SFTR solution strengthened market leadership

Risk & Compliance

Securities financing transactions regulation compliance made easy

A global market data and trading services provider strengthens its EU market leadership with a regulatory solution by supporting a throughput of 6 million transactions per hour.

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

The client offers an automated, integrated solution to its clients in the European Union (EU) for complying with the Securities Financing Transactions Regulation (SFTR).

Effective in recent years, SFTR requires timely and detailed reporting based on multitudes of data, systems, collateral, and lifecycle events. The voluminous data is captured from hundreds of millions of daily transactions made to multiple trade repositories registered by the European Securities and Markets Authorities (ESMA).

Non-compliance at any stage is risky, potentially very costly, for all trade counterparties, i.e., broker-dealers, banks, asset managers, institutional investors.

Solution

Experienced in diverse technologies, big data, and capital markets, team Iris developed a streamlined, end-to-end data reporting platform with complex trade matching and monitoring systems. Improving speed, accuracy, and flexibility, the new architecture supports high trade concurrency and acceptance rates with parallel processing of millions of transactions.

The delivered solution also enabled optimal load balancing and matched the reconciliation at the trade repository. Built with microservices to accommodate future scalability, standardization, data quality, and security requirements, the system implemented functional enhancements. A Unique Transaction Identifier (UTI) subsystem was also developed for sharing and matching counterparty transactions, enabling plug-and-play setup for new repositories, and supporting any changes in outbound or inbound data report formats required by ESMA or clients. Improved dashboards and search pages helped the end-users in better configuration and tracking of their transactions.

Outcomes

The nimble delivery and successful roll-out of the new SFTR platform delivered the desired strategic competitive advantage to the client for maintaining its EU market leader position. The consolidated solution also helped in:

  • 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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Accelerate your agile software development

Accelerate your agile software development

Businesses are increasingly using cloud technologies and service-oriented architectures to deliver their products and services on digital channels. They also want those IT solutions delivered increasingly faster. In order to meet those demands, IT has adopted Agile methodology to reduce time to develop new capabilities, apply fixes and deploy them to production.


    The nature of software development is transforming with more frequent releases and monolithic architecture giving way to services. Consequently, there is a greater need to ensure that overall quality does not degrade in terms of usability, reliability, scalability and performance. Clearly, as application architecture is being modernized and software is being deployed expeditiously, this method of testing will not empower IT to deliver effectively. Practical experience has given us some actionable insights to shift approaches to quality in an Agile development environment.

    Challenges

    We find organizations frequently face the following key challenges in transforming their approach to Quality Engineering in an increasingly Agile enterprise:

    Iris Solution

    Iris solution combines using Acceptance Test Driven Development (ATDD) methodology to bring in the culture of early acceptance with continuous testing from development to production. This approach leverages DevOps and incorporates In-sprint Test Automation to accelerate between transition from a QA to a QE mindset.  Our solution has a framework that enables these features: 
    • Integration with tools that allow for developing a common understanding of requirements and specifications within the team
    • Configuring a customer’s Agile development process (e.g., “Done” criteria) by integration with industry-standard tools that support code development, test scripts development and auto triggering of test execution, deployment and continuous monitoring
    • Libraries with templates for gathering requirements and pre-built code for test execution, deployment and reporting
    • A storehouse of reusable libraries that allow for quick access and updates of test scripts and easy integration of new components, thus reducing the maintenance burden
    • A cross-referenced checklist to mark completion of all user stories, which is one of the most critical checkpoints in an Agile project 
    • A machine learning layer with baseline objects to support features such as self-healing and test analytics reporting. Using this facility, an Agile project can support automatic fixing of test scripts and test execution predictability, thus reducing the time and cost of custom development 

    Iris Automation Practice: Focus Areas and Competencies

    Iris Automation Practice offers comprehensive services and solutions across competencies such as Intelligent Automation, Test Automation and DevOps Automation. Our approach introduces automation within the context of a function or industry to create seamless end-to-end processes and experiences. Our services, strengthened with machine learning and cognitive technologies, have stepped up productivity, resulting in immense benefits for our clients. 

    Business Outcomes

    • Our ATDD framework reduces the effort of building test automation suites by 30% and cuts maintenance costs by up to 60%
    • Faster delivery cycles improve collaboration, thereby reducing total cycle time by 25%
    • Reusability and modularity reduce efforts by up to 25%
    • Increased coverage in regression test suite by 30-40%
    To learn more about our automation solution, download our perspective paper titled Accelerate Agile Software Development.
    Download Perspective Paper


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      Cloud 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 monolith applications that were more than 15 years old 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
      Goals
      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, and Application Insights
      Business Challenge

      The client had a suite of legacy applications to generate barcodes that are scanned globally over 6 million times a day.

      These applications were built on monolithic architectures using heavy-weight application servers and outdated technologies. This architecture was causing long development cycles, making the organization less competitive. Developers’ productivity was also dropping due to high technical debt.

      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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      Anti-money laundering software saves $1M

      Banking

      Unified AML proves to be a game changer

      Global bank overcomes anti-money laundering monitoring challenges and saves $1M in infrastructure costs with a unified front-end.

      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

      The solution amplified efficiencies and reduced costs through the automated system and seamless exchanges of information. Significant outcomes included:

      • 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
      Contact

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      Reporting transformation with data science and AI

      Banking

      Data science and AI transform disclosure and reporting

      A multinational bank leveraged data automation to achieve major gains in reporting efficiency, with 99% accuracy in processing variable inputs, for its global investment fund.

      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 net asset value (NAV) 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

      The high solution accuracy helped the client’s global NAV reporting team significantly improve precision, efficiency, quality, turnaround time, and flexibility. The delivered solution contributed to:

      • 90 - 95% reduction in operational efforts
      • 99% accuracy in processing variable inputs
      • Zero rework effort and cost

      Our highly customizable and scalable solution can be seamlessly integrated with existing reporting applications and MS Outlook while accommodating additional volumes, report types, and business units.

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      Powering shop floor efficiency with data analytics

      Manufacturing

      Powering efficiency on the shop floor

      A new custom manufacturing application with real-time dashboards replaces a diesel engine maker’s outdated build-specification legacy system and eliminates production delays.

      Client
      A leading diesel engine manufacturer
      Goal
      Reduce bottlenecks on the production line that arise from last-minute changes to orders and ensure compliance with build instructions
      Tools and Technologies
      Windows, SQL Server, C#, .NET, ESB, HTML5, Angular, GitHub, JIRA, Visual Studio, and WebStrom
      Business Challenge

      A diesel engine manufacturer based in Detroit faced frequent production delays. The cause of the inefficiency was its build book system. The manufacturer used a printed build book to communicate the specifications of the engine being built to the production floor. But, often after the book was sent to the shop floor, the manufacturer had to make changes to specifications.

      In such cases, those working on the production line would not be able to use the printed build book. Waiting for a reprinted book would halt production. As a result, the changes were usually communicated outside the manual and assumed to be followed. If the new specifications weren’t followed, they would be discovered only in quality assurance, leading to a loss of time and dollars.

      Solution

      The client wanted a solution to resolve bottlenecks created by the printed build book and ensure compliance with build instructions. Ideally, the build book is dynamically pushed onto a handheld device assigned to the shop floor. The system would allow managers to update the specifications in the build book on the fly and alert the production team to the changes.

      The device would also communicate the status of production to managers. For example, they would know which work center is working on an engine so that relevant pages of the build book could be updated and displayed to those work centers. 

      Iris custom-built an application that allowed real-time updates of the build book. It was designed to push the build book to work center operators on V10 devices (RFID transponders) with screen sizes ranging from 3 inches to 10 inches. The solution included a consolidated dashboard that provided the management near real-time visibility of work centers and the status of the engine production.

      Outcomes

      During Phase 1 of the project, we deployed 250 V10 devices. After a pilot run of four weeks, the client stopped printing build books; the handheld devices with our application were a superior alternative.

      The solution helped eliminate printing costs and allowed the manufacturer to accommodate last-minute changes in specifications without disrupting production.

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      Global pivot from physical to online tests

      Education

      Global pivot from physical to online tests

      System modernization helped a multinational educational testing and assessment organization overcome COVID-19 disruptions to deliver seamless and accurate digital testing.

      Client
      A leading educational testing and assessment services company
      Goal
      Switch from in-person to online testing
      Tools and Technologies
      AWS Serverless, Dynamo DB, Node.js, Typescript, Java, Jenkins, and Angular
      Business Challenge

      Our client, which provides educational testing and assessment services, faced an existential threat with the pandemic-era lockdowns and social distancing requirements. The testing centers it operated at physical locations were unable to open, leaving thousands of students worldwide in a state of uncertainty. 

      Our client had to switch from in-person testing centers to a digital-first or online testing solution almost overnight. To achieve that, it had to migrate rapidly from legacy systems to the cloud. It also needed to ensure the sanctity and accuracy of its tests while delivering a seamless digital experience to its customers. Other challenges included the ability to dynamically scale up or scale down capacity in response to demand, maintain acceptable service levels, and enable thousands of expert test raters to access and evaluate tests.

      Solution

      Iris Software stepped in to facilitate a strategic digital pivot in the business model to secure the company’s future. Modernization efforts that were underway at the company even before the pandemic were accelerated as a digital upgrade became imperative. We shifted the data stored on legacy infrastructure to the cloud.

      Our team developed a new testing interface that would work overnight across devices, geographies, and different internet connections. Switching the testing operations to the cloud with scalable capacity could help manage the surge in the number of users for the tests. Iris also deployed automation and AI tools to deliver superior experiences for test raters. Those who faced challenges while attempting to grade tests were provided with an always-on AI-based solution to automate the troubleshooting and ticketing process.

      Outcomes

      The client now has scalable, digital-first testing capabilities to meet all its testing requirements.

      • Cloud-based testing enabled on-demand access to students, evaluators, and employees.
      • The remote testing options are accurate, secure and safe from external threats.
      • A strong focus on automation and user experience has allowed for optimized online offerings.
      • Surges in demand for tests can be met rapidly and at scale with minimal intervention.
      • Thanks to the always-on cloud offerings, service levels are easily maintained.
      • The successful digital pivot has led to strong interest in a hybrid operating model to safeguard the business from threats in the future.
      Contact

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      Do you trust your data?

      Do you trust your data?

      Data driven organizations are ensuring that their Data assets are cataloged and a lineage is established to fully derive value out of their data assets.




        Good business decisions are often the product of the right people having access to the right data at the right time. Data lineage makes this possible.

        An Iris Software Perspective Paper brings you insights on why establishing data lineage has become imperative for organizations across industries, what benefits it can bring to your enterprise, and how you can begin your data transformation journey.

        How can data lineage help your organization? Guided by Data & Analytics service providers, data lineage can drive better outcomes such as improved data quality or delivering better insights to business teams. It could also ensure compliance with regulations such as the European Union’s General Data Protection Regulation (GDPR) and BCBS 239, Basel Committee on Banking Supervision's principles for effective risk data aggregation and risk reporting.

        The perspective paper highlights the value of a Data Catalog and a Data Lineage solution in an organization. The paper details on how machine learning (ML) and natural language processing (NLP) are used to accelerate the data cataloging process and thereby shorten time-to-value.

        The paper also highlights the Iris Data Governance solution framework along-with representative case studies.

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        How to transform your risk reporting mechanisms

        Capital Markets

        How to transform your risk reporting

        A leading brokerage firm improved its UI and lowered costs with a future-ready risk reporting platform.

        Client
        A brokerage firm with a strong presence in the capital markets
        Goal
        Improve risk reporting and calculations
        Tools and Technologies
        Dot Net, C#, Greenplum, JUX Proprietary Framework and HTML5
        Business Challenge

        The client's market risk reporting and limit monitoring platform was based on products that were reaching the end of their service lines in the foreseeable future — Microsoft's Silverlight for viewing rich content and IBM's Netezza for data warehousing. They wanted to move to a new-technology platform. Among the big challenges was a lack of user-friendliness, a high cost of ownership because of the maintenance needed, and a lack of scalability as the data could not be clustered. The existing systems did not enable efficient audit trails and tracking of users. Iris had to identify alternatives that would sit well with 55 other applications in the system.

        Solution

        We considered building a visualization platform using the latest JavaScript frameworks such as Angular or React but settled on making a fresh user interface and UI framework on HTML5. We developed new UI widgets to provide better user experience, making it possible for users to customize their workspace. We integrated the module to manage a user’s role and access level. In all, we provided a modern, flexible interface for application deployment that was developed in-house.

        Outcomes

        We successfully moved all the 55 applications to the new platform. As a result, the total cost of ownership was expected to be 15% lower after the migration. It was also built for the future — a distributed, scalable, mobile-ready platform. It had an integrated module for managing user roles and access levels and could be customized with various themes to provide better user experience. User tracking and audit trails were enabled. 

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        The power of in-sprint automation

        Automation

        The power of in-sprint automation

        A large securities firm sped up time-to-market with end-to-end test automation on the cloud.

        Client
        A leading securities trading firm
        Goal
        Build a cloud-based automation framework to test client’s trading platform
        Tools and Technologies
        C#, Ranorex, TestRail, Simulators and Selenium
        Business Challenge

        The client had a legacy trading platform that had grown and evolved over time. The platform consisted of a stack of 33 applications, built on a variety of technologies and architectures.

        Testing new features and additions was proving to be a big challenge. A simple change in one feature would warrant a verification of the complete application. To ensure that any change does not affect other functionality, the client needed to do extensive regression testing and verification.

        This was a cumbersome process with over 20,000 or 30,000 test cases being checked and executed manually. The trading firm had to deploy over 20 people to carry out this exercise. The client had tried to automate the testing process with a variety of tools but was not able to get the efficiencies it wanted.

        In addition, the client had multiple squads working on different apps, functionality and features. Each squad used its own automation suite. It was becoming a challenge to co-ordinate the work of the different squads and ensure that changes made by a squad did not impact the overall functionality of the platform. Iris’s brief was to design and deploy a common cloud-based test automation framework for the client’s trading platform to ensure that it could launch new features faster.

        Solution

        Using its cloud-based ready-to-deploy test automation framework, Iris sped up the deployment of new features for the client’s trading platform. The cloud solution, based on Amazon Web Services (AWS), featured continuous testing of multiple products on a common framework layer. It allowed for complete capacity planning of spinned cloud instances and need-based shutdowns.

        Iris executed the project using acceptance test driven development (ATDD), a methodology that involves collaboration between customers, business teams and development teams. The teams jointly created the user stories and put down the acceptance criteria for any feature or functionality. Then tests were designed within the common framework to check if the feature met the acceptance criteria.

        What was unique about the approach? Typically, automation is introduced towards the end of a development cycle. You would find that, in most projects, developers bring in automation in Sprint 4 for features developed in Sprint 1, 2 and 3. As a result, return on investment isn’t maximized. Our team introduced ‘in-sprint’ automation, enabling 90% test automation with every sprint. This resulted in more efficient and faster testing, and cost savings for the client.

        Outcomes

        The client’s deployment speed improved significantly with 90% faster execution in each sprint cycle and 80% faster script development.

        The cloud-based solution is 100% configurable for on-demand execution on AWS, which reduced the client’s cloud infrastructure costs by 70%.

        The new ability for complete capacity planning through the use of infrastructure-as-code (IaC) for spinning up cloud instances helped the client achieve end-to-end (E2E) automation of regression/ functional test cases.

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