Java Projects For Insurance Domain
Member Enrollment and Eligibility System: Auto and Housing:
I'm working on the development of our Member Enrollment and Eligibility System, where customers interact with their insurance policies. =
Our functionality allows customers to manage their auto and home insurance policies seamlessly, from initial quote generation to policy modifications and claims processing.
When a customer initiates a quote, our system analyzes multiple risk factors including driving history, property location, and previous claims, then interfaces with various underwriting systems to generate accurate, real-time pricing.
We've implemented a sophisticated rules engine that handles complex scenarios like multi-policy discounts, good driver benefits, and dynamic risk assessment.
The system also includes an automated claims processing workflow where customers can report accidents, upload photos and documents, and track their claim status in real-time.
This has reduced claim processing time by 60% and significantly improved customer satisfaction.
From a technical perspective, we've built this using a microservices architecture with Java 17 and Spring Boot as our core backend, utilizing Spring Cloud for service communication, and Kafka for event-driven processing.
The system processes thousands of transactions daily, managing everything from policy updates to payment processing through a highly available infrastructure.
For data persistence, we're using Oracle for transactional data and MongoDB for document management, with Redis handling our caching layer.
The frontend is built with React and Redux, providing a responsive interface for both customers and internal staff.
We've implemented real-time integration with external services like DMV for driver verification and property assessment databases, all while maintaining strict security protocols.
The entire system is deployed on AWS using Docker and Kubernetes for container orchestration, with comprehensive monitoring through ELK stack and Prometheus.
Our automated testing suite using JUnit and Mockito ensures 99.99% uptime, while GraphQL APIs and RabbitMQ handle efficient data fetching and asynchronous processing, resulting in sub-second response times for most customer interactions.
Health Insurance Enrollment and Claims Management System:
I'm working on the Health Insurance Enrollment and Claims Management System that helps members access and manage their healthcare benefits.
The system lets members navigate health insurance options during open enrollment and manage their ongoing healthcare needs.
When members start enrollment, our system analyzes their healthcare needs by looking at their preferred providers, medications, and expected medical procedures to match them with suitable plan options.
We built a recommendation engine that considers family size, medical history, and budget to suggest coverage options that fit each member.
The system includes provider network checking, drug coverage verification, and telehealth scheduling.
This has helped reduce enrollment issues and plan changes after enrollment.
In my role, I work with core business data including member demographics, health plan details, provider networks, claims data, and clinical information.
We handle sensitive data like medical history, prescription records, and payment information.
The system processes enrollment applications, benefit verification requests, claims submissions, and provider credentialing data.
We maintain databases of insurance plans, coverage rules, network providers, and pricing structures.
On the technical side, we use Java 17 and Spring Boot for our microservices, with Spring Cloud handling service communication.
Kafka manages our real-time event processing for enrollment and claims. We store member data in Oracle and clinical documents in MongoDB, using Redis to cache frequently accessed benefit information.
The front end uses React and Redux, making it easy for members and providers to use. We connect with hospital systems, pharmacy managers, and Medicare/Medicaid using HL7 FHIR standards.
The system runs on AWS with Docker and Kubernetes for scaling during busy enrollment periods.
We monitor everything using ELK stack and Prometheus, and test with JUnit and Mockito. GraphQL APIs and RabbitMQ handle our asynchronous processing, which keeps our benefit verification quick and responsive.
The whole system follows HIPAA compliance rules for protecting healthcare data.
Provider Network Management System:
I'm working on our Provider Network Management System, which helps insurance companies handle their healthcare provider networks.
The system manages relationships between insurance companies, healthcare providers, and members. Insurance companies use it for provider onboarding, checking credentials, and managing contracts.
Healthcare providers can easily enroll, update their credentials, and track their contract status. Members can find accurate provider directories to choose their healthcare providers.
We handle different types of providers - from individual doctors to large hospitals - and keep track of how they're connected.
The system includes workflows for checking provider credentials, monitoring licenses, and looking for any sanctions.
Our contract management part handles payment rates, fee schedules, and payment terms, keeping track of changes and updates.
For the technical part, we've built this using microservices with Java 11 and Spring Boot. We use Spring Security to control who can access what, and Spring Cloud helps our services work together.
Our data is stored in PostgreSQL for regular transactions and MongoDB for documents like provider credentials and contracts.
We added Azure Cognitive Search so users can easily find providers using different search criteria. The frontend uses Angular with Angular Material components.
We connect to outside credentialing services through REST APIs, and our internal services communicate using IBM MQ. We also use GraphQL for provider directory searches where users need different types of information.
Everything runs in Docker containers managed by Kubernetes on Azure Cloud, and we monitor it all with Application Insights and Azure Monitor.
We test our code with TestNG and Mockito, and use Azure DevOps for our development pipeline. Since we're handling healthcare data, we follow HIPAA rules and keep everything secure using Azure Key Vault.
We work with lots of different data - providing information, credentials, contracts, member data, and network relationships. We handle sensitive information like provider licenses, background checks, and payment terms.
The system processes credential verifications, contract updates, directory searches, and member inquiries.
We maintain records of provider specialties, locations, network affiliations, and contract histories.
Premium Billing and Payment System:
I work on our Premium Billing and Payment System for insurance carriers, which handles our insurance financial operations. The system manages premium collections, billing cycles, and payment reconciliation.
We process billing for auto, home, and life insurance policies, each having different billing rules and schedules.
Our platform supports various payment timeframes - monthly, quarterly, and annual - and accepts payments through ACH, credit cards, and digital wallets.
The system calculates adjusted premiums when policies change mid-term, applies relevant discounts and surcharges, and sets up automated installment schedules.
Insurance carriers can see payment statuses in real-time, while policyholders use a payment portal to manage their payments and get reminders.
We built this using Java 11 with Spring Boot as our main framework. The system uses Spring MVC for REST endpoints and RabbitMQ to handle message processing between services.
We store our main transaction data in Oracle and keep payment history and audit logs in MongoDB. The frontend runs on React JS with Redux managing the state, making it easy for administrators and policyholders to use.
We added GraphQL APIs for flexible queries, especially for checking payment history and billing status. Everything runs in Docker containers managed by Kubernetes on GCP, and we use Cloud Spanner for handling distributed transactions.
We connect to different payment gateways through REST APIs and use Resilience4j for circuit breakers to handle failures gracefully.
We test our code with JUnit and Mockito, and use Selenium for end-to-end testing.
Some of our middleware services, particularly for payment gateway connections, use Node.js. We monitor everything with Prometheus and Grafana and log through Stack Driver.
For security, we use Spring Security with OAuth2 for authentication, and GCP KMS encrypts sensitive data.
The system works with various types of data including policy information, premium calculations, payment records, and billing schedules.
We handle sensitive data like bank account details, credit card information, and payment histories.
The system processes premium calculations, payment transactions, refunds, and reconciliation data.
Pharmacy Benefits Management:
I work on a Pharmacy Benefits Management System that handles prescription processing and formulary management for insurance providers and pharmacy networks.
The system manages drug formularies, prescription claims, and pharmacy network relationships. We handle drug pricing calculations considering pharmacy contracts, member benefits, and drug tier classifications.
Our platform processes prescription claims as they come in, checking drug interactions, dosages, and coverage.
Insurance providers use our tools to maintain their preferred drug lists, set pricing tiers, and manage authorization rules. Pharmacies can process claims instantly, handle refills automatically, and check coverage right away.
Members can see their prescription history, check drug prices, and find nearby network pharmacies.
We work with different types of data - drug information (NDC codes, therapeutic classes, dosage forms), member information (benefits, coverage, prescription history), pharmacy network details (contracts, fees, reimbursement rates), and formulary data (drug tiers, authorization rules, step therapy).
We also manage clinical data for checking drug interactions, including contraindications, allergies, and drug-disease interactions. Our system keeps track of pricing data like wholesale costs, average prices, and pharmacy contract rates.
On the technical side, we built this using Java 17 with Spring Boot. We use Spring Cloud to help our services find each other and manage settings.
Our data lives in PostgreSQL for transactions and MongoDB for drug and clinical information. Apache Kafka handles our real-time prescription claims and event processing.
We built the frontend with Angular for benefit administrators, pharmacists, and members to use. Redis helps us quickly check drug interactions by caching clinical data.
We connect to pharmacy systems through REST APIs and GraphQL. Everything runs on AWS EKS in containers managed by Kubernetes.
We monitor our system with Prometheus and use the ELK stack to collect logs. AWS IAM and KMS handle security and encryption.
We test thoroughly using JUnit for unit tests, Cucumber for behavior testing, and Postman for API testing.
Since we're dealing with healthcare data, we follow HIPAA rules with encryption and detailed audit logging.
The system processes millions of prescriptions daily, managing complex pricing rules and ensuring safe medication dispensing while maintaining high availability and quick response times.
Customer Self-Service Portal project:
We built an online portal where insurance customers can handle all their insurance needs without calling an agent. Think of it like online banking, but for insurance.
Customers log in and see all their policies in one place - their car insurance, home insurance, everything.
They can make changes to their personal information, like updating their address or phone number, and download their insurance cards right from their phone or computer.
The payment part was crucial - customers can pay their bills, set up automatic payments, and see their payment history.
If they get into an accident or have property damage, they can start a claim right through the portal, upload photos or documents, and track how their claim is progressing.
They can even get quotes for new policies or make changes to existing ones, like adding a new car or updating their coverage.
Behind the scenes, we used Java and Spring Boot to build the core system, with Angular for the customer-facing website.
We stored different types of data in different places - Oracle database for all the important policy and payment information, MongoDB for keeping track of customer activities and documents, and Redis to make everything run faster.
We hosted everything on Azure cloud services to keep it reliable and secure.
The system connects with lots of other insurance systems - like our payment processing system, the claims department's software, and our document generation system.
When customers make changes or submit claims, the information automatically goes to the right place and the right people.
This portal really helped both customers and the company. Customers could handle their insurance needs any time without waiting on the phone, and the insurance company saved money by reducing call center traffic.
The agents could focus on helping customers with more complex needs instead of routine tasks.
We made sure everything was secure and tested thoroughly since we were handling sensitive customer information and financial transactions.
Digital workspace for our insurance agents:
We built a comprehensive digital workspace for our insurance agents that completely transformed how they handle their daily work.
Think of it as their command center - where they can manage all their clients, policies, and sales activities in one place.
When agents log in, they immediately see their dashboard with important updates like pending policy renewals, client requests, and their sales targets.
They can quickly search for any client and see their complete profile, including all policies, claims history, and communication records. One of the most impactful features we implemented was real-time quote generation.
Agents can sit with clients (either in person or virtually) and show them different coverage options and prices instantly.
We used GraphQL for this because it lets agents pull exactly the information they need without overloading the system - much more efficient than our old REST APIs.
For example, if they're just checking basic policy details, they don't need to load all the claims history and documentation.
The technical side was interesting - we built the backend with Spring Boot, which handled all our business logic and security requirements. The frontend uses React, which gives agents a smooth, app-like experience.
We chose PostgreSQL for our database because we needed robust transaction support for handling policy changes and updates.
Redis handles our session management and caches frequently accessed data, which really improved response times - agents don't have to wait for screens to load when switching between clients.
We integrated AWS Lambda for generating policy documents and quotes on demand. When an agent needs to create a policy document, Lambda spins up, generates the PDF with all the correct client information and policy details, and delivers it back to the agent within seconds.
For security, we implemented AWS Cognito for authentication, which gives us strong identity management and lets us easily handle things like password resets and multi-factor authentication.
The portal has really streamlined our agents' workflow - what used to take multiple systems and phone calls can now be done in a few clicks.
Plus, it's given us better insights into our sales process since we can track everything happening in the system.
The agents particularly love the automated task reminders and the ability to schedule follow-ups with clients directly from the portal.
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