Data Integration Case Study: Automation for Car Dealer

Grand Financial, Inc. is a US-based company offering vehicle sales combined with flexible financing options, including loans and credit services, operating within the automotive supply chain management ecosystem. Their ability to match customers with tailored financial products is a critical component of their value proposition and competitive advantage.

• A successful data integration case study: integration with multiple third-party financial institutions
• Automated financial offer synchronization (Azure Durable Functions)
• Web-based internal portal for offer comparison and tracking
• Real-time filtering and searching of loan data via React frontend
• Fully serverless backend for low-cost, scalable execution
• Faster decision-making and reduced manual data entry errors as key benefits

Before partnering with Softellar, Grand Financial relied on manual processes to gather financial offers from a network of lending partners, each with its own disparate data sources. Sales agents were required to log in to external portals, manually review loan terms, and enter relevant details into their internal CRM and other legacy systems - a process that was slow, error-prone, and inconsistent.

This bottleneck limited the number of financial offers available to customers, often resulting in suboptimal choices and lost sales opportunities. Additionally, the disjointed approach created unnecessary delays in the customer journey, making it difficult to scale operations or ensure data accuracy.

Grand Financial needed an automated, scalable solution to integrate directly with third-party systems, unify incoming data, and make real-time offers easily accessible within their existing workflow - a critical step to improve overall operational efficiency.

• 1 Senior .NET Backend Developer (integration APIs, Azure Functions)
• 1 Senior React Frontend Developer (search UI, results visualization)
• 1 Senior Azure Engineer (storage, sync logic, infrastructure)
• 1 QA Engineer (automated functional and regression testing)
• 1 Project Manager

Softellar designed and delivered a cloud-native platform that automated the entire process of combining data from collection to aggregation across the Customer’s financial partner network.

The solution was built around Azure Durable Functions for serverless orchestration of data management and synchronization tasks. These background processes query external APIs, normalize loan offer data, and store results in an Azure SQL Database, ensuring consistency and up-to-date information.

A .NET Web API layer effectively exposes this data to Grand Financial’s internal systems, while a custom React-based frontend enables users to search, filter, and compare loan offers by institution, rate, term, and eligibility.

To optimize performance and keep infrastructure costs minimal, the backend operates on a consumption-based plan with scheduled data syncs twice per day. The frontend is deployed via Azure CDN, providing fast, low-latency access to data and a seamless user experience for sales agents.

Automated Offer Aggregation

A serverless pipeline powered by Azure Durable Functions, one of the core data integration tools, orchestrates the retrieval of loan and credit data from multiple third-party financial institutions. The system automatically handles authentication, retries on failure, and data freshness validation.

Unified Data Layer

Softellar implemented a dynamic normalization engine to facilitate data integration, transforming incoming data into a consistent, queryable schema. This ensures that all offers are comparable across fields like APR, term length, lender, eligibility, and effective date.

Integration API

A RESTful .NET Web API exposes aggregated offer data to internal systems and the custom frontend. It supports role-based access, sub-100ms response time, and ensures seamless communication between business logic and presentation layers.

Interactive Internal Search Portal

Built with React JS, the internal portal allows sales agents to filter, compare, and bookmark offers in real time, enabling quick data analysis and decision-making. Smart filters, dynamic views, and high responsiveness ensure a frictionless experience and provide sales teams with comprehensive insights.

Offer Archiving & Audit Logging

Azure Blob Storage is used to store historical snapshots of all offers and synchronization logs. This ensures regulatory compliance, traceability, partner reliability tracking, and risk management.

Cloud-Native Deployment & Performance Optimization

The entire solution is hosted in Azure with a serverless-first design. Static content is distributed via Azure CDN, and background processes scale on demand.

Softellar followed a phased implementation to ensure seamless rollout and minimal business disruption:

1. Discovery & Architecture Design
   Aligned technical requirements with core business objectives
   Mapped data formats and endpoints from key financial partners
   Designed a scalable serverless architecture with sync scheduling
   Created a unified loan data schema to accommodate format variability
2. Prototype & Integration
   Built initial Durable Function pipelines for 2 institutions
   Delivered MVP frontend to preview offer matching
   Validated performance and consistency across systems
3. Feature Expansion
   Added filters, bookmarking, export tools, and user access roles
   Extended sync coverage to include all 6 partner APIs
   Tuned frontend UX and deployed via Azure CDN
4. QA & Optimization
   Automated regression testing and load simulation
   Optimized backend performance for faster syncs and reduced Azure costs
   Documented recovery procedures and fallback operation modes
5. Deployment & Handoff
   Final rollout across internal teams
   Delivered admin dashboards, system documentation, and monitoring tools
   Ongoing support during post-launch stabilization

By implementing an automated data collection and seamless data integration solution, Grand Financial, Inc. dramatically reduced manual workload and eliminated inconsistencies caused by human error. The ability to aggregate and present offers from multiple financial institutions empowered sales agents to deliver better financial options in less time.

Business Outcomes

• 80% reduction in manual processing time, boosting operational efficiency and freeing agents to focus on customer experience
• Increased loan offer availability, improving customer conversion rates through better data analysis
• Higher customer satisfaction through faster financial decision-making
• Improved operational scalability and reduced human error across sales and related departments

Technical Outcomes

• Seamless integration with 6 financial institutions using Azure Durable Functions
• Fully automated sync pipelines with minimal infrastructure overhead
• Responsive internal portal with sub-second load times
• Reduced infrastructure costs through serverless, consumption-based architecture

"We were looking for a solution to automate our daily routine operations, and Softellar provided us with a custom development service. The solution they provided was not only efficient and accurate, but also integrated seamlessly with our existing internal system."

Boris Godes

President, Grand Financial Inc

.NET, C#, Web API, React JS, Azure Blob Storage, Azure Durable Functions, Azure SQL Database, Azure CDN, and custom data integration tools