On May 3rd, 1978, the earliest ever case of a ‘spam’ email was sent, marking an important date in the history of spam. This unsolicited email was sent to 393 users on ARPANET—the early forerunner of the internet—by a marketer promoting an upcoming product presentation by the Digital Equipment Corporation. It was reportedly not well received.
Over 40 years later and it’s estimated that unsolicited spam emails account for up to 90% of all email messages today, bombarding users and often exposing them to fraudulent activity that can damage business revenue and create very real personal challenges for individuals.
The danger of spam is that it provides a relatively easy way for fraudsters to target vulnerable systems and individuals, necessitating an adaptive, scalable fraud protection response that can meet the challenge of this high-volume environment.
Why is it called spam?
The history of spam and junk mail is now over 40 years old, but the term only entered the Oxford English Dictionary in 1998.
The term ‘spam’ originally (and still does) refer to a popular type of luncheon meat launched in the early 20th century, and is a shortened term for the phrase ‘spiced ham’, and ‘shoulders of pork and ham’.
The pathway to it becoming a catch-all term for unsolicited communication is a winding one. In the 1980s, a popular sketch by celebrated comedians Monty Python included an absurd song that celebrated “spam, spam, spam, wonderful spam.” The term was picked up by various digital communities in the 1980s, and gradually expanded to mean communications or data that flooded chats or platforms.
This eventually evolved to spam becoming a term that covered everything from unwanted and unsolicited promotions to mass-deployed unethical and fraudulent communications.
An evolving landscape of fraudulent communications
Of course fraud has a long and ignoble history in society, costing an estimated USD5tril to global economies annually today. That’s a huge global challenge of which spam plays an increasingly important part.
This fraudulent activity is a particular difficulty for the communications industry, something we’ve witnessed first hand at Neural Technologies over 20 years of delivering effective solutions to telecommunications partners. Communication service providers (CSPs) face an uphill struggle in how to stop spam.
The sheer volume of communications delivered in our modern world means identifying and preventing spam is increasingly challenging. Over 138 billion spam emails are estimated to be sent every single day. Legacy digital platforms find it increasingly difficult to effectively filter out that huge volume of spam.
Of course spam isn’t just limited to email applications. Spam text messages and digital messaging services are a growing risk for fraud protection, with sophisticated fraud tactics targeting users and businesses. There were an estimated 781 billion text messages sent every month in 2017, with internet messaging services likely far outstripping those message volumes. CSPs face an increasingly challenging landscape of managing fraud risks from text messages and spam communications.
This rapidly expanding volume of communications is a major driver behind Neural Technologies’ use of machine learning (ML) and artificial intelligence (AI) to deliver solutions to provide protection against the danger of spam and fraud.
Unlike static rules-based systems, ML/AI can rapidly adapt to changing threats and risk profiles, identifying emerging risks and responding to tackle them. That means no waiting for risk analysts to identify new threats then implementing new rules to address them, just an adaptive solution that meets changing needs.
AI/ML also offers the ability to quickly analyze high volumes of data, ensuring a scalable solution to fraud protection that is uniquely suited to tackling the danger of spam and fraudulent communications.
More than 40 years on from the first spam email, the reality is that spam is persistent and growing. Preventing spammers from sending emails and messages is likely impossible. That means an effective solution must include an ability to quickly identify these threats before they trigger revenue loss to businesses, or personal loss to customers.
While other companies struggle to realize the promise of machine learning solutions, Neural Technologies offers a powerful and effective platform with extensive deployment experience across the telecommunications industry. That means scalable response to spam and fraudulent communications with genuine real-world results.
Get in touch to see how our machine learning and artificial intelligence experience can enhance your fraud protection and better protect your customers.
