Case Study

Transforming Home Loan Processing with Glib.ai’s Intelligent Automation

Client Overview & Impact

The Home Loans / LAP division of a leading bank, catering to a vast customer base seeking financing for their housing needs, annually processes thousands of applications. This involves managing an immense volume of documentation – approximately 7,500 applications per month, translating to over 1,500,000 pages of various documents. To enhance this process and reduce manual efforts, the company sought an advanced, AI-driven solution to transform their document processing and accelerate their loan approval workflows.

Business Challenges

Before the implementation of Glib.ai’s solution, the leading home loan provider faced several significant operational hurdles in their high-volume home loan processing:

Manual Document Validation & Processing Burden

Average Handling Time (AHT)

Data Input Discipline Due to the complex assessment process, the DSA and sales teams often submitted incomplete or inaccurate data:

Scalability Concerns


Glib.ai’s Solution: A Comprehensive Digital Transformation

Glib.ai implemented an end-to-end Intelligent Document Processing (IDP) solution combining AI, RPA, and ML, tailored to the unique and complex document-heavy workflows of the home loan provider.

Solution Components

Advanced Autoclassification

Contextual Extraction & Cross-Validation

Consolidated Financial Analysis

Human-in-the-Loop (HILT) Interface

Check Listing

Accelerated AHT

Secure & Compliance-Focused Deployment

Workflow Diagram


Results and Impact

Glib.ai’s tailored IDP and automation solutions delivered a profound transformation for the leading home loan provider.

Key Benefits

Metric Pre-Glib.ai Implementation Post-Glib.ai Implementation
Turnaround Time (TAT) for Document Verification 2 Days (manual processing only) Under 4 Hours
Overall Home Loan AHT 28 Days 26 Days (estimated post-Glib: derived from document process being a minor bottleneck; ~70–75% AHT reduction)
Manual Effort Reduction 450+ staff 40% reduction
Overall Data Accuracy High risk of human error Over 92% accuracy
Autoclassification Accuracy N/A 99% accuracy
Loan Processing Efficiency Time-intensive, error-prone Semi-automated, real-time insights

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