) solutions to convert letters and characters in the images into machine-encoded text. Today, next-generation solutions can interpret natural language, incorporate computer vision, and advance machine learning. The next-generation IDP solutions play nice and integrate with a whole stack of enterprise applications. The benefits of intelligent document processing technology are almost endless,  Reduce costs Increase productivity  Improve security  Saves time  Eliminate manual processes  Automate repetitive tasks  Create custom workflows  Streamline business processes and much more!  In the upcoming section, we will focus on a few of the benefits of using IDP.  Five Ways Intelligent Document Processing Technology Helps Businesses Succeed 1. Automate document processing tasks Many business processes are automated by intelligent document processing technology, including scanning, OCR (Optical Character Recognition), indexing, tagging, and data extraction. These technologies help businesses in saving time and money while increasing productivity. 2. Improves Customer Service Intelligent document processing technology enables businesses to provide customers with faster and more accurate responses. Documents are automatically indexed and tagged when scanned, making them searchable and accessible. Companies can then respond to customer inquiries without manually reviewing each document. 3. Reduce Costs Companies can use Intelligent Document Processing technology to reduce paper-based operations and eliminate the need for manual labour. Furthermore, Intelligent Document Processing minimises the time spent on repetitive tasks, resulting in greater efficiency. 4. Optimise Workflow Intelligent document processing software makes workflow management easier and eliminates the need for employees to perform mundane tasks such as copying and entering data from business documents and forms. By integrating with existing systems, Intelligent Document Processing technology increases the speed at which documents and data are processed to streamline your business operations. 5. Improves Accuracy IDP solutions eliminate the need for manual processing of data. Hence, there is no room for human error, and the data extracted is >99% accurate. IDP ensures that data extraction processes are quicker and more accurate than before.


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Intelligent Document Processing: A Detailed Guide

Did you know more than  80% of enterprise data is unstructured? Yes, you read that right. A common challenge most companies face is a large volume of data that goes unprocessed daily due to its unstructured or semi-structured nature.  While there are traditional methods of processing data, they have proven to be expensive, time-consuming, and prone to many errors. Hence, companies have now turned to Intelligent Document Processing (IDP).  You must wonder what Intelligent Document Processing is; let us explore that in the following sections.  What is IDP?  Intelligent Document Processing (IDP) eliminates the need for manual data extraction by replacing it with machine learning and AI-based technologies. With the help of these technologies, IDP extracts data from documents automatically and converts semi-structured or unstructured data to structured data that companies can use for various purposes.  To automatically extract data, IDP uses different solutions such as Computer Vision, Optical Character Recognition (OCR), Natural Language Processing (NLP), Human in the Loop, and much more. Apart from data extraction, IDP also ensures that the extracted data is categorised, classified into relevant categories, and is simultaneously validated.  More often than not, IDP is often mistaken for OCR and vice versa. However, this is not true. Let us look at the differences between IDP and OCR to help us differentiate between the two.  Before we understand the differences between OCR and IDP, let us look at the various ways data extraction takes place. There are three ways in which data can be extracted — Manual Data Extraction, Optical Character Recognition (OCR), and Intelligent Document Processing. The least preferred of the three is manual data extraction, which proves to be cumbersome and prone to many errors. The following preferred choice is optical character recognition. You must wonder what optical character recognition is; we will give you a brief explanation below.  What is OCR? Optical character recognition assists in converting a scanned image into text by transcribing each character found on the image. In short, OCR extracts the text it detects on an image and converts it into readable information for its user.  There are two kinds of OCR — template-based OCR and zonal OCR. With template-based OCR, you can easily extract any information from a template-based document. On the other hand, the zonal OCR detects blocks of text or a ‘zone’ of the document and extracts data from the same. However, there is a downside to using OCR for data extraction.  While OCR works well with a template-based document, any slight variation in the template leads to an unsuccessful data extraction through OCR. OCR’s limited scope cannot cater to semi-structured and unstructured documents. To help overcome these limitations, companies have turned to IDP. Now, let us understand the differences between OCR and IDP.  OCR vs IDP The key differences between OCR and IDP are as follows: Key Differences  OCR IDP Scope Caters to template-based documents.  Can extract and process data from template-free and complex documents. Accuracy Data processed by OCR has to be manually verified as it can be prone to errors. IDP is almost error-free as it uses HITL technology to validate the data extracted automatically. Automation Cannot extract data fromhandwritten documents or legal documents such as contracts. IDP uses AI technology toadapt itself to extract data from multiple templates and layouts. Capability OCR is limited to data extraction; it does not perform any additional functions. IDP extracts data and classifies the extracted data into relevant categories and simultaneously validates it. As you can see from the above table, Intelligent Document Processing has proven to be more efficient than traditional OCR. However, despite its limited functionality, traditional OCR should not be overlooked. Many companies use OCR combined with Intelligent Document Processing solutions to achieve optimal results. Now let us explore the benefits of IDP.  Benefits of IDP  We have a fair overview of Intelligent Document Processing and how it works; let us now examine the key benefits of using Intelligent Document Processing solutions. The key benefits of IDP are as follows:  Cost-Effective  Running on a fixed budget is crucial for any business. However, document processing can prove to be expensive as it requires a large number of people. With Intelligent Document Processing solutions, you can eliminate the need for manual verification as they assist you in quickly processing, classifying, and validating data. Hence, as an organisation, if you choose to employ IDP solutions, you are bound to reduce the cost of document processing by 50% or more in a year.  Quick Processing  Data extraction can get painfully excruciating when there is a large volume of data that has to be processed. It is because manual data processing can be time-consuming and cumbersome. However, Intelligent Document Platform platforms and solutions have tackled this issue by employing AI and machine learning technology to process and classify data quickly. With IDP, you can save about 50% to 70% of document processing time.  Improved Accuracy As mentioned above, IDP solutions eliminate the need for manual processing or verification of data. Hence, there is no room for human error, and the data extracted is almost 99% accurate. IDP ensures that data extraction processes are quicker and more accurate than before.  Scalable Solutions  A common challenge with manual data processing or traditional OCR is that they cannot extract data from various sources such as handwritten documents, receipts, contracts etc. IDP solutions tackle these issues as it uses its AI and machine learning capabilities to adapt itself to extract data from various sources and documents of different sizes and layouts. It not only extracts data but also interprets the information found on a specific document.  Enables Automation  Most companies lose a fair amount of time performing mundane day-to-day tasks. Everyday tasks can get monotonous and may even disrupt the workflow. With Intelligent Document Processing platforms, you can help simplify data processing by automating daily, mundane tasks integral to a smooth business workflow.  Enhances Quality of Data  Almost 80% of data is unstructured, making it inaccessible. Yet another benefit of Intelligent Document Processing solutions is that it enhances the quality of data once extracted from its source. Hence, IDP solutions


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Time to drop traditional data processing and adapt “intelligent” solutions

These days, no organization can function without data. Data is the fuel that powers businesses since enormous volumes of data are produced every second from corporate transactions, sales numbers, customer logs, and stakeholders. All of this information is compiled into a sizable data set. It has its own unique difficulties. To improve decision-making, this data needs to be examined. However, businesses still face certain difficulties with large volumes of data. These include issues with data quality, storage, a dearth of data science experts, validating data, and gathering data from various sources, this will lead to bottlenecks in business processing and challenging to take decisions based on the data for further growth of the company. According to various estimates, 80% of enterprise data is semi-structured or unstructured, making it challenging to automate processes using conventional automation technologies. Enterprises are increasingly required to process massive amounts of semi-structured and unstructured materials more accurately and quickly. RPA can automate data from legacy, third-party, and web apps (surface automation), but it does not work well with unstructured data sources (e.g., documents, emails, and attachments). Simply put, unstructured data is information that cannot be easily stored in a standard relational database and is not organized in accordance with a pre-established data model or schema. So how do businesses deal with processing unstructured data in processes that are document-centric? Despite the fact that optical character recognition (OCR), whose accuracy with legacy OCR is only about 60%, aids in the digitalization of paper-based information assets, its inherent quality problems are difficult to ignore. For further processing by RPA or other downstream systems, intelligent document processing (IDP) solutions can process semi-structured & unstructured data and transform it to structured format in this situation. Data comes in various formats: Structured Semi-structured Unstructured Volume: this data is generated constantly Velocity: you need to process them quickly Variety: many sources and data types are used Veracity: data must be of good quality  The IDP software market is expanding quickly All vertical industries’ organizations continue to rely heavily on papers as a source of data input. The unstructured data in these documents necessitates knowledge workers for manual data entry, exception management, and quality checks, which makes document processing labor-intensive, time-consuming, and expensive. Large, small, and medium-sized businesses all spent roughly $400 million on IDP software in 2018, and that amount rose to about $550 million in 2019. According to Everest Group projections. It is simple to see how the unorganized document processing market for machine learning (ML) solutions is big enough for bundled IDP solutions to gain traction. Some of the main use cases for IDP solutions are Know Your Customer (KYC), invoice processing, insurance claims, patient onboarding, patient records, proof of delivery, and purchase forms. IDP software is useful in business-specific procedures including trade financing, mortgage processing, customer onboarding, and the preparation of legal papers. Given its high volume and proneness to error, accounts payable and accounts receivable are frequent use cases for IDP in the financial and accounting industry. Document automation is slowed significantly by the need to create templates In general, users of IDP software should only require a minimal amount of training for template updates. However, businesses who work with hundreds to thousands of vendors each month are aware that updating invoice templates is a time-consuming procedure. The amount of consultation time required to set up and use templates for different sorts of documents can drastically increase total costs. In such circumstances, it is simple to see how an IDP without templates can drastically lower total cost of ownership (TCO) and enable a quicker time to automation. There is no need to wait for months to create templates, let alone actual documents. IDP solutions serve as an intelligent automation tool with a specific purpose Simply said, intelligent automation integrates RPA and document capture and processing capabilities with artificial intelligence (such as natural language processing, machine learning, and computer vision). IDP solutions are utilized to ingest unstructured data into workflows for end-to-end automation, and AI/ML capabilities are leveraged to increase straight-through processing (STP) with accuracy. Automated data verification and validation as well as ongoing learning and improvement based on AI/ML algorithms and user inputs are made possible by pre-built AI/ML capabilities and business rules. IDP automates the retrieval, comprehension, and integration of documents needed for carrying out a business process by combining OCR, data capture, and AI/ML. End-to-end process automation is possible when RPA, IDP, and APIs are utilised in conjunction. IDP enables data-led automation of documents including unstructured and semi-structured data, in contrast to RPA’s focus on processes.


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