Bank of the Future, Mapped by McKinsey
Bank of the Future, Mapped by McKinsey
The consulting firm, known for its bold calls in global banking, is outlining the bank of the future. Making it reality is another matter.
Banks pay McKinsey handsomely for audacious, frequently transformative strategy ideas. Mega-mergers and acquisitions or a complete pivot of business models aren’t uncommon. McKinsey’s consultants are banking on technology and specifically artificial intelligence or AI, in its most recent study.
Specifically, banks should bake the emerging technology into their processes, in a bid to set free as much as $1 trillion in annual savings, McKinsey said. «To compete successfully and thrive, incumbent banks must become ‘AI-first’ institutions, adopting AI technologies as the foundation for new value propositions and distinctive customer experiences,» the study said.
Broad Toolkit
The AI tools listed by McKinsey are a combination of eight measures spread from client-facing projects to so-called back office functions:
1. «smile-to-pay» facial scanning to start a transaction
2. micro-expression analysis with virtual loan officers
3. biometric recognition through voice, video, and print
4. machine learning for detecting fraud patterns and cyber hacks
5. chatbots for basic client service requests
6. humanoid branch robots to serve clients
7. machine vision and natural-language processing to scan and process documents
8. transaction and risk analysis in real-time
The tools equip banks with offerings that client expect, and make firms competitive for a far more digitally-based future, according to McKinsey.
Major Weaknesses
The tools listed by McKinsey aren’t new. The various technologies are already in use here and there, but artificial intelligence hasn’t been widely applied by financial services firms yet. McKinsey pinpoints three main weaknesses at banks, which spend billions annually on their information technology.
Old «legacy» systems which require extensive maintenance and renewal, fragmented data, and outdated operating models that hurt collaboration between business and technology teams. The pandemic has stepped up digital engagement in general, while major technology companies entering financial services is a looming threat.
Choice Vs Necessity
The solution McKinsey proposes is difficult to roll out in an advisory-based approach. To completely bake AI into the process, banks need to transform themselves at several different levels:
1. technological set-up, to meet client needs (the key is «personalization”)
2. technological set-up to select and deliver products (the concept of intelligent algorithms working more effectively than client advisors)
3. massive renewal and reinforcement of core technology and data infrastructure (key word: cloud)
4. establish a platform business model; technology isn’t enough to break down banks’ silos and hierarchies
McKinsey, which has been known for apocalyptic predictions, emphasizes that it isn’t enough for banks to dabble in AI. «For many banks, ensuring adoption of AI technologies across the enterprise is no longer a choice, but a strategic imperative,» the study’s authors write.
Published at Mon, 21 Sep 2020 10:30:00 +0000
GOTHENBURG, Sweden, Sept. 21, 2020 /PRNewswire/ — Viking Analytics, a Swedish provider of advanced analytics solutions for predictive operations, and Bharat Forge Kilsta AB, one of the world’s largest forging suppliers, began collaborating in a data-driven production quality project. In the next months, Viking Analytics will prepare a detailed assessment of the data collected by sensors installed in the oven that heats steel rods used in the production of crankshafts and front axle beams for heavy duty vehicles.
In the plant located in Karlskoga, the forged steel is first heated in an induction oven, whose temperature varies according to different steel grades and products. If a disruption occurs in a later stage of the production line, the oven must be adjusted to keep the metal at a constant temperature. This process is currently performed manually, sometimes causing human-related deviations in the proper temperature level accounts.
Based on large amounts of sensor data from the oven, artificial intelligence (AI) should be able to control the system in such a way that adjustments can be made automatically. To achieve that, data scientists at Viking Analytics developed a digital twin that simulates the production stage and tests if adding more sensors or changing certain parameters can influence the quality of the data that will be used in machine learning.
Stefan Lagerkvist, CEO at Viking Analytics, explains that understanding data capability is an important first step for industries that want to increase productivity through data analytics. “Just collecting data is not enough. A data readiness assessment shows if it is ready to be used and what conclusions companies will be able to draw from it, as well as suggesting changes or improvements. We are very proud to be partnering with Bharat Forge Kilsta AB in this relevant digitalization process.”
Besides the direct effect in increasing production quality, the reduction of scrap material and optimization of energy consumed by the oven will also contribute towards the sustainability goals of Bharat Forge Kilsta AB. Hans Lindbäck, project manager at Bharat Forge Kilsta AB, continues: “For us, this is the first project where we apply artificial intelligence in our production. Our ambition is to apply similar solutions also in other production processes.”
The collaboration is the first stage of a broader program to drive competitiveness through AI involving Bharat Forge Kilsta SB, RISE, Karlstad University, Alfred Nobel Science Park, Ovako, Volvo, Business Region Örebro, and Viking Analytics.
Press contact:
Isabela Cavedem
Communications Coordinator
isabela.cavedem@vikinganalytics.se
+46 (0)76 230 3670
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SOURCE Viking Analytics AB
Published at Mon, 21 Sep 2020 10:07:30 +0000
