Transforming Shriram Finance’s Auto and Two-Wheeler Loan Processing with Glib.ai’s Intelligent Document Processing (IDP)

Client Overview & Impact

Shriram Finance, one of India’s leading non-banking financial companies (NBFCs), offers a diverse portfolio of financial products, with a strong focus on vehicle financing, including auto and two-wheeler loans. Facing challenges in manual document processing and an increasing demand for operational efficiency, Shriram Finance sought an advanced solution to streamline their loan approval processes and enhance their overall service delivery.

Business Challenges

Shriram Finance was grappling with a range of operational hurdles in their document processing and loan approval workflows:

Manual Document Validation

• The verification of Proof of Identity (POI) and Proof of Address (POA) was heavily reliant on human intelligence, making it time-consuming and prone to inconsistencies.
• Dependency on manual checks posed significant risks of delays, particularly in high-volume loan disbursements.

Turnaround Time (TAT) and Average Handling Time (AHT)

• Manual data processing extended TAT and increased AHT, resulting in delayed loan approvals and customer dissatisfaction.
• The average handling time for loan documentation spanned from 25 minutes to several hours, depending on complexity.

Risk and Fraud Management

• Detecting fraudulent documents and ensuring the authenticity of data were reliant on human checks, which limited the accuracy and speed of risk assessments.

Scalability Concerns

• Shriram Finance struggled to scale operations efficiently as the demand for auto and two-wheeler loans grew, due to bottlenecks in manual processing.

Glib.ai’s Solution: A Comprehensive Digital Transformation

Glib.ai deployed an end-to-end IDP solution customized to Shriram Finance’s specific needs, leveraging Artificial Intelligence (AI), Robotic Process Automation (RPA), and Machine Learning (ML) to automate and enhance their loan processing workflows.

Solution Components

Automated Document Classification and Extraction

• Implemented a state-of-the-art document classification system that categorized various types of documents such as KYC forms, bank statements, and proof of income.
• The IDP solution extracted key data points with over 93% accuracy, significantly reducing errors and ensuring reliable data input for risk assessment.

Human-in-the-Loop (HILT) Interface

• Integrated a HILT system to enable on-the-go training and verification, allowing Shriram Finance staff to oversee and correct discrepancies in real-time.
• This feature improved adaptability and supported continuous learning within the system.

Advanced Fraud Detection Mechanisms

• Employed AI algorithms to cross-validate POI and POA documents against third-party data sources, enhancing the detection of inconsistencies and potential fraud.
• The system flagged high-risk cases for further review by the risk team, streamlining the focus on complex assessments.

Reduction in TAT and AHT

• Automated the end-to-end loan processing workflow, reducing TAT by over 70% and cutting AHT from 25 minutes to under 3 minutes.
• This led to faster loan disbursement and improved customer satisfaction.

On-Premise and Compliance-Focused Deployment

• Delivered an on-premise solution that adhered to local regulatory requirements, ensuring data privacy and protection in line with the latest RBI guidelines.

Solution Workflow

Workflow Overview

1. Customer Interface → Customers submit documents digitally via a secure web portal.
2. Digital Document Submission → IDP technology categorizes and validates documents.
3. Automated Document Classification (IDP) → Intelligent processing of document types.
4. Data Extraction & Validation (RPA & AI) → AI-driven data verification.
5. Real-Time Risk Analysis → AI models analyze risks and detect fraud.
6. Quick Loan Approval → Faster loan approvals and disbursals.

Results and Impact

Key Benefits

• Reduction in TAT and AHT → TAT reduced by over 70%, AHT dropped from 25 minutes to under 3 minutes.
• Decrease in Manual Dependency → Automation reduced reliance on manual processes, allowing employees to focus on strategic roles.
• Enhanced Data Accuracy → Achieved over 93% accuracy, minimizing human error.
• Scalable Operations → Enabled seamless scalability to meet growing demand.
• Improved Fraud Detection → AI-driven risk analysis increased fraud detection accuracy.
• Regulatory Compliance → On-premise deployment ensured full compliance with RBI and data protection laws.

Adoption Scale

• 2500+ Field Agents use the Glib Portal for document processing.

Quantitative Impact Summary

Conclusion

Glib.ai’s tailored IDP and automation solutions have provided Shriram Finance with a faster, more secure, and efficient approach to loan processing. By significantly reducing manual interventions, enhancing data accuracy, and optimizing regulatory compliance, Glib.ai has enabled Shriram Finance to offer a seamless, customer-centric experience that sets a benchmark in India’s vehicle loan sector.