AI / ML Applications and Use Cases
Communications, Media and Entertainment
Potential Business Areas of Significant AI/ML Impact
Key solutions detailed below, all of which have been developed in close association with various clients, have relied heavily on using advanced Anomaly detection, NLP, Gen AI and Transparent Machine learning capabilities of EazyML.
Fraud Management System (FMS):
Is voice wholesale fraud, especially those related to mobiles, a concern? Are you suffering from frauds like false answer supervision, international revenue share fraud, premium rate fraud, wangiri, among several others? Is it damaging your reputation, harming your traffic as carriers pull you out of their routing table? Deploy FMS to arrest these – not only alert with priority for suppressing false alerts, but also implement auto-remediation in your routing engine to limit damage. Major global carriers have implemented EazyML based solutions, are delighted customers, automating fraud management.
- Fraud Management System using auto alerts to prevent frauds like false answer supervision, international revenue share fraud, premium rate fraud, wangiri, among others. Implement auto-remediation in the routing engine to limit damage.
- SPAM/ SCAM call detection. Use augmented intelligence coupled with NLP analytics to trigger SPAM/ SCAM alerts. Telecom regulation offers traditional protocol of using STIR/ SHAKEN authentication, or TRACED act for penalties, but are ineffective in eliminating this menace. Suppress false alerts which capturing true positives using AI.
Pricing and Monetization:
Mining the insights to develop effective pricing & monetization offers.
- Insights derived from various internal & external attributes influencing the price and its alignment with pricing strategy.
- Offers can be customized for different user personas or different segments.
- Understanding from take up rates which pricing plans are working, and which are not.
- Guided intelligence to decide promotions.
Using Insights derived from data cutting across demographics, customer relationship and digital interactions, building Propensity Models to
- Predict propensity to churn.
- Predict propensity for upselling.
- Assess customer sentiment & preferences.
- Improve customer engagement through enhanced user experience and personalization.