Drawn from published evidence and regulatory guidance specific to retail and e-commerce. Each is pre-scored on a 5×5 likelihood × impact matrix in the Risk Register tool and referenced in the generated policy.
HighLikelihood 4 · Impact 4
AI Dynamic Pricing Discrimination Exploiting Consumer Price Sensitivity and Vulnerability
AI dynamic pricing systems that adjust prices in real time based on individual consumer profiling — incorporating location, device type, browsing history, purchase urgency signals, inferred income level, and vulnerability indicators — systematically charge higher prices to consumers identified as less price-sensitive or more financially vulnerable, exploiting information asymmetry in ways that cause disproportionate financial harm to disadvantaged consumer groups and may constitute exploitation of vulnerability under EU AI Act Article 5.
HighLikelihood 4 · Impact 4
AI Dark Pattern Manipulation Subverting Consumer Decision-Making at Scale
AI-optimised user interface design systems — trained to maximise conversion, subscription sign-up, or data consent rates — generate and test dark pattern interface configurations that exploit cognitive biases, create false urgency, obscure cancellation paths, pre-select unfavourable options, and deploy confirmshaming language, causing consumers to make purchases, subscribe to services, or consent to data sharing they would not have chosen under neutral interface conditions.
HighLikelihood 5 · Impact 4
AI-Generated Fake Reviews and Synthetic Social Proof Undermining Consumer Trust
AI tools used by retailers, marketplace sellers, or reputation management services generate synthetic product reviews, AI-authored testimonials, and AI-amplified positive sentiment at scale that deceives consumers relying on review authenticity for purchasing decisions, causing financial harm through purchases of misrepresented products and systematically distorting marketplace competition in favour of sellers willing to employ AI review manipulation.
CriticalLikelihood 3 · Impact 5
Algorithmic Price Coordination Between Competitors Creating Anti-Competitive Effects
Retailers using shared AI pricing platforms, common algorithmic pricing vendors, or AI systems that observe and rapidly respond to competitor prices achieve tacit price coordination — maintaining prices above competitive levels — without explicit communication between competitors, creating anti-competitive harm that competition authorities in the EU, UK, and US are increasingly treating as potentially unlawful concerted practice even in the absence of direct communication.
HighLikelihood 3 · Impact 4
AI Delivery and Service Allocation Discrimination Producing Disparate Geographic Outcomes
AI logistics optimisation, delivery scheduling, promotional allocation, and store inventory systems that use residential postcode, neighbourhood demographics, or geographic proxies as allocation inputs produce systematically inferior delivery timelines, reduced promotional access, and lower product availability for consumers in lower-income areas and minority-majority communities — replicating historic retail redlining through algorithmic systems that treat geography as a neutral optimisation variable rather than as a protected characteristic proxy.
HighLikelihood 3 · Impact 4
AI Retail Credit and BNPL Scoring Producing Discriminatory Consumer Lending Outcomes
AI buy-now-pay-later eligibility scoring, retail credit decisioning, and consumer credit limit management systems used by retailers and their embedded finance partners encode demographic and socioeconomic proxies into credit decisions — producing systematically less favourable credit access, lower limits, and higher effective costs for minority ethnic consumers, younger consumers, and those in lower-income postal codes, in violation of ECOA, EU Consumer Credit Directive, and equal treatment obligations.