Platform transformation and multi-cloud integration improve multinational publishing company's order management, time-to-market and performance.
Client
Multinational publishing, media, and educational company
Goal
Improve order management and transaction processing capabilities
Technology Tools
AWS EKS, Kong, Salesforce Commerce Cloud (SFCC), Salesforce CRM, Jenkins, Sumo Logic, Datadog
Business Challenge
The client's order management platform was complex and had scalability issues, causing poor customer experience and loss of revenue. The platform was hosted on Oracle cloud, with data stored in different repositories. Services were also hosted in the Oracle cloud, which used the BICC extract to fetch information about order details from Oracle databases. The low performance of customer-facing applications was causing latency and very high transaction processing time.
Solution
Team Iris transformed Oracle-based SOA services into six microservices and migrated them to AWS EKS for autoscaling with self-healing and monitoring capabilities.
We developed services for publishing data to Salesforce CRM for quick order processing and conversions. The BICC system for diversified information and order history was enabled with real-time integration between Oracle Fusion and materialized views for data consumption.
Post migration, these services were registered in Kong for discovery, and a CI/CD pipeline was created for deployment using Jenkins. Sumo Logic was used for monitoring the logs, and Datadog was used to observe latency, anomalies and other metrics.
Outcomes
The order management platform transformation delivered the following benefits to the client:
- System performance improved by 70%
- Transaction processing capability increased by 4x
- Order processing capabilities were enhanced by 200%
- Total cost of ownership (TCO) was reduced by 30%
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Custom analytics enable faster business decisions
Optimized data and on-demand analytics deliver faster business insights and better user experience for asset management firm
Client
U.S.-based asset management company
Goal
Streamline and improve data and analytics capabilities for enhanced user experiences
Technology Tools
Java, React JS, MS SQL Server, Spring Boot, GitHub, JenkinsBusiness Challenge
The client captures voluminous data from multiple internal and external sources. The absence of quick, on-demand capabilities for business users was inefficient in generating customized portfolio analytics on attributes such as average quality, yield to maturity, average coupon, etc.
The client teams were spending enormous amounts of manual effort and elapsed time (approximately 12-15 hours) to respond to requests for proposals from their respective clients.
Solution
Iris implemented a data acquisition and analytics system with pre-processing capabilities for grouping, classifying, and handling historical data.
A data dictionary was established for key concepts, such as asset classes and industry classifications, enabling end users to access data for analytical computation. The analytics engine was refactored, optimized, and integrated into the streamlined investment performance data infrastructure.
The team developed an interactive self-service capability, allowing business users to track data availability, perform advanced searches, generate custom analytics, visualize information, and utilize the insights for decision-making.
Outcomes
The solution brought several benefits to the client, including:
- Simplified data access to generate custom analytics for end users
- Eliminated manual processing and the need for complex queries
- Enhanced the stakeholder experience
- Reduced response time to client RFPs by over 50%
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Test Automation Speeds Model Risk Management System
Client
Top international bank
Goal
Fully automate the model risk management system framework to improve quality and confidence in testing results
Tools and technologies
Java, Selenium, Maven, TestNG, Git
BUSINESS CHALLENGE
The client's existing model risk framework was inefficiently handling functional testing aspects and risk scenarios due to lack of an end-to-end testing framework. Built on redundant, hard-to-debug, and non-scalable code, the system was unreliable for model risk testing. Test cases and controls were maintained and executed in Excel, eliminating parallel workflow abilities, tempering testing results, contributing to increased testing efforts and even delaying production launches in some cases. Scalability of testing using automation, running data-driven, end-to-end test flows, and restoring confidence in test results were the client's prime challenges.
SOLUTION
Iris built a lightweight and scalable new framework, providing 100% automated regression testing of functional test cases. Using simplified, customizable code that separated automation utilities and test functions, Iris' solution brought multiple improvements. Among them was faster test execution due to significantly reduced manual efforts. It also resulted in better quality and stability from the early identification of testing issues, enabling immediate corrective actions to occur. Another advantage of the solution was adaptability to multiple application areas due to ease of maintainability and traceability of code employed.
OUTCOMES
The client experienced several positive effects from the new, fully-automated solution:
- Acquired a 100% stable, scalable, reusable test framework
- ROI of 72%; payback period of less than 8 months
- 20% reduction in testing efforts for faster time to market
- Significant decrease in time required for ongoing maintenance of test scripts
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Get in touchData warehouse enhances client communications
Client
A U.S.-based investment bank
Goal
Improve data collation and information quality for enhanced marketing and client reporting functions
Tools and technologies
Composite C1, Oracle DB, PostgreSQL, Vermilion Reporting Suite, Python, MS SQL Server, React.js
BUSINESS CHALLENGE
The client’s existing investment data structure lacked a single source of truth for investment and performance data. The account management and marketing teams were making significant manual efforts to track portfolio performance, identify opportunities and ensure accurate client reporting. The time-consuming and manual processes of generating marketing exhibits and client reports were highly error-prone.
SOLUTION
Iris implemented a comprehensive investment data infrastructure for a single source of truth and improved reporting capabilities for marketing content and client report generation. An automated Quality Assurance process was instituted to validate the information in critical marketing materials, such as fact sheets, snapshots, sales kits, and flyers, against the respective data source systems. Retail and institutional portals were developed to provide a consolidated view of portfolios, with the ability to drill down to underlying assets, AUM (Assets Under Management) trends, incentives, commissions, and active opportunities.
OUTCOMES
The new data infrastructure delivered a holistic, on-demand view of investment details, including performance characteristics, breakdowns, attributions, and holdings, to the client's marketing team and account managers with:
- ~95% reduction in performance data and exhibit information discrepancies
- ~60% improvement in operational efficiency in core marketing and client reporting functions
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Get in touchBrokerage platform transformation improves UX
Client
A leading U.S. brokerage firm with $1+ trillion in assets and serving 6,000+ RIAs
Goal
Resolve online platform accessibility, functionality and timeliness issues
Tools and technologies
Angular 9, Jenkins, Pivotal Cloud Foundry, Oracle, Kubernetes, Spring, Docker
BUSINESS CHALLENGE
Client’s existing brokerage platform supporting over 6,000 Registered Investment Advisors (RIAs) and containing information about assets valued at more than $1 trillion had accessibility issues. The high cost of owning and maintaining outdated technologies and time-to-market for new features were adding to the business challenges.
SOLUTION
Iris transitioned the client’s monolith applications to microservices to transform the RIA platform. An open-source, cloud technical stack was leveraged to develop a single-page, micro-UI-based application. BFF (Backend for Frontend) design was applied, and Angular 9 was used to achieve superior compatibility on mobile devices. Widgets were introduced to enable seamless transitions within third-party applications. Consolidated user views were created to track assets and their performance for a unified experience for the RIAs.
OUTCOMES
- Fully functional mobile views
- 100+ integrated third-party applications
- Instant and seamless access to client accounts
- Downtime for hot deployments of fixes brought to zero
- Technical debt decreased by 45%
- Release timelines shortened by 80%
- Issue resolution time reduced by 90%
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Get in touchDigital ledger secures trading integrity
Client
Global bank's trading operations
Goal
Resolve trading transaction breaks and related regulatory issues through expandable intra-company digital ledger system
Tools and technologies
Hyperledger Fabric 1.4/2.2, Java 8, Go Language 1.8, Kafka, Node JS, Microservices, OpenShift, Dockers, Kubernetes
BUSINESS CHALLENGE
A highly-manual, paper-dependent, trading and reconciliation process was causing the accumulation of a large number of daily transaction liquidity breaks, which had been cited by federal regulators and risked a billion dollar cost impact. The lack of a robust trade audit and reconciliation process to reduce liquidity breaks and operating costs led the bank to seek an immutable system that could record and unify financial practices and be expanded to other transaction areas.
SOLUTION
Iris' solution comprised a production-ready, configurable platform using microservices and blockchain-based digital ledger architecture. It employed Smart Contracts coded with requisite business rules to facilitate front office trade booking and trade reconciliation processes. RPA was utilized to automate data mapping and testing of transactions. Preventive controls were enabled by recording intra-company transactions at their initiation using uniform booking practices, and consequently guaranteeing the term of the trade. A multi-layered infrastructure was created to support real-time, batch streaming of differing file formats. The UX was enriched through Interactive UI and automated workflows.
OUTCOMES
Iris successfully introduced a global intra-company distributed ledger and trade reconciliation system that did not exist before. With self-executing contracts matching both sides of transactions prior to feeding downstream systems, the platform ensures complete integrity at the source and reduces time and cost for all transactions. The solution also achieved:
- 30% fewer liquidity breaks
- 70% improvement in operational efficiency due to the use of RPA
- 60% reduction in business-rules configuration time, due to the smart contracts
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Get in touchSoftware transformation gets compliance for bank
Client
A global investment bank
Goal
To have a unified functional validation system for FDIC compliance
Tools and technologies
SQL Server, Sybase, Data Lake, UTM, .NET, DTA, Control-M, ALM, JIRA, Git, RLM, Nexus, Unix, WinSCP, Putty, Python, PyCharm, Confluence, Rabacus, SNS, and Datawatch
BUSINESS CHALLENGE
SOLUTION
OUTCOMES
- Faster and more efficient internal analysis with highly accurate QFC open positions
- 100% compliance with timing and format of required daily QFC report submissions to the FDIC
- Significant decrease in exceptions before the platform went go-live and zeroed critical defect delivery post-go-live
- An intuitive UI dashboard reflecting the real-time status of critical underlying data volumes, leakages, job run, and other stats
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Get in touchIT modernization lowers costs for capital markets
Client
A major financial institution
Goal
Re-engineer key compliance application for greater efficiency
Tools and technologies
Oracle 12c, 19c, Elastic, Java and Kafka
BUSINESS CHALLENGE
SOLUTION
OUTCOMES
The solution improved the user experience, turnarounds, data quality, deal compliance, and risk management processes while lowering the costs. Major impacts of the solution include:
- Reduced system issues by 93%, while 7% tackled subsequently
- Reduced enterprise-level license costs significantly
- Improved advanced search features
- Reduced costs of multiple searches per document by $200,000 per year
- Enabled views generation for info responses in less than 3 seconds
- Reduced system maintenance and development efforts by 20%
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Get in touchPlatform re-engineering for operational efficiency
Banking & Financial
Re-engineering data extraction platform for increased efficiency
A legacy data extraction platform was limiting business efficiency and transaction processing capabilities. Iris system modernization and platform re-engineering platform services advanced the operational efficiency manifold.
Client
One of the top 20 brokerage banks in North America
Goal
Modernize an existing, licensed data platform to meet the increasing volume of transactions and product offerings
Tools and technologies
Python, Core Java, Oracle, ETL Framework, Apache Zookeeper, Anaconda, Maven, Bamboo, Sonar, Bitbucket
BUSINESS CHALLENGE
SOLUTION
OUTCOMES
- Quicker, real-time configuration and execution of 500+ jobs for loading trade feed
- Zeroed downtime, even during the trade reference data changes
- 15% faster onboarding of the new feed or data source
- Nearly 20% faster throughput for various critical feeds with parallel processing feature
- Reduced anomalies and duplication with improved consistency
- 35-40% savings in annual third-party platform/ module license fees.
- Standardized and streamlined onboarding processes and turnaround time, scaling the operations efficiencies
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Get in touchIT modernization boosts Insurance customer base
Insurance
IT modernization boosts Insurance customer base
Existing applications and business systems of a Fortune 500 Insurance Carrier were inadequate to meet customer expectations. Iris business systems transformation solution enabled the client to deliver a consistent customer experience, improving acquisition and retention significantly.
Client
A leading American Fortune 500 Insurance Services Provider, offering insurance, investment management and other financial products and services across the Americas and 40 other countries
Business Drivers
To advance business agility and customer experience through modernized business systems
Technologies and Frameworks
C#/.NET, JAVA, DevOps, Python, NodeJS, App Services, Managed Application Support
BUSINESS CHALLENGE
SOLUTION
OUTCOMES
- Infrastructure availability increased to 99%
- Optimized maintainability reduced the KYC process time by 75%
- Customer response time cut down by around 40%
- Promoter score incremented from 5 to 9 out of 10
- Customer retention improved by nearly 80%
- Customer acquisition increased by 65%
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