Fraud Detection

In the United States, the Federal Trade Commission received more than 2.1 million fraud reports from consumers in 2020, with imposter scams remaining the most common type of fraud reported to the agency.

The second most common fraud category was online shopping. COVID-19 came to make this type of fraud worse. The top categories of online fraud were internet prizes, sweepstakes, and lotteries; accompanied by telephone and mobile services.

Overall, according to reports, consumers lost more than $3.3 billion to fraud in 2020, compared to up $1.8 billion in 2019. Similarly, nearly $1.2 billion of losses reported last year were due to imposter scams, while online shopping accounted for about $246 million in reported losses from consumers.

Per Forbes, the impact of fraud goes beyond financial losses. For a company, it affects customer experience, fraud management operational costs, compliance, brand damage, impacts to conversion and authorization rates.

Considering all the ramifications fraud can have on a company, it is easy to see that its management and damage control efforts require a small army of people. This is where RPA and AI can be of great help.

Given its versatility, RPA can gather information from all the company’s systems, aggregate it, analyze it and, when needed, feed it to an AI engine to detect patterns. At the same time, an army of robots can help manage and bring agility to identifying social media (or email) interactions with customers.

A well-engineered group of robots (aka digital workforce), can alleviate the cost burden of fraud management, ensure compliance, monitor impact to the brand and monitor and analyze the factors for conversion and authorization rates; thus improving them as a consequence.