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Thats not my name: challenges in KYC name matching The team combines qualitative anthro-linguistic expertise with access to tailored quantitative data science algorithms and machine learning techniques to overcome name-matching challenges and deliver accurate results
Match Accuracy - SymphonyAI NetReveal Financial Services Increase match precision with intelligent detection models and easily configure to keep your risk strategy agile Match common typos rather than treating all spelling differences equally, enabling greatly improved overall match accuracy
SymphonyAI NetReveal AML transaction monitoring regulatory exposure, and reducing the cost of compliance It provides a global view of financial crime and offers flexibility to monitor and quickly update an organisation’s AML detection strategies as criminal typologies change, employing a “white-box” d
Fuzzy approach based money laundering risk assessment The main goal of the KYC process is to implement a robust solution allowing the obliged entities to assess the level of money laundering risk as part of the cus-tomer relationship establishment, often referred as an on-boarding process
Fuzzy matching: Getting the balance right The parameters should be tested and calibrated in line with the risk appetite of the firm Measures should be in place to ensure that it remains effective Calibrating screening systems to the appropriate level of fuzzy matching is a key tool to protect a firm against financial crime
Predictive Analytics for KYC and AML in Fintech (2025 Guide) What Is Predictive Analytics in AML and KYC Compliance? Predictive analytics in AML and KYC compliance refers to the use of data models to detect suspicious behavior and prevent regulatory violations before they occur