Microsoft responsible machine learning capabilities build trust in AI systems, developers say

Anyone who runs a business knows that one of the hardest things to do is accuse a customer of malfeasance. That’s why, before members of Scandinavian Airlines’ (SAS) fraud detection unit accuse a customer of attempting to scam the carrier’s loyalty points program, the detectives need confidence that their case is solid.

“It would hurt us even more if we accidentally managed to say that something is fraud, but it isn’t,” said Daniel Engberg, head of data analytics and artificial intelligence for SAS, which is headquartered in Stockholm, Sweden.

The airline is currently flying a reduced schedule with limited in-flight services to help slow the spread of COVID-19, the disease caused by the novel coronavirus. Before the restrictions, SAS handled more than 800 departures per day and 30 million passengers per year. Maintaining the integrity of the EuroBonus loyalty program is paramount as the airline waits for regular operations to resume, noted Engberg.

EuroBonus scammers, he explained, try to gain as many points as quickly as possible to either book reward travel for themselves or to sell. When fraud occurs, legitimate customers lose an opportunity to claim seats reserved for the loyalty program and SAS loses out on important business revenue.

Today, a large portion of leads on EuroBonus fraud come from an AI system that Engberg and his team built with Microsoft Azure Machine Learning, a service for building, training and deploying machine learning models that are easy to understand, protect and control.