ACTICO, a global leader in providing software for intelligent automation, today announced DMI Finance as its first Indian customer for its new product, ACTICO Machine Learning.
DMI Finance has been working with the platform since April 2018 to enable real-time decisions across the lending lifecycle - from credit scoring and decision-making to loan disbursals. DMI Finance has also made an investment in ACTICO Machine Learning to apply intelligent technologies to optimize and automate decision-making processes at scale.
"We are happy to extend our already successful partnership with ACTICO. Machine Learning is an integral part of our decision-making capabilities - in line with our focus of making the best credit decision in the least amount of time. We believe ACTICO's Machine Learning platform is a strategic addition to our technology stack and will help us achieve scale without meaningful additions to our team", said Shivashish Chatterjee, Co-Founder & Managing Director, DMI Finance.
"We are thrilled to deepen our association with DMI. The Machine Learning capability of our platform provides a vital toolkit for Banks, NBFCs as well as for the new age Fintech companies to unearth insights from ever-increasing quantities of data. We strongly believe that, in the future, a combination of human intelligence and data insights will help firms take optimum decisions and this will continue to be the guiding philosophy for our product development endeavors", said Ajit Shah, Managing Director- APAC, Middle East and Africa, ACTICO.
Launched in May 2019 in India, the ACTICO Machine Learning platform totally redefines the conventional approach of using machine learning in standalone systems and integrates it into operational decision-making. The predictive models generated are used to optimize business outcomes in intelligent automation scenarios across the business lifecycle, such as product recommendations, fraud detection and risk management.
This story is provided by BusinessWire India. ANI will not be responsible in any way for the content of this article.
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