The rapid evolution of artificial intelligence (AI) technology resembles the proverbial sword of Damocles, poised above us with both promising opportunities and formidable challengesAs AI continues to advance, its impact on various sectors, particularly finance, has become a topic of heated debateThe sudden rise of AI-driven financial fraud has raised alarms, with certain scams reportedly achieving success rates close to 100%. This alarming trend was brought to the forefront during discussions led by cybersecurity experts in China, where the intersection of AI and criminal activity has sparked urgent discussions.

At a pivotal conference in December 2024, a notable figure in cybersecurity, Yu Yang, the Vice President of Tencent Security and head of the Xuanwu Laboratory, was among those drawing attention to the pressing need for the financial industry to rise to the occasionHe highlighted a critical question: how can AI be strategically employed to combat the very threats it has facilitated? Yu Yang pointed out that while large model technologies have been maliciously exploited by nefarious actors, they also offer significant advantages for enhancing efficiency in vulnerability detection and penetration analysis within the industry.

In the quest to create a robust defense against cyber threats, experts emphasized that achieving equilibrium in this digital battlefield demands a gradual and methodical approach

“Operational security is not a new demand,” argued Niesen, Tencent’s Security Deputy General Manager and a specialist in the Cohen LaboratoryHe explained that to effectively harness AI against AI, sectors need to invest time in accumulating industry-specific knowledge while refining data preparation and contextual detailOnly then can they reach the point where defenses are robust enough to contend with the sophisticated offensive tactics of cybercriminals.

The discussion of AI’s double-edged sword touches upon three main points described at the World Internet Conference in Wuzhen: black-boxing, criminal enterprise adaptation, and weaponizationThese revelations underscore how advanced technologies like deepfakes are becoming increasingly indistinguishable from reality, posing significant risks to both individuals and organizationsMoreover, the concept of black-boxing indicates that the processes involved in generating AI models cloud the visibility of potential malicious actions that can proliferate harmful content and misinformation, complicating efforts to combat these threats.

Weaponization describes further misuse of AI, where tools created for benefit are turned into weapons against cybersecurity

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For example, AI can generate sophisticated phishing emails or malicious software, allowing even those with minimal coding experience to launch attacks, thereby drastically increasing the number of potential cyber threats.

However, not all perspectives view AI solely through the lens of dangerMany industry professionals stress the potential for AI to act as a powerful ally in the cybersecurity realmGao Rui, Director of Threat Intelligence Product Planning at Tencent, illustrated this point, stating that the application of AI in threat detection has been most remarkable in its noise-reduction capabilitiesBy automating routine, repetitive tasks, manpower can be redirected towards more complex and critical security challengesThis transition represents a significant transformation within cybersecurity operations.

Furthermore, Tencent Security has innovatively leveraged AI to enhance its operational processes by creating a centralized “Security Lake.” This aggregate of data from various endpoints and traffic sources facilitates comprehensive analysis using advanced AI models, enabling automated responses and streamlined threat mitigation processes

This integrated approach is emblematic of how industry giants are adapting to the evolving digital landscape.

In terms of empowering the financial sector, there is a concerted effort to cultivate a stronger reliance on domestic software and hardware, boosting confidence in their efficacyWang Fenghui, the Deputy General Manager of Tencent Financial Cloud, shared insights highlighting the successful implementation of Tencent Cloud Data Security Audit (DSAudit), which utilizes advanced AI models to secure sensitive financial dataGiven that financial organizations deal with a plethora of sensitive information—including personal identification details, financial characteristics, and emerging identity traits—the need for stringent data security measures has never been more critical.

The data security audit system is built upon a foundation of big data and AI, creating an intricate web of monitoring, anomaly analysis, and fine-grained security auditing

With over 700 pre-configured rule models to assess potential risks and deviations, this system reinforces necessary safeguards against data exploitation and abuse.

Within this framework, the rule engine operates in real time: when an action aligns with predefined parameters, alerts are triggered accordinglyThe semantic engine goes a step further, comprehensively interpreting SQL commands to ascertain the true intent behind data manipulations, thus enhancing the accuracy of threat detection and reducing the incidences of false positives.

As companies usher in the digital economy, the shift has fundamentally changed the nature of banking operations; a staggering 99% of transactions can now be executed onlineHowever, financial institutions are now confronting dual pressures: the increasing difficulty of risk management for new retail credit businesses and the rising risks associated with existing operations

This phenomenon necessitates a focused approach to risk assessment, particularly in pre-loan assessments and subsequent management.

The prevalence of deepfakes complicates this landscape, allowing potential borrowers to submit fraudulent applications or falsified information easilyAddressing this challenge, Tencent Security has developed the Tianyu Financial Risk Control Large Model, uniquely tailored for the financial sectorBy tapping into two decades of experience in mitigating adversarial tactics, Tencent combines progressive AI methodologies and diverse financial datasets to create a generative intelligent risk management tool.

It is imperative for the financial industry to not only harness AI’s potential but also protect its own practices and technological frameworksAI safety becomes paramount as the integration of sophisticated models introduces inherent risksThese risks encompass multiple areas: from filtering out unsafe data during model training to overseeing content outputs for potential violations and addressing any arising issues post hoc.

If a large model falters, the repercussions can be costly

Regulatory bodies have begun issuing stringent guidelines that necessitate adherence to standards of authenticity and accuracy in AI-generated contentThe Chinese government, for instance, has focused on implementing measures that eliminate harmful content produced by AI systems, highlighting the growing concern for responsible technology implementation.

The financial sector must navigate these macro-regulatory dynamics while recognizing the precedents set by organizations like TencentDrawing from these best practices, financial groups can establish robust frameworks for AI content safetyTencent has advanced comprehensive content safety solutions for AI generated content, which range from audit services to risk monitoring frameworksBy committing to a holistic approach, these measures help mitigate potential risks throughout the operational lifecycle.

Lastly, Tencent’s ongoing investments in AI reflect a burgeoning commitment to enhancing the safety of financial operations and systems