
The KYC process involves a significant amount of data collection from sources such as documents, photographs and fingerprints, among others. Often, this data needs to be cleaned up before it can be stored in a format which is suitable for practice use and which meets regulatory recordkeeping requirements. In the process, the large amount of data involved needs to be prioritized so as to focus on high-risk accounts. This process is known as data remediation. Let’s look at what data remediation is in a KYC context and what the process involves.
From the same root word as “remedy”, data “remediation” refers to the process of correcting errors in data and organizing it so that it can be stored in a form which is useful for its intended purpose and is compliant with regulatory standards. To make data useful, high-risk accounts are flagged so they can receive priority attention, while outdated accounts and irrelevant information may be purged.
The remediation process involves tasks such as:
Performing these tasks helps isolate high-risk accounts and prepare data from these accounts for verification and investigation. It also saves time and money by allowing resources and storage to be dedicated to high-risk accounts.
The data remediation process typically involves a few key steps:
KYC data remediation tends to be an involved process. For best results, consult a data remediation analyst and use an identity platform which supports the remediation process.
To understand more about KYC, please read the following:
Chapter 1 – KYC Verification
Chapter 2 – KYC Compliance
Chapter 3 – KYC and AML Differences
Chapter 4 – KYC Checks
Chapter 5 – KYC Data Remediation
Chapter 6 – KYC for Banking and Finance
Chapter 7 – KYC Solutions
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