Stolen by a ringing phone: The hidden criminal economy behind MoMo fraud

Prof. Samuel Lartey

www.pefghana.org

Mobile money has become the invisible infrastructure of everyday life. It powers commerce, remittances, salaries, transport, informal trade and household survival. In Ghana, MoMo is not simply a payment channel. It is the economy moving at digital speed.

Yet within this success lies a parallel economy. A criminal ecosystem that feeds on trust, urgency and technological asymmetry. MoMo fraud has evolved into an organised, scalable and adaptive threat that undermines financial inclusion, erodes confidence and transfers wealth silently from the many to the few.

This article examines the operational anatomy of MoMo fraud, its systemic financial impact, the regulatory expectations under the Bank of Ghana framework, and the institutional and societal response required to contain a threat that now rivals traditional financial crime.

The Scale of the Threat

Mobile money fraud represents a significant and growing share of reported financial crime. Regulatory disclosures indicate that mobile money-related incidents account for approximately one-fifth of all reported fraud cases annually. While reported case counts have shown marginal declines in some years, total financial losses have increased, reflecting higher value incidents and repeated victimisation.

Beyond direct losses, institutions incur secondary costs through customer reimbursements, system upgrades, investigations, compliance reporting and reputational damage. These indirect costs often exceed the value of the stolen goods.

How MoMo Fraudsters Operate:

MoMo fraud is primarily a crime against judgment rather than software. Fraudsters rely on persuasion, impersonation, and urgency to convince victims to authorise transactions. This allows criminals to bypass technical safeguards without breaching core systems. Their operations are mainly human exploitation over system hacking

Call Script Engineering and Behavioural Control

Fraud rings use rehearsed call scripts designed to dominate conversations. These scripts deploy authority claims, false reassurance and time pressure. Victims are discouraged from verifying information and are guided step by step toward compliance.

Data Driven Targeting

Fraudsters analyse transaction flows, agent float behaviour, and user demographics to identify vulnerable targets. High-activity agents, elderly users, new registrants, and small merchants are disproportionately targeted.

Fraudsters infer insider-like knowledge of customer transactions by actively monitoring social media, messaging groups and digital fundraising platforms where users publicly share payment appeals, donation screenshots, MoMo numbers, group savings contributions and update messages, then correlating these visible disclosures with response behaviour, timing patterns and follow-up interactions to identify active wallets, transaction frequency, spending habits, trust networks and periods of heightened vulnerability to social engineering.

Virtual Theft Mechanisms

SIM manipulation, OTP interception, deceptive USSD prompts and fake transaction notifications convert legitimate system features into instruments of theft. The transaction appears valid while the intent is fraudulent.

Real World Impact and Aggregate Losses

Data-driven targeting in MoMo fraud is primarily driven by the systematic exploitation of innocent user behaviour rather than by widespread insider compromise. Fraudsters construct intelligence by observing how users transact, respond and communicate in everyday situations. Through repeated social engineering calls, test messages, fake reversals and impersonation attempts, they identify active numbers, frequent transactors, high-pressure responders and individuals inclined to trust authority.

High-activity agents, small merchants, elderly users, and new registrants unintentionally disclose valuable cues through response speed, language, transaction familiarity, and procedural uncertainty. What appears to victims as insider knowledge is often the product of disciplined profiling, behavioural analysis, and information voluntarily disclosed during routine interactions, rather than access to protected systems.

While insider threats are not the dominant driver, opportunistic collusion does exist and can materially enhance the effectiveness of fraud when combined with external data. Former agents or subcontractors may retain procedural knowledge of float management, verification steps and peak transaction windows.

Temporary staff may casually share operational routines, escalation paths or system behaviours without malicious intent. In more serious cases, compromised agents may collaborate directly with fraudsters to validate information or expedite withdrawals. Even limited insider insight, when layered with open-source signals, observed behaviour, and social engineering techniques, significantly improves targeting accuracy and success rates.

The fraud economy, therefore, thrives at the intersection of human transparency, procedural familiarity and occasional insider leakage rather than systemic institutional failure.

MoMo fraud generates layered losses across the financial ecosystem. The table below summarises typical aggregate impact patterns observed across reporting periods.

Aggregate Impact of MoMo Fraud by Stakeholder Category

Why Fraud Continues to Succeed

Speed, fragmentation, and delayed reporting create opportunity. Transactions are instant, while investigations are slow. Accountability is distributed among operators, banks, and regulators. Victims often report late, allowing funds to be laundered through multiple wallets. Weak agent supervision and inconsistent enforcement further widen exposure.

Prescribed Regulatory Compliance Alignment

Regulatory Expectations

Under the Payment Systems and Services Act and associated directives, the Bank of Ghana expects all mobile money operators, banks, fintechs, and agents to implement risk-based fraud management frameworks proportionate to their respective exposures.

Key regulatory expectations include

• robust Know Your Customer and SIM registration enforcement,
• real-time transaction monitoring and anomaly detection,
• clear escalation and incident reporting timelines,
• customer protection and dispute resolution mechanisms,
• board-level oversight of fraud risk,
• regular regulatory reporting and audits

Failure to comply exposes institutions to sanctions, license restrictions and reputational consequences.

Compliance in Practice

Institutions must treat MoMo fraud as a prudential risk, not a customer service issue. Fraud controls should be embedded in governance, technology, operations and staff incentives. Regulatory compliance should be demonstrable through documented policies, tested controls and audit trails.

Proposed MoMo Fraud Risk Framework for Institutions

A practical institutional framework should be built on five integrated pillars.

1. Risk Identification

Map fraud typologies across customer journeys, agent operations, SIM lifecycle and transaction flows. Identify high-risk user segments, transaction thresholds and behavioural anomalies.

2. Risk Assessment

Quantify exposure using frequency, value and velocity metrics. Classify risks by impact and likelihood. Align risk appetite with board-approved thresholds.

3. Risk Mitigation

Deploy layered controls, including behavioural analytics, transaction velocity limits, biometric authentication, agent supervision protocols and customer verification checkpoints.

4. Monitoring and Detection

Implement real-time alerts, machine-learning pattern recognition, and cross-network intelligence sharing. Monitor emerging fraud trends continuously.

5. Response and Recovery

Enable rapid account freezing, fund tracing, customer notification and regulatory reporting. Maintain clear recovery and reimbursement policies.

This framework should be reviewed annually and stress tested regularly.

Continuous Awareness, Training and Media Engagement Strategy

Fraud prevention fails without education. A structured national awareness and training program is essential.

Recommended Actions

1. Establish quarterly fraud awareness campaigns coordinated across telcos, banks and regulators
2. Conduct mandatory annual fraud training for agents and frontline staff
3. Use radio, television and digital media in multiple local languages
4. Publish anonymised fraud trend reports for public education
5. Engage community leaders, trade associations and transport unions
6. Create a national MoMo Fraud Awareness Week supported by regulators

Sustained visibility reduces victim success rates more effectively than reactive enforcement alone.

Conclusion

MoMo fraud is not an accidental byproduct of innovation. It is an organised response by criminals to opportunity. As digital finance deepens, fraud will continue to adapt unless governance, technology and human behaviour evolve faster.

Protecting mobile money is protecting economic inclusion. It requires informed users, disciplined agents, accountable institutions, vigilant regulators and active security enforcement.

The ringing phone that steals today can be silenced tomorrow. But only if the ecosystem acts together, decisively and continuously.

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