- Using artificial intelligence and machine learning-powered technology to identify and stop fraudulent orders, PetSmart saved $12 million last year — $4 million in order costs, $8 million in labor, shipping, fines and other costs, reports ZDNet. Since February 2018, the company has already saved $1.5 million.
- PetSmart wanted to move fraud prevention in-house and turned to a tool that aggregates transactions and outcomes and determines the fraud risks of customers to identify nefarious transactions. As the tool’s algorithm becomes familiar with a seller’s business, it learns and improves.
- Preventing fraud also protects the company’s brand and reputation, because customers could associate fraudulent charges with a failure by PetSmart to protect them, according to ZDNet. Tackling fraud in the confines of a business can have rippling effects in industry and society. Information gathered by PetSmart’s fraud prevention program helped uncover a multistate fraud ring, close the murder case of an NYPD officer and further a human trafficking ring investigation, report ZDNet.
As malicious actors become more savvy, so too must the technology protecting a businesses network and customers. Fraud has increased steadily since 2012, and in 2017, 84% of companies experienced a fraud incident. The theft, loss or attack of information was the most prevalent form of fraud.
The perpetrator in around 58% of cases is a company insider, so businesses need to manage security within and outside of their networks. AI and ML are far more proficient at analyzing transactions and business events to pinpoint unusual or fraudulent activity than human cybersecurity workers, leading to a proliferation of technologies grounded on the advanced technologies.
More companies are focusing on security solutions in the mobile space as consumers turn to mobile platforms and payments. But sussing out effective applications in the space, however, can be difficult when an already crowded vendor landscape begins stamping AI and ML on most security products.