The financial sector stands at a pivotal moment as the integration of artificial intelligence (AI) transforms the landscape of data protection and cybersecurity. With trust being an essential component in handling billions of dollars and sensitive customer information, the stakes have never been higher. According to the Global Benchmark Study 2024, one-third of budgets for digital transformation already flow into AI technologies such as machine learning and generative AI (GenAI). However, with the proliferation of these technologies comes a rise in risks, particularly from sophisticated cyberattacks that put the security architecture of the financial world under increasing pressure.
A recent PwC survey from 2024 revealed that over half of the asset managers surveyed indicated that disruptive technologies significantly influence their security strategies. As banks navigate this new terrain, they are increasingly turning to fintech partnerships, with nearly half of established institutions relying on such collaborations. This shift is driven by the need for enhanced security measures, compliance, scalability, and the reputation of technology partners.
However, as the use of AI expands, new standards are emerging. Privacy-by-design, maximum system availability, and minimizing third-party risks have become paramount considerations. IT managers and decision-makers must strategically evaluate these factors to select the right technology partner and leverage digital transformation to their advantage.
AI presents remarkable opportunities for asset managers, from personalized financial services to precise analytics. Yet, these innovations come at a cost. AI models require vast amounts of sensitive customer data, which must not only be stored but also retained and continuously updated over long periods. This reality heightens the risk of data breaches, cyberattacks, and regulatory violations. As such, banks face a delicate balancing act between technological innovation and stringent data protection regulations.
To address these challenges, banks must prioritize privacy regulations in their initiatives, ensuring that every AI system is developed according to the privacy-by-design principle. This involves removing or anonymizing personally identifiable information from training data. When anonymization is not feasible, the AI architecture should be designed to safeguard privacy, such as by carefully evaluating external AI services from major providers and, in certain cases, opting for locally hosted open-source models. This approach is grounded in the belief that privacy regulations should dictate the use of technological innovations, rather than the other way around.
As the new generation of investors demands not only personalization and speed but also seamless 360-degree support, banks must provide IT systems capable of reliably handling increasing transaction volumes. A critical criterion for selecting the right technology partner is system availability. One major client manages a customer base in the upper millions and an annual transaction volume in the three-digit millions, with peak loads of approximately 200 to 300 transactions per second. However, many banks underestimate a crucial aspect: the right API strategy is vital to ensure system availability even under heavy loads. This strategy should be based on a combination of synchronous and asynchronous interfaces.
For real-time applications like web banking or front-office systems, banks require swift and efficient communication between systems. Synchronous APIs can be employed to quickly send and receive data, ensuring smooth performance and short response times. For processes that do not require immediate feedback, asynchronous APIs with message queues are recommended. These allow systems to process requests in the background, maintaining a smooth operation even under high workloads. This approach can help achieve high system availability.
However, the threats to financial institutions are not limited to internal data gaps; external threats are also increasingly pressuring these organizations. Cyber resilience—the ability to swiftly repel attacks and recover from them—has become a fundamental requirement for collaboration between banks and fintechs. Solutions must include regular penetration tests, incident response frameworks, and data backup systems. Additionally, more financial institutions are turning to cloud solutions.
A KPMG study from 2023 indicated that 63 percent of surveyed financial companies prefer to implement new IT projects in the cloud. However, this trend has also led to heightened demand for transparency among financial institutions. Questions arise about where the servers housing customer data are located and what this means for regulation. What security measures are being taken by third-party platforms used by fintechs? Banks expect clear answers and the highest standards, particularly those operating internationally, which require technology partners with cross-border regulatory expertise. Collaboration with local experts, including consulting firms and law firms, is essential, coordinated through a central compliance team.
In summary, while the risks posed by new technologies like AI are growing, the potential benefits outweigh these challenges. By choosing the right partners, financial institutions can remain competitive and safely harness digital innovations.
Meanwhile, in a related development, the law firm Burns White LLC, based in Pittsburgh, has announced the expansion of its cybersecurity practice to include a specialized group for data protection, cybersecurity, and artificial intelligence. This move reflects the increasing importance of data protection and AI in today’s digital landscape. The new group will be led by experienced experts who bring extensive knowledge in these areas.
As the demand for specialized legal services in cybersecurity and data protection has surged, companies face the challenge of meeting complex legal requirements while safeguarding their data from cyber threats. The integration of artificial intelligence into these processes offers new opportunities to optimize security measures and enhance efficiency. Burns White LLC is responding to these developments by combining its expertise in cybersecurity with innovative approaches in artificial intelligence, enabling the firm to provide tailored solutions that address both the legal and technical aspects of data security.
The establishment of this new group comes at a time when the demand for data protection and cybersecurity services is steadily increasing. Companies are increasingly seeking specialized law firms to help them navigate the complex landscape of data protection laws while protecting their data from threats. Experts agree that combining legal expertise with technical innovation is crucial to meet the challenges of digital transformation.
With the expansion of its cybersecurity practice to include data protection and artificial intelligence, Burns White LLC positions itself as a leader in a rapidly evolving market. The firm is committed to not only providing legal advice but also offering strategic support for implementing security solutions. The future of cybersecurity and data protection will be significantly shaped by technological innovations, and Burns White LLC is well-positioned to actively participate in these developments, helping its clients navigate safely in an increasingly digitized world.
