Case Study

Applied AI for Realtime & Accurate NAV Calculation

About the Company

Client is a prominent financial institution with a global presence, providing a wide range of financial services to clients worldwide. Renowned for its expertise in asset management and custody services, the institution serves a diverse clientele, including institutional investors, corporations, and government entities.

Background of Business Problem

Our Approach & Solution

Infinite used AI and RPA to automate three processes:

AI-Based NAV System

Infinite implemented an AI-driven Net Asset Value (NAV) system, leveraging machine learning to enhance accuracy in NAV calculations and address historical data quality issues. We used AI Model to find data issues by creating a system for quick processing of big data, like stock market info and daily trading data.

Data Quality Enhancement

AI models were used to improve data accuracy, consistency, and reliability throughout the custodian's operations, ensuring trustworthy financial reporting and bolstering transparency.

Robotic Process Automation (RPA)

RPA was used to streamline data gathering from multiple sources, automating tasks and reducing manual effort.

AWS-EMR for Data Processing

AWS Elastic MapReduce (AWS-EMR) facilitated efficient data processing, enabling rapid computation and analysis of extensive datasets crucial for timely NAV valuation.

Business Outcomes

95%

Reduction in NAV processing time. From 3-4 hours per client -> to less than 5 mins

~Zero

data discrepancies helped eliminating process failures

> 30%

Improved efficiency of Compliance team by reducing the time needed to generate compliance rules from over a month to less than a week.

> 90%

Accuracy in price moment prediction

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