Success is Never Accidental

    • Using decision tree, regression & neural network models to predict risk of churn for different customer types on a daily, weekly and monthly basis
    • Forecasting customer level profitabilty to optimize potential offers that customers are eligible for
    • Using social network analysis to identify leaders and influencers within the customer base. Measure and predict how social influences impacts contagious customer behavior
    • Quantitative analysis of call-detailed-records and events data to improve event-driven marketing campaigns ROI
    • Enabling a test-and-learn platform for continous improvement of below-the-line marketing offerings
    • Short Term and Long Term electricity demand forecasting utilizing Linear Regression, ARIMAX and multiple times series methods
    • Analytical foundation set-up for pricing, hedging and purchasing decision making in the electricity market
    • Applying statistical techniques for core customer segmentations for a Utilities client
    • Development of a systematic scoring routine integrating customer behavior, potential value and profitability to re-align pricing policies for a local bank
    • Delivery of core personal banking segmentations for a multinational bank including value, behavioral and attitudinal dimensions
    • Re-design and development of a pre-approved personal loan process for a multinational bank
    • Delivery of a cash loan application scorecard consolidating internal and credit bureau information
    • Offer optimization and selection of best offer based on customer behavior, credit bureau information and geo-tagged features
    • Quantitative analysis for improving real-time and event based campaign performance
    • Behavioral customer segmentation for the SME (Small and Medium Enterprise) segment of a multinational bank
    • Risk profiling for pricing in auto-insurance
    • Product Cross-Sell prediction and Scoring of the base for targeting
    • Decreasing loss ratio by the increase in fraud detection and reduce false positives
    • Constructing real-time fraud detection and assessing risks during the underwriting process
    • Below the Line Campaign Management
    • Assessing and Improving Campaign Targeting Criteria and Response Measurement
    • Sales Propensity Modeling
    • RFM ( Recency / Frequency / Monetary ) Analysis for Service Propensity