Though a surge in global Anti-money Laundering (AML) and Know your Customer (KYC) regulations over the last 15 years has made KYC one of the most popular RegTech topics, one of the problems that is still addressed manually is KYC record remediation for standard clients and Politically Exposed Persons (PEPs). KYC documentation reviews frequently expose outdated or missing data, incorrectly matched documentation, and remediation backlogs. The KYC Remediation Accelerator uses Optical Character Recognition (OCR) and Natural Language Processing (NLP) to automatically confirm that all data is present and that evidence has been submitted. It cross-references and validates the evidence to uncover missing, misattributed or inconsistent data and dramatically reduces remediation time and errors.
Synechron’s KYC Remediation Accelerator dramatically reduces KYC Remediation time with multi-level data assurance across Confirmation, Validation and Cross-reference checks and an automated workflow that reduces manual work and mitigates unnecessary human error, strengthening the bank’s control framework. Users can create a reference profile against which all checks are done. A client file can be linked to multiple reference profiles. This flexibility allows for periodic checks combined with one-off checks, or global checks combined with specific country checks.
Confirmations: The accelerator pulls data from client Customer Relationship Management (CRM) systems and evidence databases and confirms all documentation has been submitted. Missing evidence is aggregated on an intuitive dashboard to prioritize workflow and create a foundation to automate alerts, next action in the workflow, or easily integrate that data into other systems.
Validation: Using Optical Character Recognition (OCR) and Natural Language Processing (NLP), the accelerator extracts data from evidence documents to confirm the evidence is valid, e.g. if a passport has not been expired. Should evidence be invalid, or in any way obscured inhibiting full data extraction, it will be flagged for replacement and unable to proceed in the reconciliation workflow.
Cross-reference check: If all required data fields are present and backed by evidence, the accelerator performs a Cross-reference check using OCR and NLP to compare the evidence documents to the CRM data, exposing errors that could be the result of misattributed evidence, inconsistent data entry or updates, or fraud. The framework allows for the implementation of automated requests for missing evidence, followed by validation and cross-reference checks upon submission.
The intuitive dashboard uses an open Application Programming Interface (API) architecture making it easy to add on additional functionality and integrate with existing CRMs, data storage, network drives, books and records systems, onboarding systems or Anti-money Laundering (AML) / Fraud solutions based on the existing workflow and technology ecosystem.