End-to-End KYC Process

An end-to-end KYC process is based on the general basics of KYC compliance, which consists of three measures:

1. Customer onboarding. This is the process of identity verification applied at the initial stage of the user journey, which is before they open an account on an online platform. Often, document verification, selfie verification, and database checks are used, paired with other methods like address verification (for example, in crypto, when the user’s wallet needs to be verified). 
2. Due diligence. This is the part where automation is used for risk assessment, aka assessing the customer’s risk profile through AML measures, such as PEPs and sanctions screening. For example, PEPs require Enhanced Due Diligence (EDD) measures since they are considered to be high-risk (due to being more prone to corruption and financial crime). 
3. Ongoing monitoring. This is the last part of end-to-end KYC, which is based on concepts like perpetual or pKYC, as KYC is not a one-and-done matter, but a continuous process. In an end-to-end KYC process, this stage means that continuous monitoring of customer activity, monitoring transactions for suspicious patterns, and other similar measures are automated and applied. 

An end-to-end KYC process is backed entirely by automation, which means it’s more efficient. Often, such automated solutions use AI and are no-code or low-code, enabling companies to integrate, adjust, and tailor the KYC process depending on their internal risk assessment requirements. The biggest benefits that come out of this are faster user onboarding, improved accuracy rates and conversions, as well as overall better customer experience — all in line with regulatory requirements. 

Manual KYC stops the scaling process, which isn’t acceptable in many cases, especially if the company needs to handle large volumes of customers. Expanding manual KYC means hiring more compliance specialists, which demands more resources, making operational costs rise. 

Manually reviewing ID documents, proof of address, or other records like source of funds — then requesting additional information, updating internal databases, cross-checking external sources, and making a final decision — is a rather slow and error-prone process. On top of that, relying on outdated or incorrect data increases the risk of mistakes, making manual KYC verification inefficient and unreliable (especially when no automation is used). 

An end-to-end KYC process uses built-in automation tools for effective ongoing monitoring, which is typically based on monitoring suspicious user behavior and transactions. 

Other steps include:

• Identifying and screening politically exposed persons (PEPs)
• Screening and monitoring individuals on sanction lists
• Monitoring out-of-area or cross-border transactions
• Looking for AML red flags, such as unusual spikes in activity
• Screening for adverse media mentions