There’s been a significant increase in demand for technical workers with data, advanced analytics, and AI skills in the modern banking sector. However, there aren’t enough qualified data and AI professionals to meet the requirements of major organizations across the globe. This major talent gap between requirements and availability of talent may not be filled unless appropriate changes are made (like offering relevant and accessible training and educational programs).
One possible solution might also be to combine outsourced services with a special focus on upskilling a company’s workers so that they are able to work on projects involving emerging technologies such as AI, Big Data, and machine learning.
Research conducted by the publishers of the Digital Banking Report reveals that financial services providers (of all sizes) have a relatively low level of data maturity, even though there’s an increasing array of AI platforms and services provided by third parties.
The research study found that only 12% of organizations surveyed think they’re “very effective” or “extremely effective” at competently using data and advanced analytics programs. As first reported by the Financial Brand, there are fewer organizations now that are confident about using new technologies when compared to the time period before COVID. Although legacy platforms are often cited as the main reason for not being able to integrate the latest tech, the second most cited reason is the lack of skill or expertise within companies to launch AI-enhanced solutions.
Banks and credit unions may be able to afford buying modern AI software, but there’s usually not enough planning that’s been done so that they can effectively integrate these solutions, the report claims. This may lead to a digital transformation “paradox,” where key decision-makers and workers might believe AI is beneficial yet they are unable to use these technologies due to lack of planning and implementation.
The report confirms that we now have the ability to effectively collect, analyze and make informed decisions using AI and machine learning technologies. However, the key challenge now is getting a company’s employees to attend proper training programs so that they can use these tools effectively.
As covered recently, applying “old thinking” to new problems and use cases might derail artificial intelligence progress and integration, according to a new report.
AI has vast applications in many different fields including key areas of the Fintech sector. Mastercard recently introduced an AI-enhanced solution to protect digital financial services providers and online businesses from cyberattacks.
Skan, the AI-enabled process discovery and operational intelligence provider, recently announced that it secured $14 million through its Series A funding round, which was led by Cathay Innovation with participation from Citi Ventures, Zetta Ventures, Bloomberg Beta, Plug and Play Ventures, and Firebolt Ventures.
As covered in October 2020, AI and machine learning technologies are expected to play a key role in expanding the multi billion dollar digital banking sector, according to a recent report.