Transaction monitoring is the process of keeping track on customer transactions, which includes analyzing previous and present customer data and interactions to provide a full picture of their behaviour. Transfers, deposits, and withdrawals are all examples of this.

Leveraging automation, artificial intelligence, and machine learning from the ground up, the IDVerifact transaction monitoring and case management solution provides the most sophisticated, configurable, and accessible financial crime lifecycle management solution on the market.

Financial crime risk and regulation shift constantly. Both also demand operational agility to adapt so reflecting changes in strategy requires technical resource, incurring delays and cost. IDVerifact places business users firmly and in control.

Financial crime experts can make changes directly, without programming, using natural language.

Stay ahead of them and amend rules, models, or even integrated application providers in minutes, eliminating the typical wait time.

The IDVerifact platform’s functionality is entirely transparent and accessible thanks to this method.

Easily drag and drop different third-party data sources, rulesets and Machine Learning models into a journey builder to create a strategy or journey in seconds. Our orchestration gateway does the heavy lifting, eliminating the need for lengthy and costly IT intervention.

IDVerifact is about making safe commerce simple. No other financial crime and compliance platform can offer business users the power, speed, and ease.

The system was built around delivering ultimate configurability alongside a best-of-breed user experience.

Multiple integrations are required for effective financial crime lifecycle management since it requires access to best-in-class data and services. With incumbent suppliers, integration costs might range into the hundreds of pounds and weeks of development time per service.

IDVerifact, on the other hand, simply requires one integration.

Implemented by financial crime technology specialists, a straightforward and intuitive Restful Application Program Interface (API) provides quick integration, providing a route to live in days, not months.

High quality decisioning starts with the best possible data. IDVerifact brings granular information from multiple datasets back into orchestration.

IDVerifact takes the intelligence generated by third party services and puts it into a single flow to create an overall risk score, called the “unified score.”

Changes in risk are recognized as best practices throughout the lifecycle.

Apply dynamic and persistent risk scoring at the account, customer, or transactional level using IDVerifact decisioning combined with orchestration and data.

Cases can be automatically escalated to suitable specialists or teams when an automated ‘pass or fail’ determination is not achievable.

IDVerifact integrates everything an agent needs to see to visualize risk, examine insight, and manage a case referral into one straightforward, easy-to-use interface.

  • Change risk scores
  • Add comments
  • Assign cases to various team members
  • Instantly convey choices across the organization
  • Submit fraud data to third-party databases and agencies in a timely manner

IDVerifact offers customers access to its own proprietary decisioning models as well as the ability to integrate their own or third-party models regardless language or platform.

Machine Learning capabilities drive:

  • Automated decisions
  • Improve the performance of rules
  • Reduce referral rates and operational costs

Virtual Agent is a proprietary Machine Learning model that learns from real agent choices.

As enabled, it can automatically simulate human agent behaviour when needed, such as when a fraud referral needs to be handled late at night and real agent resources are restricted.

Virtual Agent provides amazing automated decisioning that improves over time by retraining and utilizing real agent data.

Only a few data security systems can secure data while still keeping its utility.

Data is more useful in all the places we can use it to make judgments.

Data masking ensures data security by substituting sensitive information with a non-sensitive proxy in such a manner that the copied data appears and behaves identically to the original.

Non-sensitive data can be used in business operations using Dynamic Data Masking without having to change the supporting apps or data storage facilities.

Eliminate danger without jeopardizing the company’s operations.