ML Superheroes Vs Fraudsters Inc.

Machine Learning (ML) models are viewed as the superheroes of fraud prevention. Let’s understand why ML is taking over from rules in preventing frauds, money laundering and scams.

Why rules don't suffice:

·   Fraudsters are smart: Fraudsters learn and understand which patterns are tracked. And fraudsters are using AI & ML!

·   How many rules: Over time every incident has become a rule and systems have close to 400 rules and are unmanageable

·   Alert / Case flood: Many clients are running short of staff to review cases generated due to the growing volumes

Why ML Models are the superheroes we seek:

·   Adaptability: They learn from new data, evolving to new techniques

·   Manageability: ML model efficiency can be enhanced based on training with new data and does not need increase in staff

·   Reduce False Alarms: Fine tuning helps minimize false positives and improve true positives

So how do you keep a model from flipping to the dark side:

·   Explainability: Regulators need explainability as consumer interest needs to be protected

·   Governance: Model & data governance is key to ensuring there is no drift or bias in the model

ML models and their accuracy are our best allies to secure payments. Explainability & Governance not only builds trust, but also help uncover biases, discover data issues, and refine model performance.