Dotfile Features

Orchestrates customer journey via customizable workflows.

Contains e-signature functionality.

Captures customer data through digital forms.

Uses OCR to scan customer documents, extract data, and auto-fill forms using the extracted data.

Scans and verifies customer identification documents.

Runs KYC checks on customers using information gathered in the application.

Checks customer credit information.

The solution uses intelligent algorithms like fuzzy matching to identify potential risks.

Create watchlists that can include sanctions lists (e.g., Dow Jones, WorldCheck, WorldCompliance, and Accuity).

Score persons and organizations based on their history and risk potential.

Pool data from various sources to auto-populate e-filing of Suspicious Activity Report (SAR) or Currency Transaction Reports (CTR) forms.

Standard workflows to assign workload and to alert users based on predefined triggers.

Manage due dilligence processes such as Customer Due Diligence and Know Your Customer.

Comply with regulations from multiple jurisdictions such as OFAC, UN, EU, OSFI, UK and AUSTRAC or FATCA.

Compliance with fraud and risk management policies created by the company using the solution.

Create behavior models that can be used to detect suspicious behavior.

Simulate and validate scenarios to address multiple types of risks.

Real-time transaction screening to immediately identify potential risks.

Allows users to segment and manage lists of suspicious persons and organizations.

Evaluate the quality and performance of the anti-money laundering activities.

Ability to generate standard reports for compliance purposes such as FATCA/CRS, SARS/STR and SWIFT.

Display suspicious activity by period, risk type, person or organization.

Dashboards to provide real-time data on suspicious transactions, persons, or organizations.

Has integreated AI features to assess and assign risk scores to transactions and customer profiles, enabling prioritized investigations based on potential threat levels.

Uses AI algorithms to identify complex patterns and anomalies in transaction data that may indicate money laundering.

Improves performance based on feedback and experience

Makes informed choices based on available data and objectives

Makes informed choices based on available data and objectives