SFTR solution strengthened market leadership

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

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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Anti-money laundering: managing regulatory risks

Anti-money laundering: managing regulatory risks

Banking

Big Data platform improves global AML compliance

A multinational bank leverages big data platform to improve Anti Money Laundering (AML) compliance and prevents global clients and franchises from financial crimes.

Client

A leading global bank with operations in over 100 countries

Goal

Address data quality and cost challenges of legacy AML application infrastructure

Tools and technologies

Hadoop, Hive, Talend, Kafka, Spark, ETL

BUSINESS CHALLENGE

The client’s legacy AML application infrastructure was leading to data acquisition, quality assurance, data processing, AML rules management and reporting challenges. High data volume and rules-based algorithms were generating high numbers of false positives. Multiple instances of legacy vendor platforms were also adding to cost and complexity.

SOLUTION

Iris developed and implemented multiple AML Trade Surveillance applications and Big Data capabilities. The team designed a centralized data hub with Cloudera Hadoop for AML business processes and migrated application data to the big data analytical platform in the client’s private cloud. Switching from a rule-based approach to algorithmic analytical models, we incorporated a data lake with logical layers and developed a metadata-driven data quality monitoring solution. We enabled the support for AML model development, execution and testing/validation, and integration with case management. Our data experts also deployed a custom metadata management tool and UI to manage data quality. Data visualization and dashboards were implemented for alerts, monitoring performance, and tracking money laundering activities.

OUTCOMES

The implemented solution delivered tangible outcomes, including:

  • Centralized data hub capable of handling 100+ PB of data and ~5,000 users across 18 regional hubs for several countries
  • Ingestion of 30+ million transactions per day from different sources
  • Greater insights with scanning of 1.5+ Billion transactions every month
  • False positives reduced by over 30%
  • AML data storage cost reduced to <10 cents per GB per year
  • Extended support to multiple countries and business lines across six global regions; legacy instances reduced from 30+ to <10

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