Of the many things one might take for granted, access to banking and financial services may not immediately come to mind. But as a thought experiment, imagine trying to buy a home or a car without the ability to take out a loan. Try depending on cash payments from your employer, or relying on alternative banking solutions like short-term payday loans, check-cashing services, and prepaid debit cards.
In today's dynamic financial landscape, threats are not only escalating but also rapidly evolving. At the same time, regulators impose stricter transparency and compliance requirements on financial institutions. So, how can decision-makers navigate this challenging environment, with relentless cyber threats coming at them from one side and rising regulatory demands from the other?
In the ever-evolving landscape of the financial services Industry, change is a constant and transformation is a requirement—to stay at pace with new regulations, risk mitigation, and the technological developments that support transformation. And just as financial services experiences its cycles, this time of year I find myself returning to the topic of cost reduction.
Banking is a critical but highly complex industry. It is a highly regulated environment, and banking applications must be developed in compliance with privacy and security standards of the region the bank operates. Credibility is an invaluable asset to any financial institution, so they can’t afford to let any bugs, even the most minor, slip into production and impact the user experience.
Financial professionals encounter periods of high activity throughout the year. Whether you serve as a CFO, specialize in taxation, or contribute to the team responsible for closing financial records and generating year-end reports, any time can become crunch time. These intervals demand long hours at the office (or working evenings from your home office) as you diligently tackle the extensive list of tasks that require immediate attention.
With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. But in highly regulated industries where these technologies may be prohibited, the focus is less on off the shelf generative AI, and more on the relationship between their data and how AI can transform their business.
In the fast-paced and highly regulated world of financial services, software quality is arguably of utmost importance. To ensure financial products meet complex requirements and deliver seamless user experiences, robust testing methods are crucial. One such approach that has gained significant traction in the financial industry is Behavior-Driven Development (BDD) testing.
Bank turmoil associated with recent bank failures has highlighted the importance of due diligence for managing financial risk, growing revenue, and retaining jittery customers. Regulators will likely ramp up their scrutiny–even after hitting financial institutions with a jaw-dropping $2.7 billion in fines in 2021 for failing to meet compliance and due diligence standards.
