WEBINAR WRITE-UP
Combatting social engineering fraud
Social engineering fraud poses a significant threat to the banking industry, with fraudsters employing ever-more sophisticated psychological tactics to exploit vulnerable individuals. Banks are increasingly leveraging advanced analytics and AI, as well as behavioural and biometric data for fraud prevention.
In this MoneyLIVE webinar, an expert panel of fraud leaders at ABN AMRO, Danske Bank, TSB Bank, Bank of Ireland and Fullstory shared their insights on how they’re combatting fraud attacks, whilst maintaining that customer trust.
The rise of social engineering fraud
Banks are experiencing a surge in social engineering fraud, where bad actors are not only extracting personal information but also probing financial systems for weaknesses.
The sophistication of these scams is evident in tactics like the “double tap” scam, which involves a follow-up message to exploit the victim’s heightened worry. This method targets individuals at their most vulnerable moments. Banks need to understand the innovative mindset of fraudsters to counteract their strategies effectively – by building robust barriers and continuously evolving defence mechanisms, banks can delay and ultimately thwart these scams.
Generative AI is another tool used by fraudsters to enhance their scams, including deepfakes and voice impersonation in banking employee impersonation scams. This technology makes it difficult for customers to distinguish between genuine and fraudulent communications, leading to significant financial losses. It is clear that banks must invest in advanced AI technologies to detect and prevent these sophisticated scams, ensuring customer protection.
Strategies for combatting fraudsters
Fraud imposes significant financial and reputational costs, with data breaches potentially costing millions and leading to fines and lawsuits. The real impact is on customers who lose their money. Banks must integrate fraud prevention into their customer experience strategy, focusing on customer education and implementing robust security measures to mitigate risks and protect customers from financial harm.
Trust in banking has historically been strong, but misinformation and unsafe interactions have eroded it. Social engineering tactics have become central to fraud prevention strategies, necessitating a dynamic response from banks, especially with regulatory changes shifting liability and increasing the focus on fraud detection and prevention. Recent UK regulation changes have improved outcomes for customers through consistent reimbursements and refunds for scams, fostering collaboration between sending and receiving banks.
The increased financial burden on UK banks, due to higher refund costs, has driven investment in detection and prevention technologies, leading to advancements in inbound payment monitoring, AI, and machine learning detection platforms. Collaborative efforts among banks have enhanced data sharing, providing a comprehensive view of fraud across the industry. These investments are reducing fraud success rates and driving the development of new technologies and strategies to stay ahead of fraudsters.
Identifying and protecting vulnerable customers is crucial in fraud prevention. The definition of vulnerability has expanded, especially post-COVID-19, with increased digital presence leading to heightened loneliness and susceptibility to scams like romance frauds. Elderly customers’ predictable banking behaviours can be monitored for suspicious activity. By analysing behavioural changes, banks can flag potential fraud and intervene before significant harm occurs, highlighting the importance of behavioural analytics in safeguarding vulnerable populations.
Harnessing AI and behavioural analytics
Harnessing data, AI, and behavioural analytics is key to combating social engineering fraud. Enriched transaction data provides a comprehensive view of customer behaviour. Machine learning-based systems automate transaction assessments at scale, enhancing anomaly detection and fraud prevention. Collaboration among banks, government agencies, and other bodies is vital for improving fraud detection. Sharing suspicious data and leveraging advanced technologies helps banks enhance protective measures and reduce fraud impact.
Partnering with specialised software vendors is an effective strategy for banks. These vendors access a broader range of data from multiple financial institutions, enriching fraud detection models. Utilising sophisticated smart rules from vendors provides a nuanced understanding of fraudulent behaviours, ensuring banks benefit from more comprehensive data.
Behavioural science enhances the quality of data used for fraud detection. Analysing transaction data through behavioural psychology offers deeper insights into customer behaviours and spending patterns. Behavioural scientists provide context to data, identifying anomalies and potential fraud, allowing banks to create accurate profiles of legitimate behaviour and detect deviations.
The human element remains critical in fraud detection and prevention. Training frontline staff to handle sensitive situations with customers is essential. Staff must guide customers in identifying and preventing fraud, especially when customers are unaware of their vulnerability. Sensitivity and clear communication build trust and ensure customer support.
Final summary
Social engineering fraud poses a significant and evolving threat to the banking sector, demanding a comprehensive approach for effective mitigation. Banks must utilise behavioural and biometric data, advanced analytics, and AI technologies to stay ahead of fraudsters. Understanding the tactics employed by fraudsters and evolving defence mechanisms is crucial for protecting customers from financial losses. Customer education and robust security measures are essential to ensure individuals are aware of risks and equipped to avoid scams.
The banking industry must innovate and invest in advanced fraud detection and prevention technologies, integrating security into the design phase and collaborating across institutions. Leveraging behavioural analytics enhances customer experience and builds a secure environment. The evolving tactics of fraudsters necessitate a dynamic response to maintain trust in banking. As the industry moves forward, focusing on education, awareness, and technological advancements will be key to mitigating fraud and protecting customers.
About Fullstory
Fullstory is the leading behavioral data platform that helps technology leaders make smarter, faster decisions by integrating rich behavioral signals into their analytics stack. Its patented technology captures every digital interaction and transforms it into high-fidelity, actionable insights at scale.
With agentic AI, Fullstory enables enterprises to anticipate the needs of both customers and employees, personalize experiences in real time, streamline workflows, and drive meaningful business outcomes. From boosting efficiency and conversion to increasing loyalty and revenue, Fullstory turns digital behavior into a competitive advantage.
Headquartered in Atlanta with teams across North America, EMEA, and APAC, Fullstory is trusted by the world’s most innovative organizations to transform behavioral data into business impact.
To learn more, visit https://www.fullstory.com/
