AI in Fintech
Security, reliability, and usability are critical factors that determine the success of a fintech app. However, it is not easy to process and analyze huge volumes of financial data involving millions of transactions every day. With artificial intelligence, fintech companies can analyze large data sets, assess risks, understand customer behavior, and deliver a secure and seamless user experience. HyperSense no-code AI platform empowers Banking and fintech companies to build prediction models for multiple fintech use cases and gain fast insights from data to quickly identify and respond to threats and to deliver a superior user experience.
Why HyperSense?
What can you do with HyperSense?
Better transaction success rate
Track metrics that impact transaction success rate to identify and understand root causes of issues to eliminate roadblocks to user experience.
Eliminate fraud
Identify and resolve security loopholes and critical fraud incidents across internal and customer-facing applications in real-time before it impacts the business.
Optimize revenue
Actively monitor revenue metrics to accurately forecast sales and get enhanced visibility into revenue trends to make smart, profitable business decisions.
Improve payment gateway
Accurately identify points of failure in a complex payment infrastructure distributed across multiple payment channels and partners to improve the payment gateway experience.
Prevent policy breaches
Monitor SLA metrics involving complex financial policies and regulations to proactively identify and prevent breaches within business functions and with external vendors.
Enhance customer experience
Analyze customer behavior metrics such as conversion rate, churn rate, etc to gain actionable insights to improve customer satisfaction and identify new areas for growth.
See how HyperSense can help you
A no-code platform for greater AI Adoption
A no-code AI platform that empowers business users without a technical background to leverage AI/ML.
Manage Whole ML lifecycle
Advanced MLOps to automate and manage the whole Machine Learning lifecycle.
Run faster AI experiments
Use a repository of pre-built templates, libraries, and workflows to manage complex analytics models and run experiments with ease.
