Generative AI Takes Center Stage 

The State of Alloy Fraud Report 2026 found that 67% of respondents reported an increase in fraud attempts over the past year - with over 50% of it involving artificial intelligence, according to Feedzai.

Fraudsters are embracing generative AI to create new scams. Voice synthesis tools can now clone a customer's voice from a few seconds of audio captured from social media. Every image, video, and piece of personal information a customer uploads to the internet is becoming a weapon that can be used against them. 

What used to take hours of manual work can now be done in minutes with AI tools that create realistic identity packages, complete with matching addresses, job histories, and social profiles. These synthetic identities are advanced enough to easily slip past traditional KYC controls, which were built to catch human-made mistakes. 

Organized crime networks are using these tools to orchestrate coordinated attacks across institutions. These sophisticated operations run fraud rings with mule networks, account takeover schemes, and money laundering operations, all enhanced by AI to help them evade traditional detection methods. Traditional fraud prevention approaches built for a different era are having a hard time keeping up.  

What Fraud Trends Are You Fighting in 2026?

Fraud trends topping the charts for financial institutions in 2026 are defined by these patterns, and each one requires new defensive strategies. 

AI-Powered Social Engineering Scams

This currently represents one of the largest and fastest-growing threat factors for institutions in the finance industry. First-party fraud, where customers are tricked into authorizing transactions themselves, has become a major challenge. 

We see this take effect in authorized push payment fraud, investment scams, romance scams, and more. AI makes these acts more convincing, more targeted, and easier to scale than ever before. What makes these attacks particularly tricky is that they bypass traditional fraud controls because the customer approves the payment themselves.

Financial Institutions have to find ways to protect their customers from fraudulent acts, manage liabilities while ensuring that their policies and interventions don’t drive users away. 

What This Means:

Banks must assume that customers can be socially engineered and design systems that detect manipulation, slow high-risk actions, and intervene at the moment of deception. 

What to Do:

The most effective approaches combine technology, process, and customer behavior change. 

• Strengthen authentication and authorization to make it hard for manipulated customers to authorize fraud
• Reinforce behavioral and transactional fraud detection - banks must detect intent anomalies, not just credential misuse
• Deploy smart friction - friction at the right moment to interrupt scams without harming good customers
• Enhance employee, call center, and customer controls and education to lessen susceptibility to manipulation
• Explore scam intelligence and collaboration to stay ahead of evolving tactics

Synthetic Identity Fraud

The State of Alloy Fraud Report found that synthetic identity fraud was the most commonly observed fraud type among institutions over the past 12 months, with 44% of 500 surveyed fraud and risk leaders reporting it. This not only highlights where attackers are currently focusing their efforts but also offers valuable insight into the threats your organization may face in the year ahead.

AI has made it easy to create synthetic identities that pass identity verification. These fabricated personas establish credit histories, open accounts, build trust over months, then execute coordinated fraud across multiple institutions. It’s scary how well-orchestrated these attacks are becoming. However, it reinforces the need for fraud managers to take extra measures in fraud detection and overall prevention. 

What This Means:

Synthetic identity fraud is a slow-burn crime. Banks must shift from point in time KYC to identity lifecycle risk management, where trust is earned over time and constantly re-evaluated.

What to Do:

Develop controls that detect inconsistencies and intent over time.

• Harden identity proofing at onboarding by looking at impossible combinations
• Treat thin files as high risk by default
• Develop longitudinal monitoring to detect fraud that emerges months later (this is where most banks fail)
• Install strong controls around credit line management to prevent bust-out losses
• Consider consortium and cross-industry collaboration to catch synthetics before they scale

Account Takeovers (ATO) Fraud

The report also found that ATOs accounted for 42% of the most frequent cases in the previous year, second only to synthetic identity fraud. AI-enabled social engineering is dramatically increasing ATO success rates, and we also see contact centers being targeted with voice-cloning attacks that manage to slip by authentication and voice biometric processing.

Phishing has also become more personalized. These AI tools are being equipped by bad actors to craft convincing messages that reference real transactions, real relationships, and real-life scenarios. It’s becoming more challenging to differentiate fabricated cases and scenarios from real-life circumstances. 

What This Means:

ATO prevention is about continuous trust.  Banks must monitor who is using the account, how they behave, and what they try to do - then intervene before money moves.

What to Do

Banks should assume that credentials will be compromised and focus on detecting malicious access and intent in real time.  Best practice approaches layer identity, behavior, device, and transaction controls across the entire account lifecycle.

• Solidify login and authentication with adaptive multi-factor authentication (MFA) and phishing-resistant MFA (FIDO2/Passkeys)
• Install device and session intelligence tracking to detect attackers who log in successfully
• Consider behavioral biometrics to identify non-owner behavior in real time
• Step up account change monitoring controls to stop the “lock out and drain” phase
• Upgrade transaction-level ATO detection to prevent monetization
• Educate customers, call center, and assisted channel to close the human backdoor risk

The New Defense Playbook for 2026

Financial institutions need to learn how to adjust to constantly evolving malicious threats. Some major defense plans to consider for 2026 are:

• Anticipatory and Agentic AI: Anticipatory AI predicts risk in real time, during account opening, at login, or before a payment is processed, by analyzing behavior and past patterns. Agentic AI acts like a smart assistant for analysts, suggesting what to investigate, drafting recommendations, and automating routine tasks.
• Consortium Intelligence and Signal Sharing: When one institution spots a new scam, everyone benefits. When properly integrated, community signals can help trigger rules and alerts, reducing detection time significantly. RippleShot and others are building systems that could promote such implementation and enable real-time community intelligence. 
• Behavioral and Graph Analytics: These tools help banks spot fake identities and coordinated fraud rings that normal transaction checks often miss. By looking at how accounts, devices, merchants, and sessions are connected, banks can see patterns that reveal organized fraud.
• Modern Identity Standards (Passkeys and FIDO): Passkeys and FIDO logins make accounts phishing-resistant and greatly reduce account takeovers. Banks that adopt them early see clear drops in ATO rates. The key is a careful rollout: start with high-risk customers, require multiple authenticators, and ensure recovery processes are secure.

Rippleshot is expanding the use of AI agents and automation to deliver real-time intelligence, decision support, and better operational efficiency for financial institutions. Our solutions deploy fast (up and running in 2 weeks), help stop fraud, and also evolve to address future challenges. Reach out to us today to find out more.