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Fraud isn¡¯t a new challenge for banks, but the increasing sophistication of schemes and scams is leaving financial institutions¡ªparticularly smaller ones¡ªscrambling to protect themselves.

Beyond being a persistent threat, fraud is also expensive. According to a 2024 , for every $1 lost to fraud, US banks spend $4.41 in related expenses, including legal fees and recovery¡ªa 9% year-over-year increase. And the costs go beyond dollars: 79% of respondents in the study said fraud makes it harder to win customer trust.

AI is getting smarter¡ªand that¡¯s helping banks stop fraud before it happens. For smaller banks that don¡¯t have large, in-house fraud teams, the contact center can be a powerful first line of defense. That¡¯s why it¡¯s so important to have an AI-enabled contact center partner¡ªone that can detect suspicious activity, respond in real time, and protect customers when it matters most.

This blog post explores:

• The evolving fraud landscape for community and regional banks
• The evolving fraud landscape for community and regional banks
• How an AI-enabled contact center partner like ¾ÅÉ« Connect can help banks fight fraud, reduce customer loss, improve customer fidelity, and limit liability

The Fraud Landscape in Banking

Fraudsters rely on methods like spoofing, social engineering, and data harvesting to carry out their schemes. In the earlier days of fraud detection, banks took a more reactive approach, using methods like manual account review and rules-based logic to identify suspicious activity. But these methods have pitfalls, including false positives, detection delays, and limited contextual analysis. Addressing fraud only after it has occurred can lead to significant financial losses and reputational damage.

However, limited financial resources can make it challenging for smaller banks to allocate funds for fraud-detection technology. Advanced fraud-detection systems can be expensive, and may not integrate with banks¡¯ legacy systems and more limited IT capabilities. And even if the technology is within reach, implementation requires skills and expertise in data science, cybersecurity, and financial fraud¡ªnot to mention the cost of training employees on fraud detection.

What Are Some Common Fraud Schemes That Threaten Banks?

Phishing and Social Engineering: Fraudsters use deceptive emails, phone calls, or text messages to trick employees or customers into revealing sensitive information, such as login credentials or account numbers. This information can then be used for unauthorized transactions.

Pharming: Attackers redirect users from legitimate banking websites to fraudulent ones to capture login details and other sensitive information

Credential Stuffing: Using credentials obtained from data breaches, attackers attempt to gain unauthorized access to bank accounts

Account Takeover: Cybercriminals gain control of bank customer accounts through stolen credentials obtained via phishing, malware, or social engineering, allowing them to conduct unauthorized transactions.

Fake Check Scams: Fraudsters use counterfeit checks drawn on valid bank accounts. These checks are initially accepted by the bank, but the fraudsters disappear with the funds before the scam is detected.

Loan Fraud: Criminals submit fraudulent loan applications using stolen identities or fake documents to secure loans they never intend to repay.

Insider Threats: Bank employees may misuse their access to embezzle funds, manipulate accounts, or conduct unauthorized transactions, either under external duress or for personal gain.

AI Fraud Detection: The Contact Center¡¯s Secret Weapon

Fraudulent schemes may be getting more sophisticated, but so is the AI technology used to fight them. AI systems can now integrate and analyze data from multiple sources¡ªincluding transaction data, user behavior, device information, and external databases?¡ªto provide a comprehensive view of potential fraud risks. This allows for a shift from reactive fraud measures to proactive prevention, intercepting fraud before it reaches the customer. Machine learning, neural linguistic programming, and generative AI models continuously learn and adapt to new types of fraud as they arise, improving their accuracy over time.

Financial institutions are using AI not only to identify fraudulent activity but also to instantly alert fraud detection teams or automatically take actions such as freezing accounts, declining transactions, or requiring additional authentication. AI can predict the likelihood of fraud before it occurs by identifying emerging patterns and trends indicative of fraudulent behavior. These advancements enable banks to stay ahead of fraudsters, ensuring security and preserving customer trust.

Here are some ways AI helps banks detect suspicious activity and thwart fraud before it happens:

• Behavioral Analytics: Analyzes user habits and creates profiles of customer behavior based on transaction patterns and spending habits, flagging transactions that don¡¯t fit typical behavior.
• Voice Stress Detection:AI tools analyze vocal tones during customer calls to detect stress or deception, helping call center agents identify potential fraud attempts.
• Anomaly Detection/Unusual Transaction Patterns: AI establishes a baseline for normal transaction behavior and flags anomalies in real time. Algorithms detect significant deviations from a customer¡¯s usual spending habits, triggering immediate reviews.
• Data Mismatches: : AI tools cross-reference customer information across databases to identify discrepancies that may indicate account takeovers.
• Textual Analysis: AI identifies suspicious keywords, behaviors, or requests during customer service chats and other text-based channels, including emails, social media, and online forums.
• Image and Video Analysis: AI-powered image recognition detects counterfeit documents, manipulated images, and deepfake videos used in identity fraud and other scams.
• False Positive Reduction: AI techniques significantly reduce false positives by more accurately distinguishing between legitimate and fraudulent activities.

¾ÅÉ« Connect: Your AI Partner in Fighting Fraud

With fraud tactics evolving quickly, many institutions are looking for smarter, faster solutions.

Ready to transform your bank¡¯s contact center into an AI-powered fraud-fighting machine? You don¡¯t have to go it alone. Armed with contact center and AI expertise, ¾ÅÉ« Connect is the partner you need to take a proactive stance against threats to the integrity and safety of your institution and customers.

¾ÅÉ« Connect builds and implements AI-powered solutions to sniff out suspicious activity in real time. Our experts have deep financial industry and contact center operation knowledge, and we¡¯ll arm your agents with the training they need to be your bank¡¯s eyes and ears against fraud. It¡¯s time to lean into the power of AI to protect your regional/community bank or credit union and ensure customer trust.