Enhancing Data Integrity and Reducing Operational Costs with Xoriant CDi Solution for a Global Financial Services Firm

How Xoriant CDi Solution Automated Data Workflows and Improved Accuracy for Streamlined Operations

Challenges:

A leading global financial services firm was facing persistent challenges related to data cross-referencing, data integrity, and operational inefficiencies, all of which contributed to compliance risks and potential revenue loss. This was particularly critical in the context of regulatory mandates, as inaccurate or incomplete data threatened both the company's compliance status and financial standing. The challenges included:

Difficulty in managing large data volumes and documents from diverse sources.
Ensuring accurate and consistent data across multiple sources in real-time was difficult, impacting efficiency and accuracy.
Ensuring compliance amid data integrity issues posed a risk to the client’s financial and legal standing.
Controlling high operational costs with legacy tools failing to adapt to the client’s evolving data needs, reducing profitability.

Solution:

Xoriant CDi provided a robust solution focusing on real-time data processing, which was instrumental in supporting client’s entity data concordance for downstream consumers. The solution included:

Implemented Retrieval Augmented Generation (RAG) Pipeline with ORIAN, Xoriant's GenAI framework.
Deployed Xoriant CDi to automate data workflows, reducing manual effort and errors while streamlining data processing.
Implemented continuous testing and integration via Application Testing and DevOps to ensure data accuracy and reliability.
Provided a real-time dashboard for data visibility and monitoring.
Automated data ingestion, processing, and mapping, improving data accuracy and efficiency.
Integrated a service request system to maintain audit trails and improve compliance management.
Provided 24*5.5 production support through Managed Services to maintain uninterrupted operations and swift issue resolution.

Business Value:

98% Accuracy in Data Quality which significantly enhanced the reliability of downstream reports.
25% faster data processing enabled quicker decision-making and more timely reporting.
30% reduction in operational costs achieved through automation and the replacement of the legacy tool.