• Boris Bialek, Global Field CTO Industries at MongoDB


• 09.09.2024 11:30 am
#Security #DigitalInnovation

Customer expectations of banking have changed drastically over recent years. With the rise of neobanks, the closing of physical branches, and the COVID-19 pandemic, customers are increasingly turning to digital as their primary means of banking. And with the advent of AI in all shades of services, it’s not enough for any type of financial services companies to just have a digital offering. They must be ready to offer best-in-class efficient, integrated options independent if they are consumer centric, commercial or investment banking

Even with forays into the world of online banking, traditional ‘brick and mortar’ banks are still often underpinned by legacy technology that is based on end-of-day processing versus real time. This makes any digital banking development rather difficult. The rigid data architectures associated with legacy mainframes and monolithic enterprise banking applications holding them back. Despite the prominence of these outdated systems, research from MongoDB and Celent found that banks are proactively exploring AI with 58% evaluating or testing gen AI and AI is already being adopted by the sector in areas such as risk, fraud, and compliance. This suggests that there is a desire to embrace new technology, however if banks lack the fundamental technology infrastructure, they will struggle to integrate innovations into their legacy systems.  

Inflexibility and resistance to modification are barriers to technological adoption. But as banking takes on a digitally advanced approach, could a lack of data security threaten AI potential?

Developers determine digital

AI has supercharged IT operations, growth and operational agility. It has improved developer productivity and the creation of best-in-class applications. In fact, gen AI can increase developer capacity in areas like payment product innovation, leading to actualised growth. These gains benefit both the internal operations of a business and the services they can provide customers. 

But why is this important? Well, the rise of neobanks and digital-only institutions altered the public’s expectations for every financial application. Everything from credit software to financial fraud detection software must be digitally efficient, secure, and effective while being user friendly and delivering a consummate user journey at the same time.

What’s more, undelivered product enhancements due to resource constraints could create a 5.3% growth in payments revenues. So, for traditional institutes to adapt and compete with these digital success stories, developers are the critical lynchpin in the building and performance of services with leading UX and CX features.

Security is the foundation

As banks turn to AI, benefitting from efficiencies and the ability to deliver the best digital experience for customers, it is crucial that data security is embedded throughout. This should be the starting point for any digital transformation or improvement in the financial sector. Highly sensitive data must be collected and stored correctly before any innovative or advanced technologies can be adopted. In doing so, banks protect customer data and are more likely to retain their customers.

Financial institutions must have built-in security controls within their data storage strategies, with robust security features. Features like authentication (both single sign-on and multi-factor authentication), role-based access controls, and comprehensive data encryption are vital aspects for any solid approach to data. 

These security measures detect, defend and prevent against the risk of unauthorized access from external third parties. And, when financial institutions use AI tools, comprehensive security measures provide a layer of confidence in the data that fuels these advanced solutions.

The best innovation is secure

The adoption of AI technologies is undoubtedly exciting for the financial services sector. It sparks the potential to deliver consistent, constant services to a wider range of users. 

Outside of customers, the implementation of advanced technologies as a tool to support developers building online applications will help traditional banks rival digital first financial services. We will see a transition to a hybrid, physical-digital model which will be customer-led. 

As previously mentioned, those that don’t have the foundational infrastructure in place to support their advancements will find themselves limited in the benefits that they can receive from AI. In the worst case scenario, a reliance on legacy technology and incorrectly handled information could lead to data security breaches. 

AI will play a significant role in helping business grow. In finance, it will revolutionise customer experience and operational effectiveness. The levers of AI will be used to accelerate digital experience and help financial institutions remain competitive. Prioritising a considered security and encryption strategy should form the core of any technological development. Not only will this protect sensitive customer data, it will allow the AI technologies to flourish.