AI Improves Profitability at Paraguay Bank
公司规模
1,000+
地区
- America
国家
- Paraguay
产品
- H2O Driverless AI
- IBM SPSS Software
- IBM Power System AC922
技术栈
- R
- H2O
- Openscoring.io
实施规模
- Enterprise-wide Deployment
影响指标
- Customer Satisfaction
- Productivity Improvements
- Revenue Growth
技术
- 分析与建模 - 机器学习
- 分析与建模 - 预测分析
适用行业
- 金融与保险
适用功能
- 商业运营
- 销售与市场营销
用例
- 需求计划与预测
- 预测性维护
服务
- 数据科学服务
- 系统集成
关于客户
Visión Banco is a financial institution based in Asunción, Paraguay. The bank provides a range of financial services to small and micro-sized companies in its home country. These services include credit card services, remittances, utility and tax collection services, pension plan contribution plans, and payment transfer services. The bank's data scientists were performing business intelligence using traditional techniques, such as dimensional modelling and moving data to a warehouse using extract, transform, and load (ETL). However, the team was looking to expand its services and offers to customers, easily determine credit risks, and do so with accuracy and speed. They also wanted to enhance their practices by implementing predictive analytics, such as to predict customer payment default or churn.
挑战
Visión Banco, based in Asunción, Paraguay, provides financial services to small and micro-sized companies in its home country. The bank was looking to expand its services and offers to customers, easily determine credit risks, and do so with accuracy and speed. It also wanted to enhance its practices by implementing predictive analytics, such as to predict customer payment default or churn. However, the bank was facing challenges in scaling these operations without a new tool or plan. The data science team first hired an external consultant who developed a model using IBM SPSS Software, a process that took a year. Then the team started using open source tools R, H2O, and Openscoring.io, which allowed the data scientists to deploy models in Predictive Model Markup Language (PMML) format—an industry standard for data models. Yet predictive analytics were still taking considerable time and effort.
解决方案
To address these challenges, Visión Banco used H2O Driverless AI, H2O.ai’s automatic machine learning platform. H2O Driverless AI empowers data scientists and data engineers to work on projects faster and more efficiently by using automation and state-of-the-art computing power to accomplish tasks that otherwise can take months. Deployment can potentially be reduced to hours or minutes by delivering automatic feature engineering, model validation, model tuning, model selection and deployment, machine learning interpretability, time-series, natural language processing (NLP), and automatic pipeline generation for model scoring. At Visión Banco, the H2O software runs on IBM Power System AC922. The bank is currently performing additional testing in preparation to migrate or convert all of its models to Driverless AI. It’s starting by evaluating historical data and soon will move fresher data in to verify the results.
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