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QualityKiosk Helps a Leading Private Sector Bank Achieve Intelligent, Real-Time Loan Deduplication
Industry & Segment
Objective
To enable real time and accurate detection of duplicate loan applications including in-process cases through a scalable and secure rule based deduplication system that reduces fraud and accelerates loan approvals.
Partner
Overview
A leading private sector bank in India sought to strengthen its loan processing system by minimizing duplicate applications and reducing potential fraud.
The bank aimed to leverage the Elasticsearch stack to design and deploy an advanced, rule-driven deduplication system that could accurately detect duplicate loan applications, including in-flight transactions (applications still under processing), while maintaining speed, accuracy, and compliance with stringent security standards.
Engagement Overview
The bank’s existing systems could only detect duplicates among disbursed loans, leaving in-process applications unchecked. This key compliance gap increased the risk of duplicate loans, data inconsistencies, and fraud.
To close this gap, QualityKiosk Technologies designed and implemented a high-performance, deduplication search engine powered by Elasticsearch, AWS Lambda, and other AWS components.
The project involved building a custom service layer that handled over 40 complex API calls dynamically, ensuring only relevant checks were executed per transaction while maintaining sub-second response times, even at scale.
Business Challenges
Contact us to transform your loan processing with real time intelligent deduplication
QualityKiosk’s Solution and Approach
QualityKiosk designed and implemented a next-generation Elasticsearch-based deduplication framework, engineered for precision, scalability, and compliance.
1. Intelligent, rule-based deduplication logic
- Optimized execution by running only needed API calls from up to 42 queries. For example, if a user entered a PAN, only PAN-related validation rules were triggered; if a mobile number or email was provided, corresponding match rules were executed dynamically.
- This adaptive rule execution significantly improved query performance and system efficiency.
2. Enhanced search relevance with advanced analyzers
- Leveraged custom Soundex analyzers and fuzzy matching capabilities to detect similar-sounding names or variations.
- Supported both exact match and partial (percentage-based) match conditions for improved deduplication accuracy.
3. Cloud-Native Architecture on AWS
- Deployed on AWS Lambda to enable scalable, event-driven query execution.
- Integrated Logstash with the JDBC plugin for incremental data ingestion, ensuring up-to-date results across millions of records.
4. Enterprise-Grade Security and Compliance
- Implemented role-based access controls, data encryption/decryption, and ensured the entire setup passed VAPT validation at the client’s end.
- Continuous collaboration with the bank’s security teams ensured compliance with internal IT and audit standards.
Strategic Business Outcomes
Fraud and Risk Mitigation
Substantially reduced the bank’s risk of fraudulent or duplicate loan disbursals by enabling precise, real-time duplicate detection across in-progress applications.
Operational Agility
Accelerated the loan disbursal process by automating key verification steps, enabling faster approvals and smoother workflows for the Loans team.
Customer Trust & Experience
Enhanced customer experience by identifying and eliminating duplicate loan applications, ensuring faster processing and accurate application tracking.
Future-Ready Infrastructure
Delivered a scalable and extensible deduplication framework that can easily adapt to other financial products or business lines.
Results Achieved
100%
coverage of in‑process (real‑time) applications
10,000+
loan applications/day processed
42
dynamic deduplication rules executed per transaction
< 1
second response time (millisecond latency)
Business Impact
Enabled real-time deduplication checks for all in-process loan applications, covering up to 10,000 applications per day.
Achieved millisecond-level response times, typically under one second, even while executing up to 42 dynamic Elasticsearch queries per transaction.
Enhanced search relevance and accuracy through Soundex analyzers and fuzzy match queries, improving the system’s ability to detect duplicate or near-duplicate entries.
Ensured secure, compliant, and stable operations by passing client-led VAPT assessments and implementing robust encryption and access controls.
Implemented dynamic rule execution that automatically triggered only relevant checks based on input data.
TESTIMONIAL
Testimonial
QualityKiosk helped us close a critical gap in our loan processing as our legacy system couldn’t detect duplicates among in-process applications. Their Elasticsearch-based solution now processes over 10,000 applications daily with millisecond response times, dynamically running up to 42 deduplication checks per transaction. It’s significantly reduced our fraud exposure and accelerated loan approvals, all while meeting our stringent security and compliance requirements.
Senior Vice President
Big Data Leading Bank, India
Conclusion
By enabling real-time, rule-based checks with millisecond response times, the solution helped the bank reduce fraud risks, speed up loan processing, and build a scalable, future-ready framework for smarter lending decisions. To explore how we help teams overcome similar challenges, learn more about our Enterprise AI Search services.
BAN-ENAI-2078
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