Investors in the financial services sectors are increasingly eyeing locations that have strong artificial intelligence (AI) resources in a bid to benefit from their competitive advantages, especially given the increased importance of the digital transformation following the outbreak of Covid-19.
Indeed, the pandemic has accelerated the need for banking and financial services to embrace AI technologies.
“The adoption of AI has varied significantly across industries,” says Matt Szuhaj, managing director, real estate and location strategy, at Deloitte Consulting. “However, financial services companies have been early adopters of virtualisation due to consumer preferences and market forces, and therefore are positioned to leverage AI more readily.”
AI is, then, making its presence felt across the financial services industry, and this is having an impact upon site selection companies when they determine the best location for banking and financial services clients to relocate to or expand in.
“As AI continues to transform the financial services industry, one of the most important site selection factors for this sector will be the need for skilled talent and relevant academic resources to support the continued development and growth of these companies,” says Mark Simmons, principal at Parker Poe Consulting.
John Boyd of New Jersey-based location consultancy Boyd Company adds that his company’s site searches now focus heavily on those global markets that have strong academic programmes based around AI, given clients’ need for the latest in AI skill sets as well as a requirement for academic resources to continue to train workers in this discipline.
How important are operational costs to AI site selection?
On top of a sustainable supply of talent and academic resources, operating costs are another competitive factor that companies take into consideration in the site selection phase, along with indicators such as a favourable operating climate, regulatory requirements, infrastructure, business disruption risks and incentives.
Indeed, Boyd explains that site searches also prioritise those cities that already house a large number of financial services jobs and skill sets, along with a favourable operating cost profile. His company has identified 25 cities that show a superior fit for AI recruiting when it comes to the banking and financial services sectors. The cities are ranked by the cost of operating a typical operations centre occupying 2,787m² and employing 150 workers.
Montreal is the top-ranked city in terms of cost efficiencies and AI talent. One key reason behind this rating is that it houses an important lab for deep learning research, the Montreal Institute for Learning Algorithms, which is fronted by one of the founders of machine learning, Yoshua Bengio.
The city also benefits from its deep pool of workers in financial services, and Canada’s global recruitment-friendly immigration policies and favourable exchange rate. Indeed, Boyd adds that Boston-based State Street and New York City-based Morgan Stanley have generated 2,000 new jobs in Montreal. The Canadian city has also been the recipient of new investments from major AI players DeepMind, Facebook, Google, Microsoft, Samsung and Paris-based Thales.
Locations for innovation
AI activities fall into two types of related operations within the financial services sector, according to Szuhaj at Deloitte Consulting. He adds that there is an overlap between the hubs for each type of operation.
The first type includes financial service delivery centres performing fintech, cybersecurity and business analytics activities, while the second type involves software and IT service centres performing design and research and development activities.
Szuhaj says that for financial service delivery centres, traditional/mature hubs – based on high concentrations of sector employment relative to the overall labour force – include Greater New York City, Phoenix, Salt Lake City, Charlotte, Boston and Philadelphia. However, there are also emerging hubs in this space, based on jobs added between April 2015 and March 2020, which include San Antonio, Boise, Jacksonville, Dallas-Fort Worth, Nashville and Tampa. Leading emerging hubs are Phoenix, New Orleans, Chicago, Raleigh, Little Rock, Hartford, Dallas-Fort Worth, Indianapolis, Orlando, Portland, San Antonio and Salt Lake City.
The rise of these emerging hubs, alongside advancements in more mature hubs, is causing AI to become more widespread in the financial services industry. Indeed, with financial services firms looking to increasingly leverage AI in a bid to deliver new products and services, reduce costs and generate additional revenue, more and more hubs look set to emerge as options for investors or companies looking to expand in the financial services or banking industries.
This article forms part of GlobalData’s AI week. For other articles in the series, please visit: