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17 Oct 2019, Edition - 1556, Thursday

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ACTICO Signs DMI Finance as Its First Indian Customer for Their Machine Learning Offering

by businesswireindia.com

Business Wire India
  • To provide prescriptive and predictive analytics on a single unified platform
  • This marks further strengthening of the ACTICO-DMI partnership

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 decisioning 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.
Speaking on this partnership, Mr. Shivashish Chatterjee, Co-Founder & Managing Director, DMI Finance said, “We are happy to extend our already successful partnership with ACTICO. Machine Learning is an integral part our decisioning 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.”
Speaking on the new customer win, Mr. Ajit Shah, Managing Director- APAC, Middle East and Africa, ACTICO, said, “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.”
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 business lifecycle, such as product recommendations, fraud detection and risk management.
Source: Businesswire