Passa al contingut principal

Fraud Detection as a Service

ITESOFT

Increase fraud detection with robotic document & data control​

Falsified documents are involved in 56% of fraud.
Tired of fighting fraud blindfolded?

ITESOFT offers a unique and differentiating approach for fraud detection by systematizing document’s controls a priori. Meaning as soon as they are submitted (by paper, email, or via a web portal) and before any business process starts (such as customer onboarding, compensation, invoice payment, and more).

​ By using Fraud Detection as a Service, you will be able to:
​ - Systematize document control (100% not a sample) by leveraging robotic & automation technologies.
​ - Avoid costly identification of beforehand patterns and fraud schemes.
- Reinforce fraud detection activities immediately.
- Improve compliance.

Backed up by ITESOFT’s 30+ years of expertise in Artificial Intelligence applied to document processing and strong BPM capabilities, Fraud Detection as a Service combines:
​ - Unique and intelligent document-alteration detection technologies.
- Inconsistent data identification leveraging business rules and open data.
​ - Document audit trail.

Targeted markets:
​ - Banking & financial services.
​ - Insurance & healthcare companies.
- Government & local administrations.​
- Other corporates.​

Setting standardized digital processes for fraud has become a strategic challenge for corporates and government agencies seeking to simplify their customer and citizen relations while avoiding the malicious behavior that can be costly for them (both financially, legally and in terms of reputation). With Fraud Detection as a Service, ITESOFT provides a ready-to-go powerful Cloud service to overcome this challenge without any additional workforce required. ​
https://store-images.s-microsoft.com/image/apps.8066.54c1931f-4aff-47be-be1c-58014b0e612f.d34161c4-d254-4da9-ba29-f8f67f6f3fe5.328d4758-ca69-432c-9485-af711d52a4d5
https://store-images.s-microsoft.com/image/apps.8066.54c1931f-4aff-47be-be1c-58014b0e612f.d34161c4-d254-4da9-ba29-f8f67f6f3fe5.328d4758-ca69-432c-9485-af711d52a4d5