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Optimizing Loan Processing with Intelligent Automation: UiPath RPA Automation

Client Overview

A mid-sized small business and personal loan financial services organization has most of its business in the North American market. The organization processes thousands of loan applications every month through diverse channels like online applications, partner referrals, and direct applications.
Industry: Financial Services

Business Scope: The client manages a diverse loan portfolio across multiple business verticals, handling various loan types, including personal loans, small business financing, and specialized lending products. Their operations require accurate, real-time processing to meet customer expectations and maintain regulatory compliance.

Problem Statement

The client faced several pain points in their manual document extraction process:
  • Manual and Time-Consuming Application Processing: Loan applications required 20-30 minutes of manual processing, resulting in significant bottlenecks.
  • Inconsistent Data Entry: Manual data entry across multiple systems led to errors and compliance risks.
  • Resource-Intensive Operations: Scaling operations to meet growing demand required substantial increases in staffing.
  • System Integration Issues: Legacy systems were not effectively integrated, creating data silos that hindered decision-making.
  • Customer Experience Challenges: Support teams were overwhelmed with status inquiry calls, diverting resources from complex service needs.
These inefficiencies resulted in approximately 50% of potential customers abandoning the application mid-process and seeking alternatives with faster approval times, representing a significant revenue loss.

Solution: Automating Loan Processing with RPA

To address these challenges, a two-bot RPA architecture was implemented using UiPath – Dispatcher and Performer – to automate the complete document extraction pipeline from the VeraSuite portal.
Technology Stack
  • Robotic Process Automation (RPA): Automated the end-to-end loan processing workflow.
  • UiPath: Enterprise automation platform used to build, deploy, and manage software robots

Detailed Process Workflow

1. Form Submission Monitoring:

  • Bot checks designated Gmail accounts every 15 minutes
  • Identifies new loan application form submissions
  • Flag emails with the appropriate subject line and attachment formats.

2. Automated Data Extraction:

Extracts all mandatory fields from the application forms:
  • Applicant's name
  • Physical address
  • Property address
  • Loan type (Rental - Cash Out, Rental - Purchase)
  • Requested loan amount
  • Credit score
Structures extracted data into a standardized format for processing

3. Eligibility Calculation:

  • Applies pre-defined business rules to the extracted data
  • Performs calculations based on credit score thresholds
  • Evaluates loan-to-value ratios using the property address and the loan amount
  • Determines appropriate loan terms based on loan type (Rental - Cash Out vs. Rental - Purchase)
  • Calculates risk assessment scores

4: Portal Integration:

  • Automatically logs into integrated loan portals using secure credentials
  • Populates all required fields with the extracted and calculated data
  • Submits applications through the appropriate channels based on loan type

5: Data Validation and Exception Handling:

  • Validates data entry completion and accuracy
  • Identifies discrepancies or missing information
  • Route exceptions to human reviewers when needed
  • Records detailed logs for audit purposes

6. Notification Management:

  • Generates appropriate notifications upon process completion
  • Sends status updates to applicants
  • Alerts internal teams about approvals or exceptions requiring attention

Key Process Improvements

1. Loan Application Intake

  • Automated monitoring of Gmail accounts every 15 minutes to check for new loan application submissions.
  • Applied data extraction algorithms (Regex) to parse and structure mandatory application fields.

Pre-Automation Challenges

  • Manual monitoring of submission channels created delays in application processing.
  • Data extraction errors led to incomplete applications moving forward.
  • Inconsistent validation standards resulted in compliance risks.

Post-Automation Achievements:

  • Systematic monitoring of Gmail accounts every 15 minutes for new submissions.
  • 95% accuracy in data extraction and structured storage of mandatory fields.
  • Standardized validation ensures all regulatory requirements are met.

Eligibility Assessment

  • Implemented automated business rules to determine loan eligibility based on credit score and loan type.
  • Applied loan-to-value calculations using property addresses and requested amounts.
  • Generated pre-approval recommendations based on predefined criteria.
Pre-Automation Challenges:
  • Inconsistent application of eligibility criteria across processors.
  • Manual credit assessment led to subjective decisions.
  • The time-consuming evaluation process delayed customer notifications.
Post-Automation Achievements:
  • Consistent application of eligibility criteria across all applications
  • Objective credit assessment based on standardized models
  • Processing time reduced from 20-30 minutes to 3-5 minutes per application
  • Dynamic adaptation to changing business rules without coding changes

Implementation Approach

The automation was developed and deployed in a structured manner:
Step 1: Requirement Analysis & Planning
  • Documented existing manual loan processing workflows
  • Identified mandatory fields required for loan decisions (name, address, property address, loan type, loan amount, credit score)
  • Established key performance indicators for success
  • Created detailed process maps for automation design
Step 2: Development & Testing
  • Developed RPA workflows for each process component
  • Implemented secure Gmail monitoring with 15-minute intervals
  • Created data extraction components for all mandatory fields
  • Built calculation engines for eligibility determination
  • Conducted rigorous testing with real-world application scenarios

Step 3: Deployment & Monitoring

  • Deployed automation on secure cloud infrastructure
  • Implemented monitoring dashboards for real-time performance tracking
  • Established escalation procedures for exceptions
  • Created detailed audit logs for compliance requirements
Step 4: Training & Optimization
  • Trained loan processing staff on the new automated workflow
  • Provided support during the transition period
  • Gathered feedback for continuous improvement
  • Fine-tuned field extraction and calculation accuracy

Results & Impact

Quantitative Outcomes
  • 75% Reduction in manual effort for document extraction.
  • 50% Faster turnaround in compliance document readiness.
  • Zero Errors in document categorization and downloading phase.
Qualitative Benefits
  • Enhanced Customer Experience: Faster decisions and transparent communication improved satisfaction scores
  • Improved Compliance: Consistent application of rules and comprehensive audit trails reduced regulatory risks
  • Staff Satisfaction: Team members were reassigned to higher-value tasks, improving job satisfaction
  • Business Agility: Ability to quickly adapt to changing market conditions and regulatory requirements
  • Competitive Advantage: Dramatically faster processing times created a significant market differentiator
Ready to transform your financial services operations with RPA? Contact us today to discover how our tailored automation solutions can help you achieve similar results. Schedule a free consultation to discuss your specific challenges and opportunities
[email protected]

Client
Testimonial

The RPA solution has transformed our loan processing operations. What used to take our team 20-30 minutes per application is now completed in just 3-5 minutes through automation. The bot checks our Gmail accounts every 15 minutes and extracts all mandatory fields like name, address, property address, loan type, loan amount, and credit score. It then applies our business rules automatically to determine eligibility. With 95% accuracy in our data processing, we've significantly reduced errors while improving customer satisfaction. We've been able to redirect our team to focus on higher-value customer interactions rather than repetitive data entry
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Chief Operations Officer
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Auxiliobits is a global Software Consulting and Artificial Intelligence advisory company. Auxiliobits drives digital transformation by reinventing enterprise operations through hyper-automation and AI enabled applications.

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