This article explains how using floating‑point numbers for money leads to precision loss, demonstrates common rounding pitfalls, and provides Go‑specific solutions—including integer cents and the high‑precision decimal library—to ensure accurate financial calculations.
This article explains the fundamentals of financial reconciliation, outlines the two‑step reconciliation process, and details a streaming reconciliation architecture capable of handling 30 billion USD per hour (≈27 777 TPS) with high concurrency, distributed parsing, and efficient result aggregation.
This article outlines a comprehensive, multi‑layer database audit architecture for financial systems, covering principle‑of‑least‑privilege service accounts, database activity monitoring, log correlation, optional code scanning, API injection detection, regular security drills, and development‑side safeguards to ensure traceable, compliant data access.
This article explains the Java BigDecimal class, its internal fields and methods, demonstrates a test case, and analyzes the add operation to show how scaling numbers to long integers preserves exact precision in financial calculations.
This article explains why Java's BigDecimal class ensures loss‑free precision in financial calculations by examining its internal fields, demonstrating usage with a test method, and walking through the add method's scaling logic and integer‑based computation.
This article explains why floating‑point types cause precision errors in financial calculations, reveals four common BigDecimal pitfalls—including constructor misuse, equality comparison, division precision, and string conversion—and provides concrete best‑practice solutions such as using String constructors, compareTo, specifying scale, and appropriate formatting methods.
This article explains why using floating‑point types with BigDecimal can cause precision loss in financial calculations, demonstrates the problem with sample code, analyzes the underlying double‑to‑long conversion, and provides a reusable Java utility class to perform accurate arithmetic with BigDecimal.
This article explains the importance of selecting the right graph database for knowledge‑graph systems, compares major graph‑DB options, outlines essential characteristics of effective benchmarks, and describes the development of a financial‑graph benchmark based on LDBC standards.
The article provides a comprehensive overview of payment‑system clearing and reconciliation, detailing fund inflow/outflow matching, reconciliation center functions, various one‑to‑one, many‑to‑many and one‑to‑many matching rules, data import, error handling, and auxiliary modules such as balance entry and abnormal data recovery.
This article provides a comprehensive technical overview of financial‑grade database disaster recovery, covering backup and recovery methods, MySQL replication options, automatic failover architectures, distributed transaction protection, and application‑level stress mitigation techniques.
This article examines financial sector database disaster recovery, defining disaster recovery and backup, analyzing current practices and requirements, reviewing market trends, and detailing various distributed database disaster‑recovery architectures such as single‑center, intra‑city active‑active, and multi‑site three‑center solutions.
This article details a financial company's exploration of Apache Flink for real‑time processing, covering its unique business constraints, end‑to‑end data pipeline, single‑table and multi‑table use cases, implementation challenges, code snippets, data initialization, testing strategies, and lessons learned.
BigDecimal provides precise arithmetic in Java, but its correct usage requires understanding its internal unscaled value and scale, avoiding the inaccurate BigDecimal(double) constructor, and preferring String or valueOf methods to accurately represent decimal numbers such as 0.1 in financial and e‑commerce applications.
This document presents a comprehensive solution for merchant settlement in joint‑venture (co‑operated) offline stores, describing business models, settlement subject abstraction, billing engine components, settlement workflow, payment collection, and reconciliation architecture with detailed tables and diagrams.
