Rackspace has partnered with global financial intelligence services company, Moody’s Analytics.
The big idea is to help Moody’s Analytics manage datasets involving 400 million firms to empower the financial firm to improve its existing risk profile offering and bring new competitive services to its clients.
Moody’s Analytics is a globally integrated risk assessment firm that empowers business leaders to make better and faster data-driven decisions through insights and analytical solutions.
The firm acquired one of the largest providers of private financial statements with data from over 400 million firms with more than 20 years of credit history.
Moody’s sought a solution to improve their data management system and provide their clients with a rating or probability of defaulting score, enabling better risk assessment and better investment decisions. But the company realised it needed to do more with its data.
The Rackspace Elastic Engineering (REE) team was deployed to deliver ongoing innovation, modernization, and transformation on a 24/7 basis and worked with Moody’s Analytics to understand the key data sources, challenges, and the opportunities to extract actionable insights and metrics from Moody’s database. Rackspace Technology designed a cloud-native solution with ETL processes for Moody’s Analytics. This migration to AWS enabled Moody’s Analytics to categorise each of the 400 million firms and define their probability of default on a daily basis within four hours.
Rackspace Technology Global Head of Solutions and Services Sandeep Bhargava said his outfit was providing Moody’s Analytics on-demand access to a dedicated team of cloud engineers, enabling a cloud-native and agile operating model to deliver the desired outcome for their clients.
Moody’s Analytics Senior Director, Product Operations Louis Chapman said his company wanted to take its huge database and streamline and optimise its data streaming and aggregation processes to provide our clients with actionable insights.
“The Rackspace Elastic Engineering team was instrumental in this process, and they helped reorganize our data management system and rationalise it in a consumable and easily understood format for our clients to buy this data,” he said.
