Network Effect

A network effect occurs when a product or service becomes more valuable to each user as more people use it. Telephones, messaging apps, card networks, payment systems, exchanges and online marketplaces all show strong network effects. Economists also call them network externalities, because one person's decision to join benefits everyone already on the network.

Network effects are a central idea in the economics of platforms and in payments. They explain why a few systems, such as major card schemes or national instant-payment systems, come to dominate, why new entrants struggle, and why regulators pay attention to interoperability and access. The concept is distinct from economies of scale, where costs per unit fall as a firm produces more; a network effect raises the value to users rather than lowering the producer's costs, although the two often reinforce each other.

A single telephone is useless: there is no one to call. Two telephones allow one conversation. Once everyone in town has one, the phone becomes something you cannot live without, and anyone who still lacks one feels left out and signs up.

Payment apps work the same way. An app that none of your friends use cannot split a dinner bill. When most of them use it, it becomes the obvious choice, and that pull brings in even more users. Each new member makes the club better for everyone already inside.

• Direct effects. Users benefit directly from more users of the same kind, as in messaging or person-to-person payments.
• Two-sided (indirect) effects. A platform links two groups, and each benefits from growth on the other side. Card networks need both cardholders and merchants; marketplaces need buyers and sellers.
• Data effects. More use generates more data, which can improve a service, for example fraud models that learn from larger transaction volumes.
• Liquidity effects. In markets, more participants mean tighter prices and faster matching, the logic behind deep liquidity on large exchanges and order books.

A common rule of thumb, attributed to the engineer Robert Metcalfe, is that a network's value grows with the number of possible connections between its users. The number of possible connections is:

Here $C$ is the number of distinct pairs of users who could connect, and $n$ is the number of users. For example, a payment app with 10 users allows $10 \times 9 \div 2 = 45$ possible pairs; with 100 users it allows $100 \times 99 \div 2 = 4{,}950$. Ten times the users gives about 110 times the connections. The law is a simplification: in practice most users interact with a small group, so real value usually grows more slowly than this formula suggests.

Payment systems are textbook examples. A card is worth carrying because merchants accept it, and merchants accept it because customers carry it; interchange fees have historically been used to balance the two sides. Mobile money services such as mobile money platforms in East Africa and instant systems like PIX in Brazil and the Unified Payments Interface (UPI) in India grew rapidly once enough people and shops joined. Messaging networks such as SWIFT owe much of their staying power to the number of banks already connected.

The same logic applies to new market structures. A proposed exchange for tradable remittance contracts would depend on attracting enough sending firms and payout providers on both sides, so that price discovery becomes reliable. Platforms that match investors and businesses also gain from scale, which shapes deal flow. Pricing can be used to build a network: early users may receive discounts, or a provider may use tiered pricing that rewards volume.

Strong network effects can lead to "winner-takes-most" markets, high switching costs and market power. Competition authorities and central banks therefore push for interoperability, fair access rules and open banking, which let users and data move between providers. The Bank for International Settlements has noted that large technology firms can combine data, network effects and activities in finance, raising questions for competition and financial stability. Network effects can also work in reverse: a platform that loses users becomes less useful to those who remain, which can speed its decline, as seen in some cryptocurrency exchanges after loss of confidence.

• Bank for International Settlements: Big tech in finance: opportunities and risks (Annual Economic Report 2019)