Seamless integration of a self-service portal with FINEOS AdminSuite improved scalability, reduced processing time, and enhanced user experience.
Client
A leading insurance provider specializing in absence management solutions
Goal
Migrate data and services from a legacy platform to FINEOS while ensuring a seamless user experience and improved system reliability
Tools and Technologies
Spring Boot, APIGEE, FINEOS AdminSuite, Splunk
Business Challenge
The client aimed to migrate data and services from its legacy Group Benefits Platform Transformation (GPT) system to FINEOS AdminSuite while maintaining a consistent user interface, improving data accuracy, and ensuring minimal downtime.
The system also required enhanced automation and monitoring to streamline absence creation for agents and employees.
Solution
- Developed APIs to integrate the legacy system with FINEOS AdminSuite for seamless absence management
- Designed an interactive self-service portal, allowing users to efficiently manage absences
- Used Spring Boot for service development and APIGEE for API integration
- Implemented Splunk for real-time monitoring and log analysis to enhance system reliability
Outcomes
- Increased system scalability, reliability, and data accuracy
- Enhanced user experience with a modern, intuitive interface
- Reduced time taken to create absences, improving efficiency for agents and employees
- Faster development cycles and better monitoring, ensuring proactive issue resolution
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Streamlining policy administration with low-code development
Seamless low-code development on AWS accelerated go-to-market for policy issuance, partner integration, and agent onboarding.
Client
A leading home insurance enterprise specializing in policy administration solutions
Goal
Develop policy administration applications for partner insurance carriers with seamless third-party and home-grown app integration
Tools and Technologies
Low-Code/No-Code Platform, AWS, Agile Development, ContainerizationBusiness Challenge
The client needed a scalable policy administration solution to support insurance carriers, integrate third-party applications, and enhance policy issuance and settlement.
The goal was to accelerate the go-to-market process for partners and agents while delivering premier services for competitive pricing and superior policy coverage.
Solution
- Designed and developed a policy administration platform using a Low-Code/No-Code application development platform on AWS
- Built three Agile Pod-based teams, each containing five members for rapid iteration and development
- Leveraged containerized development, ensuring each service had its own lifecycle for enhanced flexibility and scalability
- Established weekly release plans with feature flags to enable controlled functionality deployment in production once the business was ready to adopt
Outcomes
- 200% growth in policy issuance
- Faster onboarding for agencies and agents
- Improved efficiency and scalability in policy administration
- Accelerated go-to-market for insurance partners and agents
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InsurTech NY 2025 Spring Conference
Meet our team at InsurTech NY 2025 Spring Conference
Connect with Ravi Chodagam, Vice President, Venkat Laksh and Abhineet Jha, Senior Client Partners, at InsurTech NY’s annual forum to discuss next-gen technology solutions for insurers.
The annual InsurTech NY Spring Conference is April 2-3, 2025, at Chelsea Piers in New York City. The theme of this year’s forum is InsurTech is the New R&D. The event brings together 900+ leaders and innovators in the industry, including carriers and brokers of life, health and disability, property and casualty (P&C), and specialty insurance; investors; and insurtech service providers like Iris Software. Each year, speakers and attendees focus on the technology and business management solutions that will enhance the operations, customer experience, and revenue streams of insurers.
Meet the leaders of our global InsurTech team - Ravi Chodagam, Vice President, Venkat Laksh and Abhineet Jha, Senior Client Partners - at InsurTech NY’s 2025 Spring Conference. As an integral and long-time technology partner to many top life, P&C, and specialty insurers, Iris has vast experience implementing agile and advanced technology and data solutions that ensure clients stay competitive and ahead of rapidly evolving trends in the dynamic insurance industry.
Discuss your tech priorities with Ravi, Venkat and Abhineet at the Spring Conference, or anytime, and learn how leading insurers apply our solutions in AI and Generative AI, Application Modernization, Automation, Cloud, and Data Science & Analytics to ensure their enterprises are future-ready, scalable, secure, cost-efficient, and compliant. You can also contact the team and learn more about our InsurTech Services here: Insurance Technology Services | Iris Software.
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Leveraging Generative AI for asset tokenization
Enhance efficiency, security, and user experience by leveraging Generative AI in DLT-based asset tokenization.
Asset tokenization is converting ownership rights of an asset that has traditionally resided within legacy or traditional systems into a digital token on a Distributed Ledger Technology (DLT) platform. This transformation enables numerous benefits, including fractional ownership, 24/7 availability, easier transferability, and enhanced liquidity.
Developing and deploying a comprehensive asset tokenization system on DLT is a full-scale software development endeavor encompassing all SDLC phases. Every phase presents challenges, including technology complexities, evolving business use cases, non-standardization, scarcity of resources, and reluctance to adopt.
As asset tokenization emerges as an essential solution for financial institutions, the integration of Gen AI amplifies customer value. Institutions can achieve unprecedented efficiency, accuracy, and innovation by leveraging Gen AI's capabilities throughout the asset tokenization process.
Gen AI is set to play a pivotal role in improving asset tokenization by contributing to the different phases of its implementation. Gen AI can assist both in the implementation phase and beforehand, as it can help produce synthetic financial data that closely resembles real market conditions conduct stress tests and other simulations, helping to strengthen the platform.
Read our Perspective Paper for more insights into the key phases, benefits and the road map to asset tokenization.
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Get in touchData migration to cloud expedites credit risk functions
Migrating on-premises models and data to the cloud enhances financial forecasting, sensitivity analysis, and time-to-market.
Client
A leading North American bank
Goal
Migrate credit risk data and SAS-based analytics models from on-premises data warehouse to AWS to enhance functionality
Tools and Technologies
AWS Glue, Redshift, DataSync, Athena, CloudWatch, SageMaker; Apache Airflow; Delta Lake; Power BIBusiness Challenge
The credit risk unit of a major bank aimed to migrate SAS-based analytics models containing data for financial forecasting and sensitivity analysis to Amazon SageMaker.
This was to leverage benefits such as enhanced scalability, improved maintenance for MLOps engineers, and better developer experience. It also sought to migrate credit risk data from a Netezza-based on-premises data warehouse to AWS, utilizing a data lake on AWS S3 and a data warehouse on Redshift to support model migration.
Solution
- Decoupled data workload processing from relational systems using the phased approach with a focus on historical migration, transformational complexities, data volumes, and ingestion frequencies of the incremental loads
- Developed a flexible ETL framework using DataSync for extracting data to AWS as flat files from Netezza
- Transformed data in S3 layers using Glue ETL and moved it to the Redshift data warehouse
- Enabled Glue integration with Delta Lake for incremental data workloads
- Built ETL workflows using Step Functions during orchestration and concurrent runs of the workflow; orchestrated the concurrent runs of workflows using Apache Airflow
- Architected data shift from Netezza to AWS, leveraging a flexible ETL framework
Outcomes
- Enhanced financial forecasting and sensitivity analysis operations with analytical models and data migrated to the AWS public cloud
- Expedited time-to-market catering to client’s downstream consumption needs through Power BI and Amazon SageMaker
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Generative AI platform for business use cases
Banking & Financial Services
Gen AI platform offers future-ready capabilities
Intuitive Generative AI platform provides AI, integration, and end-use capabilities and forward-looking roadmaps for the risk teams and business users at a leading bank.
Client
A leading North American bank
Goal
Provide a wide range of AI capabilities for various risk and business teams and avoid building fragmented, outdated systems
Tools and Technologies
Amazon Bedrock and Titan V2, pgvector, Faiss, OpenSearch, Llama 7B, Claude Sonnet 3.5 and 3.7Business Challenge
The Enterprise Risk function at a leading North American bank initiated a Generative AI (Gen AI) solution to offer a wide range of AI capabilities, including document intelligence, summarization, generation, translation, and more.
As the project evolved through proofs of concept and pilots, a key challenge emerged: the risk of creating a fragmented ecosystem with an overwhelming array of unmanageable bespoke solutions, model integrations, and reliance on potentially outdated models and libraries.
Solution
Based on prior engagements across clients, our team delivered thought leadership around how to develop and deliver capabilities using a platform approach. We also set up a Minimum Viable Product Team to iterate on new problem areas and solution approaches. Platform development includes generalized capabilities for:
- Setting up document ingestion pipelines, with choice of parsing approaches, embedding models and vector index stores
- A factory model along with configurations for integrating new parsers, embedding models, LLM interfaces etc., to quickly bring new capabilities to the platform
- User management, SSO integration, entitlements management
- API integration to bring in information/ data from internal and external sources
- Platform support of pgvector, Faiss, OpenSearch, Amazon Titan V2, Llama 7B, Claude Sonnet 3.5, and 3.7, etc.
- Intuitive chat interface for AI Masters - designated business users trained in Prompt Engineering and other techniques to assemble new AI/Gen AI capabilities for users through configuration - and end users
Outcomes
- A future-ready Gen AI platform that can easily incorporate new capabilities and updates
- Multiple specific capabilities, called skills, for use by various risk teams and business users
- A forward-looking roadmap, including ability to compose more complex capabilities using atomic capabilities
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Join us at Reuters Pharma USA 2025
Join us at the Reuters Pharma USA 2025 Conference
Meet Swarnendu Banerjee, Client Partner – Life Sciences, at North America’s largest cross-functional pharmaceutical forum and learn how our advanced technology solutions benefit this dynamic sector.
Reuters Pharma USA 2025 Conference, noted as North America’s largest cross-functional pharmaceutical gathering, is scheduled between March 18-19, 2025, at the Pennsylvania Convention Center in Philadelphia. With the pharmaceutical industry continually pressured by shifts in market trends and participants, product development, consumer sentiment, and government regulations, attendees and speakers at this Conference will be seeking and sharing insights and strategies to best navigate change, remain competitive, and future-proof operational units as well as global enterprises.
Swarnendu Banerjee, client partner and seasoned IT professional for the pharmaceutical and life sciences sectors, will be attending the Reuters Pharma USA 2025 Conference. He will share Iris’ extensive experience in these domains. How our advanced capabilities in AI/Generative AI, Application Development, Intelligent Automation, Cloud, Data & Analytics, Integrations, and Quality Engineering have delivered successful outcomes in mission-critical engagements, ensuring quality and compliance, reducing costs, enhancing UX, modernizing, migrating, scaling, accelerating, and streamlining.
Connect with Swarnendu at the Reuters Pharma forum or anytime, or visit our Services and Life Sciences capabilities pages to explore our innovative approach and strategies for end-to-end digital transformation.
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Get in touchTransforming payment processing for banking channels
Streamlined payments architecture delivers flexible workflow orchestration, system scalability, and improved data reporting.
Client
A leading Australian bank
Goal
Streamline the payment transaction lifecycle to handle increasing volume and complexity
Tools and Technologies
Jenkins, Kubernetes, Spring, Oracle, PostgresSQL, AWS, Docker, Kafka, JavaBusiness Challenge
Multiple banking channels - mobile, internet and branch - initiate various payment requests (20+ types such as ACH, mandate and book transfer) that need to be processed. Depending on the payment type, the channel was required to invoke one or more services in a specific order as per the associated business rules.
Changes to these payment workflows stemming from introduction of new payment types or revisions of business rules introduced complex and repeated changes to the bank’s systems, hindering scalability.
Solution
- To support lifecycle management of various payment transactions, including defining different payment workflows, we designed an event-driven architecture comprised of 40+ microservices (e.g., limit, eligibility, and fraud checks, etc.) supported by a Kafka message queuing system
- The architecture involved building an orchestration engine (landing service), acting as a front controller for all payment workflow requests from the various banking channels, such as mobile, internet and branch
- The landing service in turn invokes the corresponding service (limit, eligibility, etc.) based on the payment type and business rules associated with it
- Data flow between these microservices (resulting from further invocations) and other downstream systems is facilitated asynchronously with the help of a distributed messaging system (Kafka)
- Using Jenkins, we built a CI/CD pipeline to streamline the workflow by automatically building, testing and deploying code changes as they are committed
Outcomes
- Significantly eased the management of payment workflows, including those related to the addition of new payment types (resulting from an acquisition)
- Enabled systems to scale without introducing complex changes at the channels
- Improved reporting, resulting from faster access to data through dedicated microservices
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Seamless 24/7 Operations with App Management
Holistic administration of diverse tech stack achieves 24/7 business continuity, 25% more system uptime, and 99% SLA compliance while adapting to dynamic demand.
Client
A leading manufacturer of roofing materials
Goal
Achieve seamless, 24/7 operations with >95% SLA compliance while efficiently managing diverse technology platforms.
Tools and Technologies
.NET Azure applications and services, Sitecore, MuleSoft, Google Cloud Platform (GCP), PeopleSoft, SalesforceBusiness Challenge
Ensuring uninterrupted 24/7 business operations involves supporting and maintaining critical applications across diverse technology stacks. This includes achieving near-perfect Service Level Agreement (SLA) compliance by consistently delivering response and service levels exceeding 95%.
Managing a complex technology ecosystem spanning platforms like .NET, Azure, Salesforce, Sitecore, MuleSoft, GCP, and PeopleSoft, requires expertise and coordination. Additionally, the roofing industry's seasonal nature and frequent deployments lead to unforeseen spikes in incidents and requests, demanding dynamic resource allocation and effective load-management strategies to efficiently meet unpredictable demand.
Solution
- Cross-training of an agile team on all platforms, enabling them to handle spikes without SLA impact, shifting focus dynamically
- Proactive use of monitoring tools and automation, which reduced incidents and resolution time by addressing issues early
- A Gen AI-powered knowledge base documented resolutions, enabling faster, accurate incident handling
- Ensured seamless communication across platform systems, like Salesforce and PeopleSoft, for quick integration fixes
- Regular customer feedback loops and monthly reports aligned system performance with business needs, highlighting insights and improvements
Outcomes
- Near-perfect SLA adherence at 99.9%, ensuring minimal business disruption on an ongoing basis
- Managed 1,100+ incidents per month with a decrease in resolution times stemming from proactive monitoring and streamlined processes
- 25% uptime improvement from proactive maintenance, ensuring high application availability and minimal downtown
- 24/7 load handling that effectively managed spikes during demand surges, maintaining SLAs without extra resources
- Continuous optimization from regular RCAs (Root Cause Analyses) and process enhancements, which reduced incidents and improved system efficiency
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Modernized Payments Hub Improves UX and Compliance
Modernized core payments engine elevates client experience through seamless integration and increased functionality.
Client
U.S. operations of a leading Japanese bank
Goal
Modernize payments architecture to streamline processing and improve client experience
Tools and Technologies
Jenkins, Kafka, Spring, Oracle, JBoss, React, Elastic Search, Java, Node.jsBusiness Challenge
The evolving payments landscape, with the introduction of ISO 20022 and the dynamic nature of the regulatory environment, necessitated advancement in the bank’s payment processing capabilities.
The lack of a modern architecture hindered client experience, with multiple channels initiating various payment types that required complex processing.
Solution
Our team built a centralized payments hub to orchestrate data flows between payment initiation systems and product processors. The steps:
- Designed a flexible and scalable microservices-based architecture to facilitate translation, enrichment and processing of payment transactions
- Built a messaging layer to streamline data flows between systems, through support for various modes of interaction, e.g., MQ, API and file (canonical / industry standards such as NACHA, SWIFT, JSON, etc.)
- Introduced an API gateway to handle multiple payment types to enable channel agnostic payment capabilities
- Deployed a modular approach to support existing and new systems with isolation of core and product processors and avoid redundancies in capability builds
- Developed a React-based UI as the touchpoint for integrations between the payments hub and other systems
Outcomes
- A core payments engine capable of seamlessly integrating with multiple, complex systems
- Superior client experience, resulting from a holistic view spanning initiation, payment rails, and clearing
- A modernized payments platform that is ISO 20022-compliant and future-ready for processing and reporting needs
- Faster implementation of functionalities for payment processors
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