The Evolution of Hybrid DLT: From Permissioned Ledgers to Public Networks

Discover how hybrid distributed ledger architecture enables financial institutions to balance privacy, compliance, interoperability, and liquidity by combining the strengths of permissioned and public blockchain networks.

Financial institutions are accelerating their digital asset and blockchain initiatives but choosing between public and private distributed ledger technologies (DLTs) remains a significant challenge. While public networks offer transparency, interoperability, and access to global liquidity, they often fall short of institutional requirements for privacy, governance, and regulatory compliance. Permissioned DLTs address these concerns but can limit interoperability and market reach.

Hybrid DLT architecture is emerging as the next stage in distributed ledger evolution by combining the strengths of both models. Sensitive business processes, governance, and regulatory controls remain within permissioned environments, while public blockchain networks enable secure settlement, broader market access, tokenized asset distribution, and programmable financial services. This approach allows organizations to unlock innovation without compromising security or compliance.

Successfully implementing a hybrid architecture requires more than connecting two networks. Organizations must carefully address governance, identity management, interoperability, cross-chain communication, custody, regulatory alignment, cybersecurity, and enterprise integration. Architectural decisions around asset lifecycle management, smart contracts, cross-chain bridges, and compliance frameworks play a critical role in ensuring secure and scalable deployments.

Leading financial institutions are already demonstrating how hybrid DLT can support tokenized assets, improve operational efficiency, expand liquidity, and bridge traditional finance with decentralized finance. As regulatory frameworks continue to mature, hybrid architectures are expected to become the preferred foundation for enterprise blockchain adoption.

Read our perspective paper to explore the evolution of hybrid DLT, understand the key architectural considerations for successful implementation, and learn how financial institutions can build secure, compliant, and future-ready digital asset ecosystems.

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Agentic AI Framework Operational Risk Commercial Corporate Banking

Agentic AI Reduces Risk in Commercial Banking

Strengthen operational resilience by embedding AI-driven intelligence, governance, and human oversight into commercial and corporate banking workflows.

An Agentic AI framework introduces intelligent AI agents that continuously monitor operational workflows, detect anomalies, recommend policy-aligned actions, and support decision-making within clearly defined governance boundaries. By combining contextual intelligence with human oversight, banks can improve operational efficiency, strengthen risk management, and maintain transparency, accountability, and regulatory confidence.

The framework also enables organizations to capture and institutionalize expert knowledge through a Human-in-the-Loop (HITL) approach. As business and risk professionals review exceptions, interpret policies, and make critical decisions, the platform continuously learns from these interactions. This evolving decision intelligence improves the accuracy, consistency, and policy alignment of future recommendations while ensuring that high-impact decisions remain under human oversight.

From operational process monitoring and credit risk support to documentation automation and loan servicing, Agentic AI enables commercial and corporate banks to embed intelligence directly into operational workflows. The result is faster decision-making, improved compliance, enhanced operational efficiency, and greater organizational resilience.

Read our perspective paper to discover how an Agentic AI framework helps commercial and corporate banks transition from reactive operational risk management to proactive, AI-powered operational intelligence.

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Reuters – The Future of Insurance 2026

Reuters – The Future of Insurance

Connect with Venkat Laksh, our Head of Insurance IT Sales, at the 2026 FOI forum to learn how insurers are fusing advanced, AI-driven technologies and other enterprise growth areas.

Reuters Events hosts this year’s Future of Insurance (FOI) forum on June 25-26, 2026, at the Marriott Marquis Hotel in Chicago, Illinois. FOI is a premier North American industry event where more than 500 insurance leaders come together to discuss and align key topic areas of technology, products, customers and risk. The primary themes of this year’s FOI sessions are turning strategy into growth, building the digital backbone, elevating customer experience, and ensuring risk readiness.

Iris provides Insurtech services to leading insurers, in property, casualty, specialty, life and annuity, and other sectors, that result in measurable positive outcomes in these areas. Venkat Laksh, our Head of Insurance IT Sales, is attending FOI 2026 to share Iris client success stories and the value derived from our advanced AI-powered capabilities, domain expertise, and collaborative, client-centric approach. Learn from Venkat how partnering with Iris and applying our solutions in Agentic and Generative AI/ML, Application Engineering and Modernization, Cloud and Data Engineering, can advance the digital transformation and strategic growth goals of your enterprise.

You also can contact our InsurTech team, including Abhineet Jha, Head of Insurance IT Services, and Client Partners Glenn DeGeorge, Parijat Sharma, and Vaibhav Brajesh and Delivery Partner, Mayank Khanna, to discuss your technology objectives.

Learn more about our Insurance Technology Services and Generative AI Experience.

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Unified platform automates investment deal data

Automation Data Analytics Integrations

INSURANCE

Unified platform automates investment deal data

Self-service web portal built with API integration replaces legacy SharePoint system, delivers improved UX, cost-efficiency, and real-time reporting for teams managing deals and issuer data.

Client

Large NY-based insurance and investment company

Goal

Develop a modern, scalable system to manage deal and issuer data efficiently while eliminating legacy costs and inefficiencies

Tools and Technologies

.Net Core 6(API) , Background Service, Angular 14, SQL Server

Business Challenge

The client’s SharePoint-based system for managing deal and issuer details faced major limitations. As data volume and user count increased, the platform became slow, difficult to customize, and expensive to maintain. Integration with other critical tools was limited, reducing efficiency and scalability. These constraints created risks to effective deal management and hindered the ability to scale operations.

Solution

Built a modern web-based system using Angular (front-end), .NET Core (back-end), and SQL Server (data storage)
Developed a self-service portal for internal teams to easily manage deal and issuer data
Automated data ingestion, cleaning, and storage with a background service for accuracy and consistency
Integrated Splunk and Application Insights to enable real-time monitoring of system health and performance

Outcomes

Substantial cost savings by eliminating SharePoint licensing and maintenance expenses
Improved performance and scalability with faster system response and ability to support more users
Enhanced user experience through a modern, intuitive, and efficient interface
Increased automation, reducing manual tasks and errors while saving time
Real-time reporting and accurate deal projections for better decision-making

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