AI and the Next Wave of Robocalls: Protecting Carriers and Consumers from Sophisticated Voice Fraud

By Tim Ward, Chief Strategy Officer, XConnect

Robocalls are relentlessly targeting consumers and causing mistrust for the telecom industry as a whole. This is a problem that is accelerating as bad actors take advantage of generative Artificial intelligence (AI) to carry out more believable scams.

According to Juniper Research, fraudsters’ ability to innovate robocalling methods will cause mobile users to lose $70 billion globally by 2027. As it stands, these fraudulent and scam calls are already driving substantial financial losses for the entire telecoms value chain, from carriers to consumers. The rise of AI introduces new efficiency to fraudsters’ scams, making it even more likely for them to successfully defraud their victims. This poses a massive problem for the voice industry and puts its reputation at risk as more consumers continue to ignore calls from unknown numbers.

Advancing robocalls is a challenge the voice industry must take a proactive stance on. On the 20th July 2023, the Federal Communications Commission (FCC) announced new rules to tackle robocallers and the rise of sophisticated scams, limiting the number of robocalls placed on landline numbers. These actions, however, have had an undesired effect, with some carriers fearing that they cannot adhere to these new rules and switching off termination into the US as a result. This removes risk but also reduces the footprint of where carriers can terminate traffic.

The FCC’s latest regulations are a necessary step to mitigating robocalls in the US, and action must be taken on a global scale to truly address this rising risk. Deploying effective number information services is essential for not only meeting compliance with the FCC’s latest rules but also keeping consumers safe from unwanted calls.

AI and New Robocalling Risks

Fraudsters are increasingly benefitting from AI to create convincing deep fake robocalls to impersonate business, banking and government executives, or even family members. Consumers are following the instructions of fraudsters and give in to financial demands.

On top of this, scammers are also leveraging AI to rapidly automate calls. This allows them to originate thousands of robocalls in minutes. They can analyse large amounts of data to understand calling patterns and effectively target their victims.

If this trend continues, organisations making genuine calls will witness their business impacted by lower answer rates, driven by consumer distrust of unrecognised calling line identifications (CLIs). This has the potential to cause permanent damage to the reputation of the voice and messaging industries and encourage voice users to migrate to other communications channels.

Restoring trust in CLIs is essential to securing the future of the voice industry and mitigating against fraud and spam calls. This requires reliable and up-to-date numbering data intelligence solutions to eliminate invalid numbers.

Cracking Down on Spam and Fraud

An increasing number of consumers and businesses continue to be majorly impacted by ongoing AI-powered robocalls. National voice infrastructure must implement basic security protocols to keep users protected.

To ensure that all carriers effectively address robocalls, they need to deploy simple and efficient methods to validate CLI and accurately block invalid traffic. They can leverage the following solutions to harden their stance against fraud in voice and protect consumers:

  • Deploying a Dependable DNO List – A Do Not Originate (DNO) list protects users from fraudulent spam calls. The list identifies calls that originate from invalid, unallocated, and/or unused numbers, helping to prevent telecom fraud on known inbound-only and invalid numbers. Regulators across the world are increasingly deploying DNO lists for carriers and enterprises to check numbers against.
  • Leveraging Trustworthy GNR Data – Carriers can also leverage Global Number Range (GNR) data to strengthen their defence against robocalls. Access to real-time GNR data provides organisations with the insight to block or accept traffic based on potentially fraudulent CPN/CLI modification. GNR data can cover thousands of operators across hundreds of destinations. Carriers benefit from visibility into the validity of numbers to identify which number ranges are unallocated, ensuring that their traffic is legitimate and has the potential to reach its intended recipient without being blocked.

Addressing Advanced Robocall Tactics

With generative AI causing a major rise in harmful robocalling, tackling this issue is a top priority. Deploying a comprehensive trusted DNO list and exhaustive GNR data arms carriers with the ability to detect invalid and fraudulent numbers, making it easier for them to protect their consumers and focus on building trust.

Taking proactive action against robocalling is essential to secure the future of the voice industry. GNR and DNO solutions are essential to support the termination of legitimate voice traffic while guaranteeing adherence to the latest robocalling rules.

About the Author

AI and the Next Wave of Robocalls: Protecting Carriers and Consumers from Sophisticated Voice FraudTim Ward, Chief Strategy Officer, joined XConnect in November 2016 to lead the Number Information Services division, with responsibility for sales, marketing and product management, launching a range of innovative services for applications, messaging and interconnect providers that set new standards for access to network, service and user information.

Tim has over 30 years of experience in technical, sales and marketing roles across the telecoms industry.

He is passionate about establishing a level playing field across the industry, with a common set of standards to ensure the highest quality of service. He sees XConnect playing a pivotal role in this and, as such, works with key industry stakeholders and bodies such as MEF and GSMA to drive this agenda forward. Tim can be reached on LinkedIn and at our company website

March 5, 2024

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