Purpose
The purpose of this paper is to present the identification-verification-confirmation of identity (IVCid) model that can be used to retroactively analyze the existing customer identification programs and devise new ones that can be used in face-to-face or non-face-to-face environment.

Design/methodology/approach
This paper outlines the main elements of the customer due diligence (CDD) process and identifies those which may present a barrier to the customers. It then outlines the IVCid model. The model is used to analyze existing CDD approaches in physical presence, using reliable databases, biometrics and electronic signatures.

Findings
The IVCid model suggests that any customer identification program contains three elements: identification (collection of information), verification (checking the veracity of information) and confirmation of identity (linking the information to the individual). The accuracy of this model is confirmed by the analysis of the existing CDD procedures in some countries.

Research limitations/implications
This paper looks at a limited number of practical cases of CDD implementation. Further research might be needed to assess the strengths and weaknesses of biometric-based or e-signature-based solutions. Research might be needed to establish links between the IVCid model and financial inclusion.

Practical implications
The IVCid model allows for “modular” approach for the CDD procedures. It also underlines some risks associated with current CDD models.

Social implications
The IVCid model can be used to devise the CDD procedures that more effectively contribute to financial inclusion.

Originality/value
This paper proposes the first universal model for the CDD procedures that works for both face-to-face and remote scenarios while also being technology- and business-neutral.
Original languageEnglish
Pages (from-to)871-884
Number of pages14
JournalJournal of Money Laundering Control
Volume23
Issue number4
Early online date25 Mar 2020
DOIs
StatePublished - 25 Mar 2020

    Scopus subject areas

  • Economics, Econometrics and Finance(all)
  • Law
  • Public Administration

    Research areas

  • AML/CFT, Biometrics, Customer due diligence, Financial inclusion, Model, Verification of identity, AML, CFT

ID: 61939447