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 touchTech stack automation expedites script development by 3x
Manufacturing
Tech stack automation expedites script development by 3x
Manual processes across the multi-technology stack were severely affecting the script development cycles in terms of time, effort and cost. Iris application agnostic Test Automation framework and DevOps integration helped the client reduce the script development time and cost significantly.
Client
A leading building supplies manufacturing company
Goal
To support 30+ applications stack for UI, E2E, APIs, performance, mobile automation along with DevOps pipeline integration
Tools and technologies
.NET Core, PeopleSoft, Salesforce, WMS, JavaScript, Angular, Foxpro, C#, Selenium, SpecFlow, RestSharp, Nunit, Mobile Center/Emulators, Allure, Jira, Azure Pipeline, GitHub
BUSINESS CHALLENGE
The client had technology stacks comprising of diverse technologies that were difficult to manage. Substantial manual effort and time were spent on integrating the checkpoints, elongating the development process. Validating end-to-end business flows across different applications was the prime challenge. Reporting processes were also scattered across the entire application stack, making it vulnerable.
SOLUTION
Iris developed a robust application agnostic Test Automation framework to support the client’s multiple-technology stacks. Following the Behavior-driven Development (BDD) approach to align the acceptance criteria with the stakeholders, we built business and application layers of the common utilities in the core framework. Our experts identified E2E business flows to validate the downstream impact of the change and automated the entire stack through the shift-left approach. Azure DevOps integration enabled a common dashboard for reporting. The client attained complete version control to track production health and enforce strong validations.
OUTCOMES
Iris Automation solution enabled the client to surpass several business goals. The key outcomes of the delivered solution included:
- ~65% Increase in automation coverage
- 100+ Pipelines for in-scope applications across multiple environments
- 3700+ Test Automation scripts execution per sprint cycle achieved across applications
- 3X Faster script development of behavior-driven test cases
- Multi-day manual test effort reduced to a few hours of automated regression
- 70% Reduction in effort
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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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Get in touchSFTR solution strengthened market leadership
Client
A leading provider of market data and trading services
Goal
Support complex regulatory reporting with automated solution
Tools and technologies
Java, Spring Boot, Apache Camel, CXF, Drools BRE, Oracle, JBoss Fuse, Elasticsearch, Git, Bitbucket, Sonar, Maven
BUSINESS CHALLENGE
SOLUTION
OUTCOMES
- Generating additional revenue from extending the new reporting services to 17 firms.
- Beating the industry benchmark (~91%), achieving a higher transaction acceptance rate (~97%), and match reconciliation at the trade repository.
- Supporting a high throughput of 6 million transactions per hour which is scalable up to 10 million.
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Get in touchCloud transformation increases business agility
Standards & Membership
Global Standards organization increases business agility
Existing applications supporting the business were built on monolith architecture with high technical debt. Iris transformed over 15 years old monolith applications into microservices with automated integration and cloud deployment to deliver faster MVPs.
Client
A non-profit global organization responsible for developing and maintaining standards, including barcodes with over 115 local member organizations and over 2 million user companies
Business Drivers
To deliver MVPs in shorter cycles, reduce Mean Time for Ticket Resolution (MTTR), and lower the total cost of ownership
Tools and technologies
C#/.NET Core, Python/DJango, NodeJS/Express, Azure WAF, Azure APIM, App Services, Azure Kubernetes Service, Azure Monitor, Application Insights
BUSINESS CHALLENGE
SOLUTION
Azure cloud offered some of the foundational features like container orchestration, app engine, integration, API gateway, monitoring and others, making cloud-specific modernization a natural choice.
Modernization strategy involved reverse engineering of on-premise applications, domain-specific grouping the product backlogs by, adopting domain-driven design, and using open source cloud-friendly software with CI/CD pipeline. We transformed the applications to a .NET core framework using cloud-native design principles on Azure cloud. The solution was developed using Azure App Services, front door and service bus following the agile development approach with two-week sprints.
OUTCOMES
Iris helped the client realize multiple business benefits, including higher agility, resiliency and cost-efficient IT operations. Key outcomes of this cloud modernization engagement are:
- Reduction in Mean Time for Ticket Resolution (MTTR) by 30%
- Increase in application and infrastructure uptime to 99.9%
- Real-time visibility of application and infra metrics
- Enabled bi-weekly MVP delivery
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Get in touchAnti-money laundering software saves $1M
Client
A top 5 global bank
Goal
Create a unified platform for anti-money laundering functions, analytics, and compliance implementations
Tools and technologies
Angular 5, Java, Open Shift, and DevOps
BUSINESS CHALLENGE
The client expanded its fraud and anti-money laundering (AML) monitoring functions, involving multiple lines of business and 15,000 employees. The scaled system led to the lack of standardization of frameworks and resultant adoption of disjointed, manual-intensive, and high-cost AML technology. The ongoing disconnect hindered the efforts of automating, consolidating; and implementing AML functions, enterprise analytics, and regulatory compliance efficiently throughout the organization.
SOLUTION
Iris optimized existing operations and technology investments by developing and implementing a unified point of access for the discrete AML functions, featuring micro-front-end architecture. Engineered to be horizontally scalable through containerization with common authentication and authorization gateways, the single user interface (UI) allows onboarding and control of multiple extended AML functions, including visualization of metrics.
OUTCOMES
- Hassle-free transition from multiple to a single UI
- Unified, streamlined user experiences with more effective sessions
- Creation of standardized deployment procedures for AML rules and applications
- Saving of nearly $1M on infrastructure costs
- Reduced infrastructure maintenance time
- Frictionless migration of applications to the cloud
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Get in touchReporting transformation with data science and AI
Client
One of the world's leading bank
Goal
Improve efficiency in disclosure and reporting
Tools and technologies
Python – SciPy, Pytesseract, NumPy, Statistics
BUSINESS CHALLENGE
The client relies upon a centralized operations team to produce monthly NAV (Net Asset Value) and other financial reports for its international hedge funds— from data contained in 2,300 separate monthly investment fund performance reports. With batch receipts of rarely consistent file formats – PDF, Excel, emails, and images— the process to read each report, capture key info, and, create and distribute new metrics using the bank’s traditional tools and systems was highly manual, time-consuming, error-prone, and costly.
SOLUTION
Iris developed a Data Science solution that rapidly and accurately extracts tabular data from thousands of variable file documents. Using a statistical, AI-based algorithm featuring unsupervised learning, it auto-detects, construes, and resolves issues for every data point, configuration, and value. Complex inputs are calculated, consolidated, and mapped as per predefined templates and downstream business needs, efficiently generating numerous, distinct, and required period-end financial disclosures.
OUTCOMES
- 90 - 95% reduction in operational efforts
- 99% accuracy in processing variable inputs
- Zero rework effort and cost
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