Payment Analysis System
Видавець: CogniTensor Technology Pvt Ltd
Predictive Analytics to Reduce Timelines of Payment Collection and Invoice Management
CogniTensor’s Payment Analysis System is a combination of correlation analytics and prediction dashboards that are specially designed to assist you in addressing various finance objectives. These objectives can range from reducing timelines of payment collection, periodic reminders to customers and associated sales persons on payment dues, regular review of payment defaulters among others. This is achieved with a combination of advanced data analytics, future predictions in order to provide you with actionable insights.
The predictive analytics use bespoke combinations of cutting-edge machine learning and deep learning models, backed by advanced research. These algorithms have been tailored specifically to handle the complex data coming from numerous industries and organisations that deal with multiple vendors, channel partners, retailers, and various other sources.
The entire system is developed on a state-of-the-art platform, backed by open source technologies. Each component is highly customizable in terms of data and other relevant specifications in order to cater to your needs in today’s dynamic business environment.
Features and Capabilities:
Artificial Intelligence based prediction of future payment defaults, along with consolidated reports of payment dues and receivables to streamline the financial operations
Comprehensive grading systems based on the historical payment trends of your customers to provide data-driven insights on expected payment delays, also providing a decision support tool for future transactions
A real-time dynamic reminder system with functionality to send customised reminders to your stakeholders as well as your customers, at the click of a button
Self-learning predictive models that adapt to your needs, constantly evolving to deliver superior performance
Easy integration support with databases management systems such as Oracle, Postgres, etc.
Round the clock monitoring via an intuitive web app and on-the-go tracking through a dedicated mobile app
