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Predicting the outcomes that did not happen yet make your plans more effective.
Our data scientists apply Advanced Analytics techniques like simulated annealing, machine learning, artificial neural networks or custom made algorithms to guarantee that you make smarter business decisions on your most significant real-world challenges.
Where access to Big Data is available, the integration of Big Data Analytics platforms has been a successful approach to perform sophisticated descriptive and predictive analytics and gain competitive advantage.
But not all organizations are prepared to handle or provide Big data. With our expertise we enable you to uncover valuable and new insights from your standard data sources like data warehouses, application logs, transactions or other systems.
What are your business challenges?
Some examples that we address:
Customer acquisition
- Default Risk - Should I approve this credit line?
- Personalization - Who is the best target for my campaign?
Customer usage and growth
- Personalization - Which campaign is the most promising one for which customer?
- Growth - Which clients will buy a car and when?
- Targeting - Whom do we approach with a differentiated offer?
Risk and profitability
- Risk Return Profitability - How can we optimize our pricing model?
- Optimization - How can we optimize our scoring models further?
- Risk Mitigation - Apply PufferFish portfolio optimization
Churn
- Who will leave us and when? What should I do to avoid it?
Tools & Techniques
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Articles
Stay up to date and keep yourself informed about advanced analytics trends, best practices and much more. We hope you find these scientific insights relevant for your business.
Why we should not build models like the statisticians
by João Pires da Cruz, October 2016
by João Pires da Cruz, June 2016
by João Pires da Cruz, March 2016
by João Pires da Cruz, March 2016