Fraud tactics are evolving quickly, but the bigger challenge for fintechs and banking organizations is how support teams respond when those scams reach the contact center.
While new fraud types are emerging, leading organizations are focusing less on the attacks themselves and more on building support operations that can detect and stop fraud during live customer interactions.
The Five Emerging Fraud Types Raising the Danger Level
These attack types are drawing increased attention from fintech risk leaders because they are both difficult to detect and highly persuasive for customers.
1. AI Voice-Clone Impersonation
Voice cloning tools allow fraudsters to replicate the voice of a family member, company representative, or authority figure. Some scams involve callers pretending to be a kidnapped relative or trusted institution, creating intense urgency that pressures victims to send money or share sensitive account information.
2. Real-Time Deepfake Customer Calls
AI voice synthesis can now generate convincing deepfake voices during live conversations with support agents. This allows attackers to impersonate legitimate customers while interacting with the contact center, making traditional identity verification methods much less reliable.
3. Authorized Push Payment (APP) Manipulation
In these scams, customers are convinced to initiate transfers themselves while being coached by fraudsters. Because the payment is technically authorized by the customer, these cases are significantly harder for financial institutions to reverse or recover.
4. AI-Generated Phishing and Social Engineering
Generative AI allows attackers to create extremely convincing phishing messages at scale. These campaigns often mimic legitimate company communications and trigger waves of account takeover attempts and fraud-related support calls.
5. Synthetic Identity Accounts
Fraudsters now use AI-generated documents and identity data to create synthetic customers who pass onboarding checks. These accounts may behave normally for months before being used for large-scale fraud or financial abuse.
The common thread across these attacks is that technology enables the fraud, but human manipulation completes it.
Support agents are often placed in situations where fraud must be identified and stopped during the interaction itself.
What Weak Organizations Get Wrong
When fraud incidents are reviewed after the fact, similar operational gaps tend to appear.
Common weaknesses include:
- Authentication that relies on knowledge-based questions such as date of birth or address
- Limited training for agents on recognizing social engineering tactics
- Fraud risk signals that are not visible inside the agent desktop
- No real-time fraud scoring during customer interactions
- Slow or unclear escalation paths when fraud is suspected
- Fraud prevention teams operating separately from customer support teams
These gaps make it easier for fraudsters to manipulate support workflows and convince agents to override safeguards.
What Strong Fintech Teams Are Doing Instead
Leading fintech organizations are redesigning support operations so fraud can be detected and stopped during live customer interactions.
Eliminate Knowledge-Based Authentication (KBA)
Traditional authentication methods based on personal information are increasingly ineffective.
Modern fraudsters often have access to stolen identity data.
Instead, many fintechs are adopting layered authentication methods such as:
- Voice biometrics
- Device fingerprinting
- Behavioral authentication
These approaches make it far more difficult for attackers to impersonate customers during support interactions.
Provide Real-Time Fraud Signals to Agents
Forward-thinking organizations are integrating fraud intelligence directly into the agent desktop.
This allows support teams to see risk indicators immediately during a conversation.
Examples include:
- Fraud risk scores displayed inside CRM tools
- Alerts triggered by suspicious account activity
- Step-up authentication requirements during calls
Giving agents this visibility dramatically improves their ability to detect social engineering attempts.
Scam Detection During the Conversation (Real-Time AI Intervention)
Some fintech organizations are now using AI to monitor live calls and chats for potential scam indicators. These systems analyze signals such as:
- Customers repeating scripted phrases.
- Signs that someone may be coaching them in the background.
- Urgent transfer requests tied to emotional distress.
- Language patterns commonly associated with authorized push payment (APP) scams.
When risk signals appear, the system can:
- Alert the agent in real time.
- Trigger a fraud escalation workflow.
- Temporarily delay high-risk transactions while the situation is reviewed.
This approach reflects a broader trend toward AI-assisted agents, where AI surfaces risk signals in the moment while humans make the final judgment call.
Scam Coaching Detection
In many modern scams, the fraudster is actively coaching the victim, either sitting next to them or guiding them on another phone during the interaction.
New detection systems are designed to identify signals such as:
- Customers pausing frequently to receive instructions.
- Repeated, scripted responses.
- Language patterns that match known scam playbooks.
Some banks also train agents to ask disruption questions, such as:
“Is someone asking you to say these answers?”
Questions like this can interrupt the scammer’s control of the conversation and prompt the customer to reconsider the situation.
This proactive approach helps stop scams before funds leave the customer’s account, combining AI detection with human judgment at the moment it matters most.
Voice Deepfake Detection
This is a newer capability that is rapidly emerging.
Some fintech organizations are beginning to test tools that analyze signals such as:
- Audio artifacts within the recording.
- Voice synthesis markers that can indicate AI-generated speech.
- Inconsistencies in speech patterns that differ from natural human voices.
These systems aim to detect AI-generated voices during authentication, helping identify potential deepfake fraud attempts.
Adoption is still in the early stages, but the technology is expected to advance quickly as voice-based fraud becomes more sophisticated.
The Bottom Line
Fraud threats are increasingly intersecting with the contact center, where support teams often become the last line of defense before a scam succeeds.
Fintechs and banks that stay ahead of this shift are treating fraud prevention as a core contact center capability. That means giving agents the right tools, training, and real-time risk signals so scams can be identified and stopped while the interaction is happening.
If you are evaluating how well your support operation is equipped to handle these emerging fraud risks, schedule a CX Strategy Call with our team.
