- Filip Verloy, Field CTO at Noname Security
- 10.08.2023 07:30 am #cybrsecurity
Financial services firms deploy an increasingly complicated mix of technologies, systems, applications, and processes to serve customers and partners and to solve organisational challenges. Focused heavily on consumer hyper-personalisation, banks are evolving more and more digital assets and services to meet and exceed growing customer experience expectations.
As a result, the modern banking environment is heavily reliant on APIs to the point that they are now indispensable. APIs allow financial banks to connect with their ecosystem, while inspiring innovative developers to create new products, Excellerate existing services, and work more efficiently.
A sector disproportionately targeted
However, this reliance on APIs presents challenges. They create vulnerabilities and are often the gateway for cybercriminals. The financial services industry is disproportionately targeted by threat actors who know that it has what they want – data and money.
This has brought an ever-increasing set of cyber regulations into sharp focus to help to ensure that banks are protected and compliant. However, this has led to fragmentation, as regulators try to achieve a balance between robust governance and not stifling innovation or driving businesses abroad.
This fragmentation has occurred because banks must comply with a cocktail of regulations in the same or different jurisdictions that are well-intentioned, but sometimes conflicting, and that do not actually enhance cyber-resilience.
Therefore, what are these different types of cyber regulations and what should banks be thinking about when it comes to API security?
Stress testing banks
Earlier this year, the European Central Bank (ECB) announced plans to stress test the cyber resilience of the Eurozone's top banks in 2024 because of the proliferation of sophisticated cyberattacks, with EU law mandating that the ECB undertakes stress tests on supervised banks at least once per year. Results from these tests help supervisors identify vulnerabilities and address them early on in their interaction with banks. Likewise, the results of annual stress tests provide important input for the Supervisory Review and Evaluation Process (SREP) in the test year.
In years when there are no EU-wide tests, the ECB tests significant institutions under its direct supervision against specific kinds of incidents. These tests run in cooperation with national supervisory authorities, and the ECB publishes the results on an aggregate basis.
A lack of API standards
The European Commission has just published its proposal for the third Payment Services Directive (PSD3), to help advance open banking and strengthen consumer protection. The PSD3 and Payment Services Regulation aims to drive further development in open banking, first introduced with PSD2, as well as addressing issues around API quality, and giving authorities the required tools to better evaluate the dedicated API interfaces provided by banks and other financial institutions.
According to the European Banking Authority (EBA), “The experience acquired in the implementation of the PSD2 has shown that the absence of a single API standard has led to the emergence of different API solutions across the EU. This creates significant challenges for third-party service providers as they must invest significant efforts into connecting to different Account Servicing Payment Service Providers’ APIs and adapt their connections to changes in APIs over time.” Whilst PSD3 will absorb the lessons learned from PSD2, it’s no secret that PSD2 is seen as complex and difficult to define. In fact, between 2016 and 2022, the EBA released six technical standards, eight sets of guidelines, eight opinions, and more than 200 Q&As in relation to PSD2.
PCI DSS v4.0 is the next evolution of the PCI DSS standard. The goal of this new standard is to continue to meet the security needs of the payments industry, promote security as a continuous process, add flexibility for different methodologies, and enhance the validation methods. This is the first time APIs have been explicitly called out in the standard, underpinning their importance. In fact, the EBA argues that API standardisation is needed to reduce the barriers to entry for FinTechs wanting to access financial account data held by banks and similar institutions.
Adhering to DORA
Additionally, by January 2025, EU financial entities and their critical ICT providers must be ready to comply with the Digital Operational Resilience Act (DORA). DORA standardises how financial entities report cybersecurity incidents, test their digital operational resilience, and manage ICT third-party risk across the sector.
For certain financial entities this includes undertaking advanced threat-led penetration testing every three years. By clarifying testing methodology and introducing mutual recognition of testing results, DORA will help financial entities continue to build and scale their testing capabilities in a way that works throughout the EU.
The NIS2 Directive – which came into force in January 2023 – aims to strengthen cybersecurity risk management requirements as well as ensure companies take appropriate and proportionate technical, operational, and organisational measures to manage their cybersecurity risks as well as prevent and minimise the impact of potential incidents. The Directive aims to ensure a safer and stronger Europe by significantly expanding the sectors and types of entities falling under its scope.
It replaces the current Directive on Security of Network and Information Systems and focuses on measures including incident response and crisis management, vulnerability handling and disclosure, policies and procedures to assess the effectiveness of cybersecurity risk management measures, and cybersecurity hygiene and training.
Furthermore, it features more stringent supervisory measures for national authorities, as well as stricter enforcement requirements, along with a list of administrative sanctions, including fines for breaches of the cybersecurity risk management and reporting obligations.
Compliance across all financial Directives
The DORA Amending Directive will amend other Directives to align with DORA, including CRD IV, Solvency II, MiFID II, PSD2, UCITS and AIFMD. In-scope entities include credit institutions, payment institutions, electronic money institutions, investment firms, and crypto-asset service providers, whilst regulation 2022/2554 outlines the requirements concerning the security of network and information systems supporting the business processes of financial entities.
Clearly, APIs have become the default connectivity and data exchange method within modern financial services environments and will continue to be so in the future. With this in mind, securing APIs from both a pre-production and post-production perspective is paramount to securely operating in our digital-first banking world.
Therefore, financial services entities should work with an API security platform provider that can deliver strong API security and help with compliance and governance requirements. In this evolving regulatory landscape this will enable organisations to implement a robust API strategy across discovery, posture management, runtime protection and API security testing.
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Ally Financial dove headfirst into generative artificial intelligence after ChatGPT made its splash at the end of 2022.
The Detroit bank formed a working group around generative AI in early 2023. It met with both Microsoft and Amazon in Seattle in February and hashed out a contract with Microsoft to use its enterprise-grade generative AI software in April. The team started building Ally.ai, a proprietary cloud-based platform that developers will use for AI-related projects, in June, and launched a pilot for its first use case at the end of that month. The pilot moved to production on July 31.
"We do not want to stand still," said Sathish Muthukrishnan, the chief information, data and digital officer at Ally Bank.
Ally.ai is a bridge between external large language models (Microsoft's GPT 3.5 right now; perhaps other large language models in the future), generative AI technology, Ally's internal applications and data, its data security protections and — for now — human intervention. Ally's early work demonstrates how a $197 billion-asset bank is handling risks such as hallucinations and protecting customer information. It's also showing promise, with high approval ratings from the contact center agents that are part of Ally's first use case.
Ian Watson, head of risk at Celent, finds banks are generally doing three things right now relating to generative AI.
One is cleaning up their data foundations and pulling bank data out of its siloes. Another is choosing which large language models they want to use, from the big names such as Microsoft and Google to smaller open-source models that Watson says have much of the functionality of the big ones but can be trained on less data. The third is experimenting with use cases.
"That is the part that most captures the imagination and paints a picture of what is possible," he said. "It's where a lot of people are focused in terms of getting funding for this or to show they are on the cutting edge. But the bulk of the investment is going into data foundations."
Ally's first use case focuses on the contact center. Normally, contact center agents take notes when speaking with a customer and summarize the contents of the call when it's over. This is necessary for regulatory reasons, as well as ensuring good customer service. Ally piloted a system in June and July where AI technology transcribes the conversation in real time to the Ally.ai platform and creates a summary of the call. One goal is to relieve the agents of multitasking and let them be more present in the conversation.
"This has the potential to unleash productivity for us," said Muthukrishnan.
For now, agents will manually review these summaries to ensure everything is accurate. The system is showing promise so far: When the pilot began in late June, the rate of agents approving their summaries with no changes was in the low teens. By the time the pilot wrapped up at the end of July, the approval rate was 78%. Now, it's fully deployed to more than 700 agents.
Human intervention is still important as Ally refines its models. It's also one of three principles that Ally adopted before using generative AI. The others are to learn and test on internal customers (employees) before deploying to external customers, and to keep personally identifiable information strictly within Ally firewalls.
These precautions are vital.
Celent groups the risks surrounding generative AI into two buckets. One is adverse outcomes, such as bias, hallucination and false output. The other is external threats, such as regulatory violations and cybersecurity.
"There is a real danger of the models developing complete falsehoods," said Watson.
The team at Ally observed hallucinations when calls took less than one minute or the line was fuzzy, and had to refine prompts to prevent this from recurring. Other security measures include a secure pipeline between the bank and Microsoft and a dedicated GPT 3.5 model. Ally does not let PII leave its firewalls or let the foundational models learn from Ally data. Ally's model will "forget" personal data after a session with a customer associate is over. The team conducts tests and evaluations to guard for model "drift" and bias creeping in.
Despite the risks of generative AI, "The most obvious risk is actually not using it," said Watson. "We think it's going to change business models and the competitive playing field," from reducing drudge work and employee turnover to customizing marketing materials.
Ally is evaluating other potential use cases, such as writing user stories for software features and answering basic questions about human resources benefits.
Further down the road, it could develop use cases for customers.
"This will supply us the ability to truly understand customer needs and wants, and to personalize experiences that fit their financial needs at the right time," said Muthukrishnan.
The debut of Ally.ai dovetails with its transition to the cloud. More than two-thirds of Ally applications are now cloud-enabled.
"AI by itself requires a massive amount of compute," or processing power, memory and storage, said Muthukrishnan. "If you want horizontal scaling and infrastructure on demand, you want your applications running on the cloud."
