More Accurate, Real-time Risk Score with Fast Time-to-Market
公司规模
1,000+
地区
- Africa
- America
国家
- South Africa
产品
- Airvantage Prepaid Airtime Advance System (PAS)
- H2O Driverless AI
技术栈
- AI
- Machine Learning
实施规模
- Enterprise-wide Deployment
影响指标
- Customer Satisfaction
- Revenue Growth
技术
- 分析与建模 - 机器学习
适用行业
- 电信
适用功能
- 销售与市场营销
用例
- 质量预测分析
服务
- 数据科学服务
关于客户
Airvantage is a leading cellular telecommunication provider based in South Africa. The company operates in over a dozen countries across Africa and the Americas, offering advanced financial products and services. One of their key offerings is the Prepaid Airtime Advance System (PAS), which allows Mobile Network Operators to advance airtime, data, or mobile money to their subscribers. The system uses AI to deliver proprietary profiling and a dynamic rules engine for flexible advancing, revenue maximisation, and customer loyalty. The risk associated with advancing credit is borne directly by Airvantage, making it crucial for them to accurately assess the risk associated with each advance.
挑战
Airvantage, a South African cellular telecommunication provider, was facing a challenge with its Prepaid Airtime Advance System (PAS). The system, which advances airtime, data, or mobile money to subscribers, was using a series of static business rules to make airtime advance decisions. However, these rules were overly cautious, leading to a high number of false negatives - refusing credit to desirable customers. Airvantage needed a solution that would allow them to accurately assess the risk of advancing credit to their subscribers, without unnecessarily declining potential customers. They sought a data science toolkit that could help them build a more accurate risk model, and after evaluating over 30 toolkits and platforms, they decided to use H2O Driverless AI.
解决方案
Airvantage chose to use H2O Driverless AI to address their challenge. The company was impressed by H2O.ai's focus on engineering and solution-building, as well as the support offered by their team of engineers and data scientists. Using H2O Driverless AI, Airvantage was able to reduce their development cycles from weeks to hours, and built their first production model within a month of completing the evaluation. The model was deployed with live A/B testing to continue to test in-place. The ease of deployment offered by H2O Driverless AI MOJOs allowed the team to quickly tune the model to achieve the best results. The solution is currently deployed on client premises to lower costs and respect the sensitive nature of their subscriber data sets.
运营影响
数量效益
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