Namaste Credit enters into a collaboration with Microsoft Azure over fraud detection solutions 

Reportedly, the AI-powered fraud detection system will offer a real-time data analysis

Going by Namaste Credit’s official website, it aims to digitally transform the SME lending ecosystem in India
Going by Namaste Credit’s official website, it aims to digitally transform the SME lending ecosystem in India

Namaste Credit, an underwriting technology platform, has announced a partnership with Microsoft Azure under the STAB Program of G7 CR Technologies – A Noventiq Company.

According to an official release, with this partnership, the technology startup aims to introduce its fraud detection capabilities as part of its full stack underwriting. From what it’s understood, the AI-powered fraud detection system will offer a real-time data analysis, fraud pattern detection, and adaptability in the face of fraud mechanisms and provide assistance to banking, financial institutions, and the fintech industry.

It’s believed that through leveraging the capabilities of Microsoft Azure, Namaste Credit can scale its fraud detection system to handle volumes of data, ensuring rapid response times and real-time threat detection. With Azure’s network of data centres, Namaste Credit can offer its fraud prevention solutions to businesses worldwide. Moreover, Microsoft Azure’s security measures can enhance the protection of sensitive data to benefit Namaste Credit’s customers. Sources suggest that integrating Namaste Credit’s fraud detection capabilities with Azure’s cloud infrastructure can ensure an implementation process for businesses of all sizes.

“We are looking forward to partnering with Microsoft Azure and G7 CR Technologies – A Noventiq Company to bring our fraud protection capabilities. I believe this collaboration combines our expertise in fraud prevention with Azure’s cloud services, providing our clients with protection against fraud,” Gaurav Anand, founder and CEO, Namaste Credit, said. 

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This article was first uploaded on November seven, twenty twenty-three, at forty-five minutes past five in the evening.
Market Data
Market Data