RisK Monitoring

Data-driven Risk Monitoring powered by Hybrid AI

Make better decisions, leverage predictive capabilities and boost customer satisfaction. 

In unison, the financial sector, insurance realm, and telecommunications domain are confronted with shared obstacles encompassing credit risk, compliance risk, and customer churn. These impediments originate from the escalating intricacy of data and regulatory frameworks, the rapid pace of technological evolution, and the ever-shifting landscape of customer preferences. 

With Hybrid AI at its core, INFORM's RiskShield offers a unified strategy to address these challenges, providing data-driven insights, automation, and predictive capabilities. This empowers your business to make informed decisions, enhance customer satisfaction, and ensure compliance in an ever-changing landscape.

DISCOVER OUR Information Material on Risk Monitoring

Visualization of the Info Paper "Optimize your Claims Handling Processes with AI"

Optimize your Claims Handling Processes with AI

Dive into the complexities of claims management and discover how RiskShield's hybrid AI approach transforms processes for insurers.

Visualization of the Info Paper "Telecom Use Case: Customer Satisfaction"

Telecom Use Case: Customer Satisfaction

Explore our RiskShield Use Case on optimizing customer satisfaction with real-time scoring, automated actions, and Hybrid AI.

Visualization of the Brochure "RiskShield Case Management"

RiskShield Case Management

Dive into RiskShield Case Management, a browser-based solution offering powerful investigation tools, workflow control, and collaborative features for efficient risk management.

Visualization of the White Paper "How to Reduce Risk as Payments Transform"

How to Reduce Risk as Payments Transform

Download our white paper to learn more about the significant e-commerce trends and what can be done to reduce risk as payments transform.

Find more interesting info papers, brochures, and other downloadable assets on RiskShield in our section Expertise.