Fire Safety  
Inspection Software

Fire Safety  
Inspection Software

Business Challenge

  • The business faced a significant challenge in efficiently auditing a multitude of loan application documents.
  • With each application comprising in excess of 1000 pages and a diverse array of mandatory documents, the manual auditing process was time-consuming and prone to errors.
  • Moreover, ensuring compliance with over 250 rules added further complexity to the task. These challenges not only hindered operational efficiency but also posed a risk to regulatory compliance and customer satisfaction.

Objective

  • The primary objective was to develop a streamlined solution capable of automating the audit process for loan applications & associated documents
  • The goal was to leverage advanced AI technologies to enhance efficiency, accuracy, and compliance while reducing the time & resources required for loan audits.
  • Additionally, ensuring the security & confidentiality of data throughout the auditing process was paramount. The business aimed to achieve greater operational efficiency, improve regulatory compliance, and enhance customer satisfaction.

Solution

The team devised an Automated Loan Audit System to address the complex auditing process outlined above. This system tackles the complexities of auditing numerous documents, each containing extensive loan application forms and financial details.

The process involves auditing multiple documents, with each loan application comprising over 1000 pages. Additionally, around 50 mandatory documents need evaluation. In total, these applications and documents involve over 250 rules that must be applied to the original data.

In the early stages of the project, the team prioritized understanding the various applications involved, gathering crucial details, and analyzing diverse PDF documents. The solution integrates advanced AI services to streamline the audit process. However, before delving into the technical details of the implementation, crucial considerations such as data encryption, access control, and user authentication were addressed. This ensures that sensitive information extracted from PDF files is securely handled and protected throughout the audit process.

The system architecture, built on Azure cloud infrastructure, is designed for flexibility and scalability. It comprises serverless functions communicating through a message bus. Modules including Document-Analyze, Document-Split, Document-Data-Extraction, Rules-Engine, and Document-Table-Trigger have been meticulously integrated to handle various document sizes and types effectively.

         Process:

    • Document Intelligence: Extracts applicant data from PDF files.
    • Rule Engines: Validate loan data against audit guidelines.
    • Discrepancy Identification: Identifies discrepancies and generates audit reports.

        Key features of the Automated Loan Audit System

    • It includes generating dynamic audit reports, rule validation, scalability, performance, and robust security measures.
    • These features ensure that the system can handle volumes of audit tasks efficiently while maintaining data integrity and security.

Comprehensive testing has been conducted to validate the functionality, performance, security, and user acceptance of the system. Performance testing has confirmed the system's ability to process audits within specified timeframes, exceeding volumes ensuring optimal performance under varying conditions.

Deployment of the AI Audit Solution involves Azure Cloud setup, environment configuration, and deployment for user acceptance testing (UAT). A dedicated support team has been established to provide ongoing support, maintenance, and user training. Updates and enhancements are planned based on user feedback and implemented following a Change Control Process to minimize disruption and ensure continuous improvement of the system.

Distinctive Features

  • It includes generating dynamic audit reports, rule validation, scalability, performance, and robust security measures. 
  • These features ensure that the system can handle volumes of audit tasks efficiently while maintaining data integrity and security.
  • Comprehensive testing has been conducted to validate the functionality, performance, security, and user acceptance of the system. Performance testing has confirmed the system's ability to process audits within specified volumes and timeframes, ensuring optimal performance under varying conditions.
  • Deployment of the AI Audit Solution involves Azure setup, environment configuration, and deployment to user acceptance testing (UAT). A dedicated support team has been established to provide ongoing support, maintenance, and user training. Updates and enhancements are planned based on user feedback and implemented following a Change Control Process to minimize disruption and ensure continuous improvement of the system.

Technologies

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