Cross-Border Payments

Global payments revenue is largely based on transaction-based revenues, which are burdened by exorbitant transaction fees, intermediaries, and the interference of financial institutions.

Cross-border payments are complex, risky, and subject to high jurisdiction. Additionally, FX rates are often not fixed until the arrival of funds, with a complex multi-stakeholder process creating opacity. 

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Context & Challenges

The persistent growth of international trade, production, and cross-border e-commerce imply that the cross-border payment market will only continue to increase. Yet, payments sent across borders still tend to be more expensive, slower, and less transparent than their domestic counterparts. This is logical, given that they are inherently more complex, riskier, and more regulated. However, their challenges far outweigh these circumstances and, in their current state, they will not be able to adequately support healthy growth.

Global Payments are burdened by exorbitant transaction fees equaling around 2-10% of the transaction, and frequent lengthy delays. In 2019 alone, over $10 trillion crossed borders, a number that will only continue to grow alongside the increase in global business. Transaction-based revenue constitutes up to 40% of global payments revenue, a number predicted to grow to 46% by 2022.

Remittances are a prime example of transaction-based revenue, however, they lag behind other global payments, with a transaction fee of around 7%, with an average of 7.7% at the highest end of all global payments. By comparison, transferring money between consumers or small firms both in G7 countries usually incurs fees of 2% or less. Despite this, the remittance market is strong and growing. In 2019, $550 billion of remittances went to developing countries, which was more than the entire sum of capital such countries received as investment from multinational companies, according to the World Bank.

A few of the challenges driving the high transaction fees for global payments and remittances are:

  • Lack of transparency renders cash flow management inefficient
  • High costs associated with credit card transactions
  • High costs and lengthy processes inherent to cross-border payments
  • Transaction and settlement cycles take multiple days
  • Manual dispute and chargeback processes are laden with errors and delays
  • Global merchants with reward programs are vulnerable to loyalty liabilities

A STRATO product promises the streamline processes and drive the following benefits:

  • Establish a universal record of all transactions to eliminate the risk of record-keeping discrepancies
  • Drive transparency by building a verifiable and immutable data log, accessible by all authorized users
  • Scale to include all relevant parties seamlessly
  • Build trust around FX rates

These benefits will result in tangible cost and time saving measures:

Solution Benefits

  • Reduce the potential of error through automation, and ensure all data is updated in real-time

  • Through automated immutability, time-stamping, and traceability, reduce the regulatory burden around cross-border payments

  • By creating a single, distributed ledger, drive industry standardization and allow for seamless communication between parties across borders

  • Automate certain actions through smart contract logic,  automatically introducing rules, models, data, and transactions to be automatically enforced or updated

  • Prevent and seamlessly identify payments fraud by inherently verifying all data and tracking all involved parties

  • Use STRATO's scalability to scale to include infinite groups and institutions on shared private chains, creating standardization

Any STRATO insurance solution leverages STRATO's enterprise grade features

  • RESTful APIs for direct connection of IoT devices such as bankers' devices to the blockchain network

  • Identity Management, OAuth and SSO capabilities for simplified IoT authorization and user login

  • Privacy via private chains to keep sensitive data private and control who sees what data

  • Enterprise Data Modeling for integration into existing data systems, and to ensure interoperability

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