Blockchain & Cryptocurrency

Blockchain & Cryptocurrency covers the business reality of distributed ledgers and digital assets for BRICS-facing companies. We treat blockchain as infrastructure for multi-party coordination where trust, documents, and settlement create friction. The reader intent is pragmatic: what works beyond hype, where blockchain creates measurable value, how to manage compliance, and how to control custody and key risk.

Use case track #1 is enterprise blockchain beyond speculation: supply-chain provenance, shared data across participants, condition automation via smart contracts, and tokenization of rights/assets and documents. In complex global supply chains, blockchain is often positioned as a way to build transparency and accountability across parties who do not want to rely on a single intermediary. For B2B trade, this can reduce manual reconciliation, dispute rates, and verification time—especially when multiple stakeholders must agree on the same status and evidence.

Use case track #2 is settlement and cross-border payments. We explain when stablecoin-based flows can make sense, their potential benefits (speed, transparency, programmability), and constraints (regulation, AML/KYC, counterparty and operational risk). In 2026, stablecoins are increasingly discussed as regulated payment infrastructure in certain corridors, with policy and rulemaking developments influencing adoption paths. 

Use case track #3 is the risk layer: custody, key management, authorization controls, auditability, incident response, and business continuity. We provide enterprise custody guidance focused on reducing the risk of losing access to digital assets through control failures—cold storage, access procedures, insurance considerations, and continuity planning. 

The category is structured as a decision and implementation library: when blockchain is justified vs not, how to choose models (public vs consortium vs private), what metrics to track, how to pass compliance reviews, and how to pilot without reputational damage. The goal is to help operators separate useful deployments from trend-chasing and execute only where value is provable.