Due Diligence with AI-driven Solutions
Below are the highlighted Key features.
The AI generates a pool of randomized, context-relevant questions focused on the user’s stated intent (e.g., opening a bank account, applying for a loan, or transferring funds). This personalization helps identify inconsistencies in responses.
AI assesses the user’s understanding of their purpose for onboarding. For instance, knowledge-based questions validate the user’s intent for specific transactions, whether it's for savings, remittance, or investment.
AI detects behavioral signals like hesitation, assistance from someone off-camera, or delays that may indicate the user is being coached by external parties—common in mule account scenarios.
The AI monitors speech patterns, changes in tone, and body language to detect signs of deception, helping identify suspicious users who are coached or not genuine.
Through Natural Language Processing (NLP), the AI checks whether the user’s responses are coherent, relevant, and reflective of genuine knowledge. Scripted or memorized answers are flagged.
The system assigns a confidence score based on the user’s behavior, intent validation, and knowledge consistency. Low scores trigger further review or outright blocking from the platform.
Lets understand why AI ?
Traditional EDD processes are manual and resource-intensive, making it difficult to keep up with the growing volume of flagged transactions as financial ecosystems expand. AI enables institutions to automate EDD checks at scale, reviewing hundreds or thousands of flagged transactions simultaneously without compromising thoroughness.
AI allows for instantaneous review of transactions and user behavior, helping institutions detect fraud faster than manual systems can. This is especially crucial in stopping fraudulent activities in progress, such as identifying money laundering attempts before funds can be further transferred or withdrawn.
Human reviewers are prone to fatigue, biases, and inconsistency, especially when analyzing large amounts of data. AI eliminates these issues by applying consistent algorithms and criteria across every case, ensuring that no potential red flag is missed due to oversight.
AI and machine learning algorithms are capable of recognizing complex patterns in transactional data and user behavior that might not be immediately apparent to a human reviewer. By analyzing large datasets and historical information, AI can detect subtle signs of fraud, such as behavior anomalies, repeat patterns, or associations between flagged accounts
Fraudsters often exhibit certain behaviors that may indicate deception, hesitation, or external coaching. AI-driven voice, facial, and body language recognition systems can analyze these cues more effectively than humans. This enhances the ability to catch fraudulent actors early in the onboarding or transaction process.
AI significantly reduces the time taken for EDD checks from days or weeks to minutes, allowing institutions to process transactions without delays while remaining compliant with AML and KYC regulations. This is especially important in fast-moving markets where speed is critical to maintaining customer trust and satisfaction.
Automating EDD through AI reduces the reliance on large compliance teams, which are costly and often struggle with high attrition rates due to the repetitive nature of the work. AI can supplement human efforts, reducing operational costs while increasing efficiency.
Focus is to streamline the compliance processes by automating EDD, ensuring the authenticity of their users.
Accelerate Compliance
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