The future of the banking industry will be shaped by a range of disruptive themes, with artificial intelligence (AI) being one of the themes that will have a significant impact on banking companies. 

In banking, AI use cases include enhancing client interactions through chatbots; providing better loan terms through data-driven risk assessments; and automating laborious back-end processes. Banks can realise the benefits of AI in cost savings, quality improvements, an expansion of their services, and increased personalisation in these product offerings. 

There has never been a more important time for banks to invest in AI. With threats to the industry having come from both disruptive fintechs and the Covid-19 pandemic, which uprooted traditional branch-based banking, banks must be proactive in adapting their strategies and processes to remain competitive and desirable to consumers. Fintechs have changed consumer expectations, putting more pressure on banks to offer a better user experience. AI can galvanise waning banks and provide them with new income sources while increasing the value they derive from current sources by, for example, reducing non-performing loan (NPL) ratios through AI-enabled credit checks. GlobalData forecasts that retail banks will spend $4.9bn on AI platforms worldwide by 2024. This is up from $1.8bn in 2019, representing a compound annual growth rate (CAGR) of 21.8%. 

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However, not all companies are equal when it comes to their capabilities and investments in the key themes that matter most to their industry. Understanding how companies are positioned ranked in the most important themes can be a key leading indicator of their future earnings potential and relative competitive position. 

 According to GlobalData’s thematic research report, AI in Banking, leading AI adopters in banking include: Tencent, ANT Group, Goldman Sachs, HSBC, BBVA, OakNorth, DBS Bank, Bank of America, and Santander

Insights from top ranked companies  

DBS Bank 

DBS Bank is a Singaporean bank and financial services firm with a focus on digital banking. The bank uses AI to offer personalised offers and services to clients, in what it calls ‘intelligent banking’. This includes analysing vast troves of data and offering proposals to clients that may have otherwise not been identified. DBS Bank’s iWealth wealth management app recommends stocks in specific sectors based on customers’ portfolios. Furthermore, the bank has been using AI and ML to detect anomalous transactions on customer accounts; this ensures that fraud is combatted, cybersecurity is robust, and AML concerns are well addressed. 

HSBC 

HSBC has innovated in several areas. In 2018, HSBC launched its Global Social Network Analytics platform, which uses big data to tackle financial crimes such as money laundering and terrorist financing. The bank also uses an AI pricing chatbot forex options and keeps all its ATMs stocked through an AI-based system. The most innovative application of AI yet seen from HSBC has been the experimentation with an in-branch robot, developed in partnership with SoftBank Robotics. The robot, called Pepper, uses data intelligence to perform over 300 different actions, including opening accounts and credit card applications. Pepper uses NLP to understand multiple languages and can even basic human emotions and adapt its behaviour accordingly.  

To further understand the key themes and technologies disrupting the banking industry, access GlobalData’s latest thematic research report on AI in Banking.

  • ANT Group
  • mBank
  • Tencent
  • Nubank
  • KEB Hana Bank
  • US Bancorp
  • Bank of Montreal
  • Westpac
  • Lloyds Banking
  • Bank of America
  • UOB
  • PNC
  • ING Groep
  • Monzo
  • State Bank of India
  • Revolut
  • Commonwealth Bank of Australia
  • Capital One
  • Nordea
  • Axis Bank
  • JPMorgan Chase
  • Wells Fargo
  • TD Bank
  • Citigroup
  • Santander Group
  • Societe Generale
  • Swedbank
  • ABN AMRO
  • Sberbank
  • Intesa Sanpaolo

GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData’s Thematic Scorecard ranks companies within a sector based on their overall leadership in the 10 themes that matter most to their industry, generating a leading indicator of their future earnings and relative position within key strategic areas.