Custom analytics enable faster business decisions

Asset Management

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, Jenkins
Business 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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Data warehouse enhances client communications

Data warehouse enhances client communications

Asset Management

Investment data warehouse enhances client communications

Account management and marketing teams of an investment bank acquired improved multi-channel client communications and portfolio management capabilities with a data warehouse and a single source of truth.

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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Cloud Data Lakehouse for Single Source of Truth

Cloud Data Lakehouse for Single Source of Truth

Life Sciences

Cloud Data Lakehouse for Single Source of Truth

Data systems built on legacy technologies were delaying month-end activities and actionable insights for finance and sales teams. Transformation of data and BI applications to MS Azure delivered "Order to Cash" sales analytics on cloud.

Client

A medical devices and fertility solutions company

Goal

Establish a cloud data warehouse for a single source of truth and timely month-end activities

Tools and technologies

Azure Data Factory, Azure Data Lake, Power BI, Synapse Analytics

BUSINESS CHALLENGE

The client had multiple instances of ERPs, sales systems, and warehouses built on obsolete technology and frameworks. The existing system siloed the data, resulting in inconsistent versions of the truth. The client's finance and sales teams were struggling to reconcile data offline and feed the same back into the ERPs, causing significant delays in month-end activities. As the record systems were also not synced and legacy reports were built on the interim warehouses, line managers and executive teams were not able to extract actionable and comprehensive insights. A solution to onboard and integrate new datasets on an ongoing basis was required to support the data merger and acquisition process.

SOLUTION

A transformation strategy to transform data and BI applications to MS Azure was finalized. The transformation was executed in phases and included discovery, report rationalization and foundational build of a global system of reporting. 

The solution included the data ingestion process with Azure Data Factory, data storage and processing using Azure Data Lake and Synapse Analytics, reports and dashboards with Power BI. A utility to accelerate the onboarding of new data entities was conceptualized and delivered to onboard and integrate new datasets to support mergers and acquisitions.

OUTCOMES

Iris data practitioners helped the client overcome key challenges and advanced data warehousing capabilities by:

  • Establishing a "single version of the truth" that enabled data-driven decisions and timely completion of month-end and other critical activities 
  • Delivering analytics to cash business processes, including subject areas of sales, inventory, shipping, finance, etc., on Power BI
  • Facilitating the generation of actionable, insightful reports and dashboards, allowing "self-service" consumption for the business leadership

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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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