Case Study: Albert Fensterstock Associates achieves precise credit-risk predictions (8.49% error) with Palisade NeuralTools

Albert Fensterstock Associates - Customer Case Study

Albert Fensterstock Associates, led by Managing Director Albert Fensterstock, worked with Business Backer — a small-business lender that had funded $130M to over 4,000 businesses — to remove guesswork from credit decisions. The challenge was to identify which applicants would repay loans and to set appropriate credit limits; to tackle this they turned to Palisade and its NeuralTools neural‑network software.

Using Palisade’s NeuralTools (and Palisade’s StatTools for testing), Fensterstock built and combined multiple neural models, applied Variable Impact Analysis to select the most predictive factors, and created an ensemble model that cut prediction error to just under 8.49%. The Palisade-driven solution enabled dynamic credit limits, monthly rescoring for early-warning collection actions, and smarter recovery prioritization — improving lending decisions, collection efficiency, and overall profitability.