A selection of questions we have answered in our projects in the field of finance:
Which customer has an affinity for a particular product?
Next best offer: determining customer interest based on historical conversions and demographic information. The resulting affinity score is the knowledge base for campaign management in sales and the reason for a significant increase in response rates.
How can fraud be detected earlier?
Analysis of anonymized transaction data based on the Benford Law to detect irregularities in transactions. The algorithm detects conspicuous values and triggers an alert. The negative effects of fraud have thus been reduced.
How can the risk analysis process be more automated?
Calculation of the individual credit default risk of customers using simulations and statistical models. Employees are relieved of this routine work and at the same time the forecast quality can be further optimized.
Which customer is considering changing his bank?
Churn prevention: using data science to identify earlier which customer you are in danger of losing. Link different data sources for a time-to-event forecast that enables you to proactively target the customer and persuade them to stay.
How can the prediction of KPIs be further improved?
Further develop the existing forecast using an ensemble modeling approach that uses the best forecast model for each KPI. Implementation of this forecast in a user-friendly, interactive Shiny app.
What does the appropriate IT infrastructure for data science in a strictly regulated environment look like?
Concept development and implementation of a high-performance IT infrastructure regarding the strict regulations and requirements regarding the operating concept and security.
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We look forward to exchanging ideas with you.
Your expert on Data-Science-Projects:
Lutz Mastmayer
projects@eoda.de
Tel. +49 561 87948-370