Reporting transformation with data science and AI

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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Cloud-native app opens new markets

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

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

With the new solution, the client wished to achieve scale with minimal latency in operations and service, integrate new businesses without disruption, roll out  features faster to improve customer experience and get a competitive edge, use data to help customers make better trading decisions, and monetize the data.

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 cloud-based architecture enabled the client to create products and monetize market data. 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
  • Make releases several times a year
  • Offer customers trading in Muni bonds (an acquired product) and U.S. treasuries (a new service)
  • Support Chinese markets

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Deliver personalization via report automation

Deliver personalization via report automation

Asset Management

Deliver personalization via report automation

A leading asset management firm personalized offerings by automating processes to glean customer insights.

Client

A leading asset management firm based in the U.S.

Goal

Help asset managers deliver personalized solutions to establish differentiation.

Tools and technologies

AquaData Studio, Java, Perl, Python, Spring, Hibernate, VRS, PostgreSQL, Composite and MS SQL.

BUSINESS CHALLENGE

A generational shift in investment behavior, changing regulations, a thinning pool of investible funds and new investment patterns are posing a challenge to asset management firms.

Our client, an asset management company, wished to overcome these difficulties and stand out by offering customer-centric solutions that are flexible and adaptable. The client was overwhelmed by the need for intense manual effort to run their front, mid and back office functions; and inconsistent business rules. Other challenges included rampant data duplication, time-consuming data validation, the inability to get a holistic view of their accounts, and poor user experience on the platform.

SOLUTION

Iris created a robust data ecosystem and used advanced technologies such as artificial intelligence/machine learning (AI/ML), intelligent automation, cloud computing and test automation to deliver better digital experiences to the stakeholders.

We streamlined and integrated the client’s front, middle and back office functions. We helped the client integrate their back-office solutions with their custodians, increasing operational efficiency by more than 75%. We automated the creation of more than 7,000 reports. We developed a strategic reporting module that gave customers a holistic view of their accounts and holdings. We set up a business data validation team offshore and enabled self-service option for bespoke reports.

OUTCOMES

Our solution helped the client significantly improve front-end experience for customers, reduce manual effort and costs in the back office, and improve overall operations efficiency. Our actions:

  • Automated the exhibits process with 75% increase in throughput
  • Reduced manual effort by 70% and improved monthly artefact generation throughput by 40%
  • Reduced manual effort for customization in client profile management by 60%
  • Achieved $50,000 savings monthly in data validation for client profile management

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A robust platform for investment advisors

A robust platform for investment advisors

Brokerage & Wealth

A robust platform for investment advisors

A prominent U.S. brokerage firm transformed its monolithic legacy apps for registered investment advisors (RIAs) into a microservices-based open platform and significantly improved user experience.

Client

A leading brokerage and wealth management firm based in the U.S.

Goal

Create a best-in-class platform for registered investment advisors (RIAs).

Tools and technologies

Pivotal Cloud Foundry, Spring Boot, Spring Cloud Gateway, Angular 6, TIBCO AMX BW, SQL Server, Hybrid Automation Framework (Selenium, Appium, Perfecto) and AppDynamics

BUSINESS CHALLENGE

With growing competition from nimble fintechs, custodians are under pressure to provide RIAs a differentiated experience. Many of them are looking to use advanced technology solutions such as machine learning, artificial intelligence and data and analytics to help RIAs improve the end consumer experience.

Our client had multiple legacy platforms built over the years that were preventing it from providing their RIAs with a secure, integrated and cost-effective solution.

SOLUTION

We provided an open access platform with API architecture as part of the client’s go-to-market strategy. We enabled encryption of data in transit to protect more than 100 integrations outside the client environment and used SAML and OAuth for user authentication.

Our SSO solution provides multifactor authentication and a framework for privileged access to secure customer information. We also ensured mobile security for iOS and Android devices. The team developed responsive design as part of UI transformation for core trading, advisory and educational solutions; and transformed monolithic applications into micro services-based architecture. We also digitized end-to-end client onboarding with features for bulk onboarding and advisor authorization; and created back-office solutions.

OUTCOMES

We enabled the client to securely integrate over hundreds of third-party apps and RIA back-office applications. Our test automation and Agile solutions helped the client:

  • Reduce time to market for new features by 40%
  • Reduce the regression cycle duration by 60% with automated tests over six months
  • Increase test automation coverage to 70%
  • Reduce defect leakage to less than 1%
  • Improve performance of business transactions by 30% to 40% on the web platform
  • Address more than 70% of security and vulnerability issues, leading to a better customer experience

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