NDPC opens forensic probe into UNILAG, Lotus Bank over students' data used to open accounts
The Nigeria Data Protection Commission opened a forensic investigation on 14 August into the University of Lagos (UNILAG), Lotus Bank and fintech Hackerbella Ltd over allegations that students' personal data was used without lawful basis to open bank accounts on their behalf. NDPC's stated scope goes well beyond the underlying complaint: DPIAs, the lawfulness of any credit-scoring or profiling activity, use of automated decision-making systems, privacy notices, data-sharing arrangements, retention, and technical/organisational safeguards are all explicitly in scope, per NDPC head Dr Vincent Olatunji. Practical read: this is the NDPA 2023 machinery being used, in real time, against a university-fintech-bank data pipeline that profiles and scores individuals — directly on point for any Nigerian-corridor client running AI-driven credit scoring or onboarding on personal data sourced from a third party, and a live illustration of the automated-decision-making scrutiny the GAID 2025 Schedule 5 corridor work already tracks.
Source: Premium Times / NDPC
First real-world test of California's AI Transparency Act finds 6 of 13 covered companies non-compliant
Investigative outlet Indicator, working with the nonprofit WITNESS, ran the first compliance test of California's AI Transparency Act (SB 942) and the EU's parallel Article 50 marking duty, both live since 2 August. Of the 13 major generative-AI providers in scope (1M+ California monthly users) — Google, Meta, Microsoft, OpenAI, Adobe, Grok, Midjourney, Mistral, HeyGen, Synthesia, ElevenLabs, Suno, TikTok — only 7 had a working detector tool at all; of those, only Google's and OpenAI's correctly flagged AI origin after the file had been edited, with every other detector's accuracy degrading once content was tampered with. Non-compliance carries a $5,000-per-violation-per-day civil penalty under SB 942. Practical read: even the providers squarely big enough to be in scope of both SB 942 and Article 50 are shipping detection tools late or with real accuracy gaps — a useful, dated data point for any client weighing whether 'we'll build a detector eventually' is still a theoretical risk.
Unsure which of these developments applies to your AI systems?
Begin in writing →This briefing is general information, not legal advice, and does not create an advisor–client relationship. Summaries are original; follow source links for the full record. Adesanya AI Advisory — Abdulwahab B. Adesanya, Barrister-at-Law (Nigeria).