In today’s fast-paced financial sector, data is an invaluable tool—allowing banks and financial institutions to spot imminent financial trends, identify emerging customer needs, and roll out customized services and offerings in record time. With artificial intelligence (AI) now entering the playing field, data-led banking is evolving even more rapidly. Yet, to lead this technology in the right direction and enhance responsible implementations, trust is essential.
A key pillar in building that trust involves creating trustworthy technology, or digital ethics. Beyond protecting the rights of users, an ethical framework helps to prevent harm and secure the trust of the people subjected to technologies such as AI models. Failing to take digital ethics into account, on the other hand, can result in the creation of solutions that ignore the needs of underrepresented groups or that can be used in ways disconnected from organizational intentions.
This latter path can further interfere with organizational goals, tarnish brand reputations, and even negatively impact peoples’ lives. To avoid these outcomes, financial institutions must take a new approach to data in the AI era by putting trust at the center of all their decision-making. This means reframing their mindsets, enhancing awareness of existing systemic shortcomings, and having meaningful conversations around ethical data collection and management.
Here, we explore some of the barrier’s banks may encounter as they integrate AI into their data-led banking practices.
Download the pdf to explore some of the barrier’s banks may encounter as they integrate AI into their data-led banking practices and solutions.