Mobile banking and IoT platforms with embedded fraud detection
Hosenses is a China-based mobile and backend engineering team building fintech and IoT products. The stack spans iOS/Android client development (Swift, Alamofire, RxSwift) paired with distributed data processing (Spark, Kafka, Hadoop) and machine learning (TensorFlow, PyTorch, scikit-learn) — a shape indicating active fraud detection and real-time risk modeling. The engineering-dominant hiring mix (10 of 12 roles) with minimal recent velocity suggests a stable, product-focused operation rather than rapid scaling.
Hosenses develops mobile banking platforms and IoT systems for Chinese markets, with a primary focus on fraud detection and transaction security. The active project portfolio includes iOS and Android clients for a mobile banking product, WeChat mini-program interfaces, IoT scheduling systems, and GIS-based operations frontends. Backend services run on Spring Boot and Spring Cloud atop MySQL and Oracle, with real-time fraud detection pipelines built on Kafka and Spark. The company operates as a lean engineering team of ~4 full-time staff, concentrated in Fuzhou, Fujian Province.
iOS (Swift, Alamofire, RxSwift), Android, Spring Boot/Cloud backend, Kafka, Spark, Hadoop for data processing, TensorFlow and PyTorch for ML models, MySQL/Oracle databases, and Redis caching.
Mobile banking client apps (iOS/Android), fraud detection systems and real-time risk models, IoT production scheduling systems, WeChat mini-programs, and GIS-based operations frontends.
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