Having the most cutting-edge machine-learning algorithms in Silicon Valley, IceKredit constantly explores and pursues machine-learning (including deep-learning applications) in the fin-tech field. Currently, our technological reserves in terms of machine-learning (refers to the core algorithm codes independently developed by our modeling team) includes but are not limited to:

  • Single algorithm models such as Random Forest, Neutral Network, Support Vector Machine, Decision Tree and the bagging algorithms of these models
  • Stacking methods for various basic algorithms
  • Gradient boosting machine algorithm for Decision Tree
  • Semi-supervised learning algorithms based on SVM
  • Natural Language Processing (NLP)


On the other hand, IceKredit uses advanced technologies and best-in-class third-party data resources to provide customized services and solutions specifically tailored for each client. We offer a complete cycle of one-stop services for clients from Precise Marketing to Customer Retention. Upon obtaining the latest data from clients, IceKredit produces effective analytics to customize advanced models using big data technology and machine-learning algorithms. Once models are developed, IceKredit can then predict future performance results and design tailored solutions to fulfill various client needs.

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