Case Studies: Telecommunications

Case Study

Telecommunications: Contact Centre Fraud Prevention

A leading telecom provider offering mobile and fixed-line services encountered fraudulent activities within its contact center. Agents responsible for customer verification and order processing faced challenges with bad actors impersonating small business employees, leading to unauthorized transactions and revenue loss.

The Approach

Seeking to reduce the revenue leakage from these unauthorized transactions, Acquire.AI set out to identify the areas for improvement and support the transformation of security processes.

Acquire.AI has a proven framework for assessing and diagnosing areas for improvement, then recommending solutions from a deep panel of expert partners and from that co-creating business cases and implementation strategies that we tailored to the telecom provider’s needs.

The Challenge

• Inadequate CRM controls allowed unauthorized order submissions and account modifications.
• Existing security measures like one time passwords (OTP) and business registration checks were insufficient against social engineering.
• Agents were remunerated on the number of sales they processed and had the capability to alter sale prices and process orders post-shift, compounding the risk of internal fraud.

Our Solution

To begin mitigating the revenue risks, we identified and began to implement a multifaceted AI-driven approach that enhanced identity verification and transaction monitoring.

Advanced Identity Verification: Phase 1

• Focused on small operational and system improvements. Operationally, requiring the caller be put on hold whilst the agent obtains a consent to the order by the account holder before submitting.
• From a system perspective, locking down the agent login system to only allow them a single active login at a time.

Advanced Identity Verification: Phase 2

• Leveraging voice biometrics to verify caller identities, significantly reducing impersonation fraud.

Behavioral Analytics

• Utilized machine learning to analyze transaction patterns and flag irregularities, prompting immediate reviews of suspicious activities by a specialist team before fulfillment.

Identified Benefits

• 90%+ fraud reduction: More than 90% reduction in socially engineered fraudulent transactions, delivering a direct impact on reducing revenue leakage.
• Enhanced security: The strengthened security protocols led to a notable decrease in unauthorized account changes, further protecting customer information and assets.
• Improved trust: The new system will not only bolster security but also build customer trust, resulting in improved customer satisfaction.

Discover how AI can secure your contact center against fraud.