Croftz leverages cutting-edge automation to conduct PEPs, Sanction list, and Adverse Media checks in mere seconds, ensuring rapid response to emerging risks.

With access to over 1200 global watchlists, compliance, and sanction databases, Croftz diligently screens individuals and entities, leaving no stone unturned in risk identification.

Croftz offers both standard and enhanced due diligence options, allowing organizations to tailor their screening approach according to varying risk profiles.

Through ongoing watchlist monitoring against a plethora of global data sources including FATF, FBI, Interpol, EU, UN, HMT, and more, Croftz provides proactive detection and prevention of potential financial crimes.

As the foremost international body setting standards for combating money laundering, terrorist financing, and other illicit financial activities, our monitoring system actively tracks FATF's recommendations, advisories, and enforcement actions to ensure compliance with global AML/CFT standards.

Leveraging Interpol's extensive network of member countries and law enforcement agencies, Croftz diligently monitors Interpol's databases for alerts related to individuals, organizations, and activities linked to criminal behaviour, enhancing our clients' ability to detect and mitigate potential risks.

With the European Union serving as a key regulatory authority in the global financial landscape, our watchlist monitoring includes scrutiny of EU sanctions lists, regulatory updates, and enforcement actions, enabling clients to stay informed and adapt their compliance measures accordingly.

Croftz's monitoring system includes regular checks against United Nations databases to identify entities subject to UN sanctions, embargoes, or other restrictive measures, thereby helping clients avoid engaging in prohibited transactions and ensuring adherence to international obligations.

Monitoring Her Majesty's Treasury data sources allows Croftz to track UK-specific sanctions lists, financial regulations, and enforcement actions, providing clients with insights into sanctioned individuals, entities, and jurisdictions relevant to their operations.

Leveraging live video feeds, Croftz's platform captures real-time visual data to further confirm the user's presence and identity. Through this method, the system assesses facial expressions, movements, and other visual cues, providing an additional level of assurance regarding the authenticity of the individual being verified.

Croftz employs advanced face-matching algorithms to compare the live image of the individual with a reference image or biometric template stored securely within the system. By analyzing facial features, proportions, and contours, the platform confirms the user's identity, ensuring a seamless and reliable verification process.

By comparing the captured document with a predefined template, the system can accurately identify discrepancies or irregularities that may indicate forgery or tampering.

Automated template matching systems can process document verification tasks quickly and efficiently, reducing manual intervention and streamlining the verification process.

By incorporating advanced security features and authentication techniques, template matching helps enhance document security and prevent fraud.

Template matching systems can help organizations comply with regulatory requirements and industry standards for document verification, such as Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations.

The document to be verified is scanned or captured using an imaging device such as a scanner, camera, or smartphone.

The captured document image may undergo preprocessing steps such as resizing, noise reduction, and enhancement to improve the quality and clarity of the image.

Relevant features are extracted from both the captured document image and the reference template. These features can include text, shapes, patterns, and security elements.

A matching algorithm is applied to compare the extracted features of the captured document with those of the reference template. Various techniques such as correlation, histogram comparison, edge detection, and machine learning algorithms may be employed for this purpose.

A similarity score or confidence level is calculated based on the degree of similarity between the captured document and the reference template. This score indicates the likelihood that the document is genuine and matches the expected characteristics.

Based on the similarity score and predefined threshold values, a decision is made regarding the authenticity of the document. If the similarity score exceeds a certain threshold, the document is deemed authentic; otherwise, it may be flagged for further review or rejected.

Our platform streamlines the risk assessment process through automation, allowing for efficient analysis and prompt decision-making.

We delve into multiple risk factors, including customer attributes, jurisdictional considerations, and product-specific risks, providing a nuanced understanding of potential threats.

Utilizing a sophisticated algorithm, we assign risk scores and ratings based on a multitude of risk parameters associated with each customer, ensuring accuracy and consistency.

By swiftly identifying and addressing potential risks at the outset of a customer relationship, our framework helps mitigate adverse impacts on your organization, fostering resilience and safeguarding your interests.