Automate Fintech Services with AI Document Processing

Technological advancements in the last few decades have contributed immensely to the evolution of the banking industry. Years ago, opening a bank account or seeking a bank loan were complicated processes, and a small segment of the population utilized these services, but today there are hundreds of bank accounts opening across the globe every minute, each person has multiple insurances, and there are various types of loans a person can apply.

If you want to apply for a bank loan, you will probably register for a new loan on your banks’ website and share a few necessary documents that the bank requires to approve your loan. Once you apply for a loan, the bank collects the information you had shared, analyzes your bank statements, puts together all the necessary data to complete the underwriting process, fills out several forms for the bank’s record, and then disburses the loan.

With hundreds of loan requests coming in every day, manually collecting all the documents, analyzing the bank statements, and filling out multiple forms is time-consuming, inefficient, and prone to manual error. Inefficient processes and long durations of waiting give customers the perception of poor or inadequate service levels and can lead to unhappy and dissatisfied customers. Therefore, it becomes essential for banks to automate business processes and make them faster to retain customers and keep the business growing.

Like the loan disbursal process in banks, several core business processes in other financial services companies depend on extracting text and images from documents to update systems-of-records. Core business processes vary from company to company, depending on the domain they are in. Core processes in Banks, Financial Services, and Insurance companies include Know Your Customer (KYC), Fraud Management, Anti-money laundering (AML), Customer Onboarding, and Claims Underwriting. These processes require extracting text, images, and other content from documents such as bank statements, applications forms, credit reports, agreement forms, etc., and transforming the content into structured and usable data.

Existing solution & challenges

Operations in companies, especially in the Banking, Finance Services, and Insurance domain, involve manual processes such as extracting text and other information from these documents onto their internal databases (data entry), manual verification of multiple documents, processing of forms, etc. which are tedious, time-consuming, inefficient, expensive, and prone to error.

For example, in the case of processing loan/ insurance application forms, companies must extract information from multiple documents that contain free text and tables, tag and format extracted data for downstream processing, and have instant access to documents and structured data. Avoiding manual errors is essential to prevent the company from added complexities in such processes.

To automate these tasks, the business process owner has to either develop custom software using OCR techniques, Machine Learning, and workflow creation, or by implementing commercial products that can help companies with document processing and data extraction, but the existing products partly meet extraction and automation needs and add to integration overheads. Other challenges that companies face with the existing products include high cost, infeasible custom development, and unsuitable 3rd party technology.

An alternative solution

Technologies such as NLP, AI, ML facilitate intelligent document processing, which helps companies automate and centralize core business processes such as loan/insurance application processes. Automation will help companies in reducing costs without harming credit quality or customer service.

A software that can extract data from multiple types of documents, visualize the extracted data, tag and format the extracted data for downstream processing, correlate the extracted data with domain entities and that can be implemented easily with internal systems of a company will help companies in saving time, in eliminating manual processes and in taking faster and informed decisions.

Third Ray AI

Third Ray, a US-based company with global operations, can automate such processes by extracting text and images from any type of documents (.pdf, .docx, .png, .jpg) and storing the extracted data in the internal database. The stored data can be used for multiple purposes internally in companies. ThirdRayAI’s custom ML models can be trained to perform all the necessary operations.

Data-driven decisions are the essence of any company’s success and growth. As in the case of the Loan Disbursal process in banks, the financial stability of customers who had applied for a loan can be analyzed only with the help of data from previous bank statements. The banks take a data-driven decision whether to sanction a loan or not. ThirdRayAI’s Decision Support visualization will enable companies to gain insights into the extracted data and analyze the data.

As ThirdRayAI enables zero manual document processing with 100% GUI (no coding skills required), companies can gain over 80% savings when compared to other options.

ThirdRayAI has out-of-the-box template-based document processing automation, embedded Machine Learning models for common document types, over 70 common business systems, and databases configurable to support hundreds of integrations, custom automation, and insight engine, which will help companies in automating their core business processes.