Proven Results

Client Success Stories

Three detailed case studies showing how HNBC transformed real enterprises — from problem statement through solution architecture to measurable business impact.

AI-Powered Fraud Detection Platform

Private Sector Bank • 2M+ Customers • South India

Replacing Rule-Based Fraud Detection with Real-Time ML

A high-growth private bank was losing ₹3.2 Cr annually to digital fraud while their legacy rule-based system flagged 89% false positives, frustrating genuine customers.

The Challenge

The bank's fraud prevention team operated a 12-year-old rule engine with 240+ static rules manually curated by analysts. As digital transaction volumes tripled post-COVID, the system collapsed under load — scoring delays of 3-8 seconds were killing the mobile banking UX. Worse, adaptive fraudsters learned to circumvent the static rules within days of each update, causing recurring losses across credit card skimming, UPI reversal fraud, and identity-spoofed account takeovers.

Our Solution

HNBC designed and deployed a three-layer real-time fraud intelligence platform built around ensemble machine learning models, streaming event processing, and a closed-loop feedback system that continuously retrains on new fraud patterns.

  • Apache Kafka-based real-time event streaming at 50,000+ TPS
  • Ensemble ML model: XGBoost + LSTM + Graph Neural Network for account behaviour
  • Feature store (Redis + PostgreSQL) serving 180+ engineered features sub-10ms
  • Explainable AI (SHAP values) for analyst review and regulatory audit trails
  • Automated model retraining pipeline triggered by drift detection (Evidently AI)
  • React-based analyst dashboard with real-time alert queue and case management

Architecture Highlights

The platform runs on AWS with EKS for the model serving layer, Kinesis for event ingestion, and Aurora PostgreSQL for the feature store. Auto-scaling handles transaction spikes during salary credit days (5-10× normal volume) with zero SLA degradation. All model decisions are logged to an immutable audit ledger compliant with RBI's fraud monitoring framework.

Technology Stack

PythonXGBoostPyTorch Apache KafkaApache Flink AWS EKSRedis Aurora PostgreSQLReact GrafanaEvidently AI

“HNBC transformed our fraud operations completely. We went from fighting fires daily to proactively blocking fraud before it completes. The ROI was evident within the first quarter.”

— Chief Risk Officer, Private Sector Bank (name withheld for confidentiality)

Business Impact

73%
Reduction in fraud losses (₹2.34 Cr saved in Year 1)
91%
Fewer false-positive alerts (down from 89% to 8%)
50ms
Average fraud scoring latency (was 3-8 seconds)
50K+
Transactions scored per second at peak
18 mo
Full ROI payback period

Project Details

Industry: Banking & FinTech

Client Size: Mid-sized bank, 2M+ customers

Duration: 9 months (including integration testing)

Team Size: 12 HNBC engineers + 3 client SMEs

Engagement: Fixed-scope + managed service

Compliance: RBI Fraud Monitoring Framework

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Hospital Information System Modernisation

500-Bed Multi-Specialty Hospital • Chennai, Tamil Nadu

Zero-Downtime Migration from Legacy HIS to Cloud-Native Platform

A leading multi-specialty hospital was running a 12-year-old HIS that produced ₹40L+ in annual billing errors and required 45 minutes to generate daily MIS reports.

The Challenge

The hospital operated across four buildings with 47 departments, 500 beds, and 1,200+ daily outpatient visits. Their legacy HIS ran on an on-premise Windows server with a monolithic .NET codebase last updated in 2012. Critical issues included: billing module miscalculations costing ₹40L+ per year, zero mobile access for doctors during ward rounds, no interoperability with diagnostic lab systems, and a complete inability to participate in India's Ayushman Bharat Digital Mission (ABDM) due to lack of FHIR support.

Our Solution

HNBC designed a phased, zero-downtime migration strategy: run the new cloud-native system in parallel for 60 days before cutting over. The new platform was built as a microservices architecture on Azure, with each hospital department as an independently deployable domain service.

  • Microservices architecture: 18 domain services (OPD, IPD, Pharmacy, Lab, Billing, etc.)
  • FHIR R4 compliant EHR with ABDM Health Locker integration
  • Real-time HL7 v2 integration with LIS (Laboratory) and RIS (Radiology)
  • Progressive Web App for doctors' ward round mobile access
  • Automated billing rules engine eliminating manual tariff calculations
  • Power BI-embedded analytics replacing the 45-minute MIS report with a live dashboard

Migration Strategy

Data migration of 3M+ patient records was executed using a custom ETL pipeline with deduplication, validation, and rollback capabilities. The 60-day parallel run allowed staff to gain confidence before the final cutover, which happened on a Sunday at 2 AM with 100% data integrity. Post-go-live, HNBC provided on-site support for 30 days, training 380 staff members across all shifts.

Technology Stack

React / PWANode.js Azure KubernetesAzure SQL HL7 FHIR R4ABDM APIs Redis CachePower BI Azure DevOps

“The transition was remarkably smooth. Our doctors love the mobile access. We've gone from dreading billing disputes to having full confidence in every invoice we raise.”

— Medical Director, Multi-Specialty Hospital, Chennai

Business Impact

₹40L
Billing errors eliminated annually
50%
Reduction in administrative staff overhead
3M+
Patient records migrated with 100% integrity
100%
ABDM & NABH compliance achieved
0
Minutes of unplanned downtime during cutover

Project Details

Industry: Healthcare

Client Size: 500-bed hospital, 47 departments

Duration: 14 months (incl. parallel run)

Team Size: 18 HNBC engineers

Engagement: Fixed-price turnkey + SLA support

Compliance: ABDM, NABH, HL7 FHIR R4

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Headless Commerce Platform at Scale

Omnichannel Retail Chain • 200 Stores • India

Unifying 200 Physical Stores on a Single Digital Commerce Platform

A mid-market fashion retail chain with 200 stores and a fragmented digital presence needed a platform capable of surviving Diwali peak — and winning back customers lost to marketplace competitors.

The Challenge

The retailer operated an outdated Magento 1.9 storefront that crashed during the 2022 Diwali sale, losing an estimated ₹1.8 Cr in sales in 4 hours. Their 200 stores had no real-time inventory visibility — customers regularly arrived to collect click-and-collect orders that were already sold offline. Product data existed in three different systems with no single source of truth. The mobile experience was non-existent, despite 78% of their web traffic being mobile.

Our Solution

HNBC built a headless commerce architecture separating the commerce engine from the presentation layer, enabling best-in-class performance, flexibility for channel-specific experiences, and infinite scalability via serverless compute.

  • Next.js 14 storefront with server-side rendering (LCP under 1.2s)
  • Shopify Plus as headless commerce engine via GraphQL Storefront API
  • Real-time inventory sync across 200 stores via webhook + event bus architecture
  • AI personalisation engine (CollaFilter + embedding model) boosting average order value
  • React Native app (iOS + Android) with in-store QR scan-to-cart
  • Unified Order Management System handling BOPIS, ship-from-store, and returns
  • Razorpay + Simpl + UPI payment integration with one-click checkout

Performance & Scale

The new platform was load-tested to 50,000 concurrent users before the 2023 Diwali sale. Peak traffic reached 38,000 concurrent sessions — the system responded with 99.99% uptime and an average page load of 1.1 seconds. The store achieved ₹12 Cr in online revenue in the first year post-launch, against a pre-project baseline of ₹3.2 Cr.

Technology Stack

Next.js 14React Native Shopify PlusGraphQL AWS LambdaCloudFront CDN ElasticsearchRedis RazorpaySegment

“This Diwali we didn't just survive — we thrived. The platform handled everything thrown at it. Our online revenue grew 3.75× year-on-year. HNBC delivered exactly what they promised.”

— Chief Digital Officer, Omnichannel Retail Chain, India

Business Impact

2.8×
Increase in online conversion rate
₹12Cr
Online revenue in Year 1 post-launch
99.99%
Uptime during Diwali peak sale
1.1s
Average page load time (was 8.4s)
60%
Reduction in cart abandonment rate

Project Details

Industry: Retail & eCommerce

Client Size: 200+ stores, pan-India

Duration: 10 months

Team Size: 14 HNBC engineers & designers

Engagement: Fixed-price project

Platforms: Web + iOS + Android

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