This global payments fintech unicorn offers a financial service interface for international transactions and global funds transfer for over 100,000 corporate entities over the world. This platform was established in 2015 and it serves as a hub for customers to receive payments from close to 180 countries and send money to over 150 countries, totaling over $50 billion in worldwide remittances as of January 2024.
Challenges: Upgrading Risk Control System Amid Rising Financial Fraud
The company used to leverage a conventional relational database for their risk control system, yet the relational database has restrictions on data model representation. Besides, it was inefficient in processing multiple-table joins, leading to failed identification of risk in fraud conduct within financial transactions.
The company well understands that a successful financial platform relies on not only its ability to facilitate seamless transactions but also its capacity to guard assets and transactions, particularly with today’s sofisticated financial scams. Upon retrospective analysis of the fraudulent incidents, the company found that graph databases outperforms relational ones in revealing hidden data correlations, making them an optimum solution for such scenarios.
The Solution: NebulaGraph Boosted Their Fraud Detection Capabilities
The company evaluated several enterprise graph database solutions, including ArangoDB, Neo4j, TuGraph and NebulaGraph with regard to architectures, performance, and scalability. The selection saw the choice of NebulaGraph because of its shard-nothing distributed approach, horizontal scalability as well as professional technical support.
- Global Compliance with Distributed Architecture
Since the company operates globally, it is faced with many data compliance requests from various regional authorities such as anti-money laundering and consumer privacy protection. This requirement was met by NebulaGraph which has a shard-nothing distributed architecture design separating storage from computation.
- Superior Performance for Real-time Anti-fraud Detection
An essential goal of the selection was to support real-time anti-fraud operations. In such a context, the underlying graph database must be able to handle over 1,000 concurrent requests and offer millisecond-level response times. NebulaGraph’s powerful native graph engine enables lightning fast QPS and TPS with millisecond latency, handles high levels of concurrency, making it an excellent fit for the company’s needs.
- Seamless Scalability for Future Growth
In consideration of the future expansion plans, the company laid emphasis on scalability. NebulaGraph provides robust horizontal scalability due to its shared-nothing distributed storage design. It was thus perceived as an ideal solution which could effectively handle their expanding business and data in the future.
- Premium Technical Support for Critical Infrastructure
Stability is a must-have for any foundational software and the company needed the provider of graph databases to have reliable technical support in graph technology. NebulaGraph, the leader of the distributed graph databases, boasts a deep bench of top experts in the graph technology industry. Thus, their professional technical support capabilities have been highly praised by the company from the initial project engagement to the final rollout.
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