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Computer and Information Science · July 2026

Effectiveness of National ID as a Unique Identifier for Customer Onboarding in Financial Services in Bangladesh: A Survey

Muhammad Shakil Pervez, Md. Nasim Adnan, Ismat Rahman, Moinul Zaber, Sarker Tanveer Ahmed Rumee

Department of Computer Science and Engineering, University of Dhaka

Mixed methodsThematic analysis HCI & computer science

How they used Delve

Computer science researchers at the University of Dhaka used Delve to code semi-structured interview and focus group transcripts from ICT heads across all 61 banks and 35 non-banking financial institutions in Bangladesh, building an inductive codebook for a thematic analysis of national-ID-based e-KYC customer onboarding.

“Qualitative data—including interview and focus group transcripts—were coded using Delve Software, which facilitated systematic, rigorous analysis. [...] All of the analysis was done with Delve Software. The coding technique consisted of three columns: the transcript on the left, initial coding in the middle, and secondary codes on the right (Braun and Clarke, 2006).”

Field
Information systems and digital identity; national ID and e-KYC in banking and non-banking financial institutions
Data
Semi-structured interviews (20-90 minutes, some up to 120) conducted face-to-face or by phone with ICT heads and technically responsible personnel across all 61 banks and 35 NBFIs operating in Bangladesh, plus focus group transcripts and a structured questionnaire survey of 96 employees
Approach
Braun and Clarke (2006) thematic analysis adapted into a two-stage codebook workflow: an inductive codebook built from three transcripts, then applied to the remaining transcripts to refine codes and meanings; a three-column coding layout (transcript, initial codes, secondary codes) added a secondary-coding step beyond Braun and Clarke's guidelines; quantitative survey responses analysed alongside
Data types
Interviews, Focus groups, Open-ended survey responses

Abstract

National identity systems lie at the heart of every government’s identity management infrastructure. In Bangladesh, the National Identification Number (NID) has emerged as the primary credential for citizen identification, yet its integration with the financial sector—particularly for electronic Know Your Customer (e-KYC) compliance—remains fragmented, inconsistent, and vulnerable. This study investigates the effectiveness of the NID as a single authentication identifier for customer onboarding in Bangladesh’s banking and non-banking financial institution (NBFI) sector. We conducted semi-structured interviews with ICT heads and technically responsible personnel across 61 banks and 35 NBFIs, supplemented by a structured questionnaire survey covering six key dimensions: single authentication ID usage, e-KYC service operations, onboarding challenges, personally identifiable information (PII) handling, identity theft exposure, and agent banking practices. A mixed-methods analytical approach was applied, combining quantitative survey responses with qualitative thematic coding. Our findings reveal sixteen distinct vulnerabilities and operational gaps grouped into three categories: identity theft, privacy vulnerabilities, and technical vulnerabilities. Notably, the majority of institutions rely on manual, paper-dependent verification processes; the Bangladesh Election Commission (BEC) API constitutes a single point of failure for onboarding verification across hundreds of organizations; and a significant proportion of banks retain NID data beyond its intended purpose. Despite these challenges, we demonstrate that a Federated Identity Management (FIM) system built on the existing NID infrastructure is technically feasible and would substantially reduce administrative burden, improve security, and enable seamless cross-sector identity federation.

Citation

Muhammad Shakil Pervez, Md. Nasim Adnan, Ismat Rahman, Moinul Zaber, Sarker Tanveer Ahmed Rumee (2026). Effectiveness of National ID as a Unique Identifier for Customer Onboarding in Financial Services in Bangladesh: A Survey. Computer and Information Science. https://doi.org/10.5539/cis.v19n2p69

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