Digital ledger secures trading integrity

Banking & Financial Services

Digital ledger secures trading integrity

Automated, expandable distributed ledger system resolves trade reconciliation and compliance issues and lowers costs for global bank.

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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Software transformation gets compliance for bank

Risk & Compliance

Software transformation gets FDIC compliance for bank

World’s renowned investment bank gets timely compliant with new QFC (Qualified Financial Contracts) and FDIC (Federal Deposit Insurance Corp.) regulations through holistic system transformation and extensive QA & testing.

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

The client mandated to comply with new QFC (Qualified Financial Contracts) regulations. The client also needed to perform in-depth functional validation across a revamped data platform to ensure it could timely process, review and submit to the FDIC (Federal Deposit Insurance Corp.) required daily reports on the open QFC positions of all its counterparties. The project entailed immediate availability and processing of accurate QFC information at the close of each business day to swiftly assess data and note exceptions and exclusions for early corrective action. It also aimed to help the client meet stringent deadlines with varied report formats. Any breach or delay in compliance could attach hefty fines and reputational damage to the bank.

SOLUTION

Iris revamped the entire system and performed end-to-end quality assurance and testing across the new regulatory reporting platform. This meant validating the transformed multi-layer database, user interface (UI), business process rules, and downstream applications. We identified and solved workflow design gaps affecting data reporting on all open positions, agreements, margins, collaterals, and corporate entities, thus enhancing the capability for addressing irregularities. Our experts established an integrated and collaborative system, commanding transaction and reference data within a single platform by incorporating 166 distinct controls pertaining to data completeness, accuracy, consistency, and timeliness within a strategic framework.

OUTCOMES

Our quality assurance and testing solution delivered the following impacts:

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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IT modernization lowers costs for capital markets

Capital Markets

IT modernization lowers costs for capital markets

Age-old applications built on legacy technologies were affecting the client’s investment banking functions. Iris modernized the existing application architecture and helped the client save tremendous costs and turnaround time.

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

The client’s existing database application architecture was resulting in poor performance that was adversely affecting 10,000 investment banking functions. The age-old application posture was disrupting the compliance process for the global M&A, IPO, and other financing deals. The client’s customers were encountering problems such as regulations access, inconsistent or unusable data/deal search results, lagging database updates, delayed response time. The need for a capable system to support duplicate searches, and increasing ad-hoc IT redress efforts and costs were other prime concerns.

SOLUTION

Our tech experts re-engineered the entire compliance application and set up a new software system. We upgraded selective elements to improve the infrastructure performance and usage feasibility. The modernized system with new technology architecture streamlined processes and enabled faster, more advanced interactions between the information databases, search queries, and retrieval mechanisms. Complex procedures and the process of viewing features were also simplified.

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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Platform 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

The client had a licensed data platform for enterprise-wide risk and compliance operations. Spiked volumes with various financial product offerings and trades were restricting the processes and limiting the analytical capabilities on the existing platform. The system upgrade was required to support related, complex credit risk calculations. These calculations serve as a ground for several thousand bankers/ traders to make loan and investment decisions for customers. System modernization would also cater to the internal transaction and regulatory reporting requirements.

SOLUTION

Iris system re-engineering experts designed and implemented a scalable and highly configurable data extraction platform having global data architecture. This ETL framework-based platform enables faster, more efficient onboarding, consolidation, and processing of the numerous variable product and trading data input sources. The re-engineered platform was enabled with value-adds and tools to automate, tabulate, compare, reserve, validate and test data. We integrated the data extraction platform seamlessly with downstream risk applications and system adaptability to accommodate operational/business needs.

OUTCOMES

Our data platform re-engineering solution enabled the client to achieve enormous benefits, including user experience, data quality, and risk management capabilities. Key outcomes of the solution constitute:

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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SFTR solution strengthened market leadership

Risk & Compliance

Securities Financing Transactions Regulation (SFTR) compliance made easy

A global trading company solidifies its EU market leadership with regulatory solution and supporting to 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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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

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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 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

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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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

The client was 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 because 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. 15% Lower total cost of ownership 55 Apps moved to new platform

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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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Cloud-native app opens new markets

Cloud

Cloud-native app opens new markets

A prominent bonds trading network expands its market reach with new products and geographies.

Client

The world’s leading provider of trading services for fixed income products

Goal

Create an IT architecture to support growth across markets and products

Tools and technologies

AWS Cloud, Java, Springboot, React JS, React, Redis, Kafka, C#, Ranorex and Test Rails

BUSINESS CHALLENGE

The client, a market leader in bonds trading, was expanding to new markets, acquiring new businesses, introducing new products and adding features to existing offerings. To support its growth plans, it needed an agile, modern, cloud-based platform.

Some of the business needs the client wanted to address with the new solution were:

How do we achieve scale with minimal latency in operations and service?
How do we integrate new businesses seamlessly and without disruption?
How do we roll out new features faster to improve customer experience and get a competitive edge?
How can we use data to help customers make better trading decisions?
How can we monetize the data?

As a solution partner, we had to not only create a new IT architecture for the client’s trading platform but also constantly re-engineer and improve the architecture to quickly meet emerging business needs.

SOLUTION

We deployed a scalable, highly available auctions solution on the AWS cloud using Java, Springboot, React JS, React, Redis, and Kafka.

Optimized algorithms now achieve best matching with minimal latency while offering full price transparency. Artificial intelligence (AI) and machine learning (ML) provide greater insight and real-time price discovery for specific asset classes.

The new cloud-based architecture enabled the client to create products and monetize market data. Those products helped customers get accurate data in real-time to take better and faster trading decisions.

Test automation across the trade lifecycle using a combination of C#, Ranorex, Test Rails helped the client update user interfaces (UI) without reducing performance. It also eased integration linkages between the acquired solution’s frontend and the client’s existing backend.

OUTCOMES

The introduction of Agile methodology and the cloud-native application has helped the client significantly speed up time-to-market for new releases – it is now able to make releases several times a year.

The new IT architecture now allows the client to offer trading in Muni bonds (an acquired product) and U.S. treasuries (a new service). The solution also enables the client to support Chinese markets.

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Gen AI interface enhances API productivity and UX

Gen AI summarization solution aids lending app users

Quality engineering optimizes a DLT platform

Gen AI interface enhances API productivity and UX

Industries

Services

Gen AI summarization solution aids lending app users

Gen AI interface enhances API productivity and UX

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Banking & Financial Services

Digital ledger secures trading integrity

Client

Goal

Tools and technologies

BUSINESS CHALLENGE

SOLUTION

OUTCOMES

Contact

Risk & Compliance

Software transformation gets FDIC compliance for bank

Client

Goal

Tools and technologies

BUSINESS CHALLENGE

SOLUTION

OUTCOMES

Contact

Capital Markets

IT modernization lowers costs for capital markets

Client

Goal

Tools and technologies

BUSINESS CHALLENGE

SOLUTION

OUTCOMES

Contact

Banking & Financial

Re-engineering data extraction platform for increased efficiency

Client

Goal

Tools and technologies

BUSINESS CHALLENGE

SOLUTION

OUTCOMES

Contact

Risk & Compliance

Securities Financing Transactions Regulation (SFTR) compliance made easy

Client

Goal

Tools and technologies

BUSINESS CHALLENGE

SOLUTION

OUTCOMES

Contact

Banking

Unified AML proves to be a game changer

Client

Goal

Tools and technologies

BUSINESS CHALLENGE

SOLUTION

OUTCOMES

Contact

Banking

Data science and AI transform disclosure and reporting

Client

Goal

Tools and technologies

BUSINESS CHALLENGE

SOLUTION

OUTCOMES

Contact

Capital Markets

How to transform your risk reporting

Client

Goal

Tools and technologies