Story image

DataRobot achieves AWS Financial Services Competency status

DataRobot announced that it has achieved Amazon Web Services (AWS) Financial Services Competency status. 

This designation recognises DataRobot for delivery of effective solutions to help financial institutions identify, model, and assess risk, ensure monitoring and compliance with industry regulations, or help in surveillance or fraud monitoring.
 
Achieving the AWS Financial Services Competency differentiates DataRobot as an AWS Partner Network (APN) member that has demonstrated relevant technical proficiency and proven customer success, delivering solutions seamlessly on AWS. 

To receive the designation, APN Partners must possess deep AWS expertise and undergo an assessment of the security, performance, and reliability of their solutions.
           
AWS is enabling scalable, flexible, and cost-effective solutions for banking and payments, capital markets and insurance organisations, from startups to global enterprises. 

To support the seamless integration and deployment of these solutions, AWS established the AWS Competency Program to help customers identify Consulting and Technology Partners in the APN with deep industry experience and expertise.
 
DataRobot automates the data science workflow, enabling users to build and deploy highly accurate predictive models in a fraction of the time of traditional methods. 

Financial services companies use the DataRobot automated machine learning platform for a wide variety of uses cases, including model risk and validation, anti-money laundering, fraud detection, credit and re-payment risk, infrastructure monitoring, and prospecting. 

With DataRobot, financial services organisations can lower costs, and reduce exposure to regulatory fines and issues. 

OppLoans, a leading fintech platform, uses the DataRobot Cloud platform to deliver predictive models and underwrite processes that are more in tune with how consumers actually behave.

DataRobot also unveiled integrations with two AWS solutions, Amazon SageMaker and Amazon Redshift. 

Amazon SageMaker is a solution that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. 

With DataRobot and Amazon SageMaker, users of both solutions are empowered with key capabilities of rapid model development, automated machine learning, collaboration, and fast model deployment.
 
By adding Amazon Redshift as a data source, DataRobot makes it easy for joint customers to pull data from Redshift into DataRobot to successfully achieve deeper insights with automated machine learning.

Workday customers start deployments to AWS infrastructure
Business software vendor Workday has turned it's previously announced AWS partnership into a reality.
Royole's FlexPai: So bendable phablets are a reality now
A US-based firm called Royole is delivering on that age-old problem of not being able to fold up your devices (who hasn't ever wished they could fold their phone up...)
How to leverage cloud for data-driven business ops
The next gen of cloud-based data platform services are flexible and cost-effective so even small organisations can unlock data insights.
What MSPs can learn from Datto’s Channel Ransomware Report
While there have been less high profile attacks making the headlines, the frequency of attacks is, in fact, increasing.
Cisco expands security capabilities of SD­-WAN portfolio
Until now, SD-­WAN solutions have forced IT to choose between application experience or security.
IDC - Global digital transformation spend to near $2T by 2022
Hardware and services spending will account for more than 75% of all DX spending in 2019.
AlgoSec delivers native security management for Azure Firewall
AlgoSec’s new solution will allow a central management capability for Azure Firewall, Microsoft's new cloud-native firewall-as-a-service.
Gartner - Global RPA spending hitting its stride
The biggest adopters of RPA today include banks, insurance companies, utilities and telecommunications companies.