Is Your Workforce Future-Ready? A Roadmap for Financial Institutions
Over the past decade, the financial services industry has faced significant workforce challenges including changing employee demographics, increased competition for top-level talent and an evolution in the nature of the work itself, as technologies such as artificial intelligence become more mainstream. These rapid changes have illuminated the need for the continual training and reskilling of workers, particularly when it comes to technology.
To meet the demands of the changing financial services industry, organizations are seeking new ways to grow and support their workers’ development of hard and soft skills, especially in their information technology (IT) departments. For example, a 2018 survey by Peak10 found that 76% of financial institutions (FIs) have created new IT roles in the last two years. However, half of all financial institutions report they are finding it “difficult” or “very difficult” to hire enough IT talent to fill these positions.
At the same time, the cloud has become the dominant technology platform for the financial services industry. Many institutions are moving away from on-premises servers and hardware to Software as a Service (SaaS), Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) IT models, allowing them to attain greater flexibility, reduce expenses and increase speed to market.
To ensure their talent keeps up with technology, organizations should commit to continual professional development through training, workshops and other opportunities. Encouraging employee growth and learning can be accomplished through a variety of methods, including compensation, promotion and public recognition. Perhaps the biggest incentive, however, is in providing workers with the opportunities to use their new skills on the job. For instance, offering technology workers opportunities to deepen their knowledge and become adept in platforms such as Salesforce and nCino is a way to keep employees engaged and motivated.
Another tactic is to regularly rotate employees through a variety of business and technology roles. This approach offers FIs the dual benefits of deepening workers’ skillsets and providing them with opportunities to collaborate with colleagues in other departments and positions. The result? A deep bench of employees armed with the skills and expertise to adapt to an environment of continuous change.
Faced with the convergence of numerous disruptive forces including changing career expectations, growing competition from mega-tech firms and the rising use of automation, cognitive technologies and cloud-based software, one thing is clear: a combination of technology and talent is the key to a future-ready workforce.
The 2025 banking landscape is already evolving faster than ever, thanks to rapid technological advancements, shifting customer expectations, and uncertain economic conditions. To stay competitive, forward-thinking financial institutions must not only keep up, but also anticipate what's next.
In today’s financial landscape, digital transformation has become an essential priority for financial institutions (FIs), and credit risk management is no exception. Despite economic challenges, many banks are making significant investments in advanced technologies to fast-track their digital transformation. While cost pressures are considerable, the potential of technology to enhance automation and efficiency continues to drive these investments forward.
With the rapid evolution of technology and increasing regulatory demands, financial institutions (FIs) face the dual task of enhancing operational efficiency while mitigating risks.
As we continue to witness the exponential rise of Artificial Intelligence (AI) in the financial services industry, it's crucial to understand the inner workings of the models driving these intelligent systems.
The introduction of Apple’s transformative product in 2007 was a moment that changed the future. Like the now iconic iPhone, the launch of generative AI tools like ChatGPT and Google Bard have captured the public’s imagination, launching an explosion of applications and experiments across nearly every industry, from business and commerce, to art and government.
For many of these use cases, the “how” behind the AI model isn’t particularly relevant. If you ask ChatGPT to compose a wedding invitation in the form of a Shakespearean sonnet, you don’t necessarily need to understand how AI can instantly conjure the right rhyme scheme.
A wedding invitation is one thing; a financial institution’s credit lending decision is quite another. When it comes to such high stakes decisions, understanding the inner workings of the model is vitally important—even required. For those use cases, explainable AI is the solution.
