In conversation with Aparna Manchanda: Head of Risk and Analytics at DMI Finance The Challenge DMI Finance was facing the challenge of getting quality alternate data to fuel their analytics models and understanding what data variables hold the best for credit profiling their non-traditional credit (NTC) users. The Solution They decided to partner with GeoIQ […]
Quick Service Restaurants thrive on walk-ins. Even though these businesses have partnered with food delivery services for online orders, the overheads and order ticket sizes are the two challenges that come along with it. With hyperlocal targeting, brands in this model can identify specific catchments around their facility with a higher density of their target
Risk assessment and credit profiling for new to credit customers is tricky. Along with it, there is great scope for improving the accuracy of risk prediction for credit-served customers too. For NAVI, we discovered location attributes that indicate the risk appetite of prospect users. Next, we augmented their user database with these location variables/ attributes
In this study, we will discuss how retail major Lenskart has benefitted from its partnership with GeoIQ, a location-based intelligence provider. Having access to location-based data is immensely helping businesses that are running their decision-making engines on data. It has been established fairly well that data is the new fuel for businesses to improve their
