Complexity, productivity and tech enablers

• A study by Nasdaq & BCG shows excessive operational complexity costs financial institutions US$50bn annually, and that modernised systems could potentially unlock US$1tr in lending. The report, entitled The New Growth Imperative: Cutting Through Complexity in the Financial System, reveals that organisational complexity in banks has increased 35-fold since 1955, while external business complexity has risen only six-fold during the same period.
• Operating costs remain stubborn, despite the US$800bn invested annually in technology. Other key findings reveal that:
• • Major banks have accumulated $241bn in regulatory fines since 2015 (2% of bank income)
  • Money laundering and fraud account for $3.5tn in losses to the global financial system in 2023 (Nasdaq’s separate global financial crime report)
  • Bank consolidation continues with 30% decrease in US bank entities; however, such efficiency measures have not improved cost-to-income ratios
• The Nasdaq and BCG findings are corroborated by McKinsey: ‘Despite tech spending, productivity at US banks has been falling, and economies of scale have been elusive’. And ‘Banking has a leveraged business model and cannot simply cut costs to ‘escape gravity’’.
• The Nasdaq/BCG report therefore advises banks to focus on: embracing digital infrastructure; deploying data collaboration models; building strategic partnerships; and accelerating AI adoption, with AI seen as a key solution to reduce complexity, automate routine processes, data management and report drafting.
• As published in FinTech magazine, Adena T. Friedman, Chair and CEO of Nasdaq is optimistic: “The transformative power of AI, cloud, and modern software can foster collaboration across ecosystems, enabling organisations to adopt innovative ways of working not only to manage the challenge of complexity but transform certain aspects of it into opportunity."
• In a data-centric industry, financial institutions (FIs) have long leveraged big data to enhance customer experiences, maximise profitability and manage risk; AI is widely regarded as a major game changer in pricing, profitability, productivity and velocity of capital.  
• GenAI has therefore spurred a fresh wave of data-driven innovation and growth, enabling corporate and investment banks to use their data in new ways, at scale, for:
  • Client relationship management
  • Market sentiment analysis
  • Portfolio optimisation
  • Risk management
  • Regulatory reporting
• Another tech catalyst for banking efficiency is blockchain; it improves transaction speed, cuts cross-border payment times from days to minutes, lowers costs by automation and reduces the need for intermediaries. Its immutable and auditable characteristics ensure compliance, enhancing security and reducing fraud risk.
• Industry examples of blockchain offerings include:
• • RippleNet and On-Demand Liquidity (ODL): systems that simplify cross-border payments by minimising transaction times and currency conversion costs
  • JPMorgan’s JPM Coin: a private blockchain facilitating instant, low-cost cross-border payments for institutional clients
  • Santander’s One Pay FX and Citi’s TradeLens Collaboration: platforms that improve real-time money transfers and supply chain visibility.
• However, there are significant considerations in using blockchain, such as immutability conflicting with ‘the right to be forgotten’ and other uncertainties in smart contracts. Blockchain also involves high levels of energy consumption. Tight teamwork with legal and compliance teams is essential.
• Bank-fintech collaboration is also a key tech enabler for banks to leverage vast amounts of data to transform internal processes and deliver more efficient and tailored services to clients. The capabilities of fintech firms means they are perfectly positioned to help banks leverage GenAI opportunities, for example to enhance decision-making, minimise operational risk and maximise operational efficiency.
• Fintech partnerships can also ‘democratise’ access to capital markets, making them more standardised and cost-effective, particularly for smaller businesses struggling with the high costs and complex engagement models involved in transacting with large banks. Global markets are partnering with fintechs specialising in capital market product distribution to connect smaller businesses to innovative risk management solutions and investors through advanced digital platforms.
• Lastly, banks, like organisations across all sectors, are looking into the opportunities and risks that quantum computers and algorithms could bring. Opportunities in terms of portfolio optimisation, fraud detection and risk management; and on the other side of the coin, quantum-enabled cybersecurity risks.
• Experts predict that mainstream use of these ‘super computers’ is five to 10 years away. For banks, use of quantum capabilities involves potential collaboration across government, industry, academia, investors and starts ups. The gathering of the best minds is mission-critical in light of the fact that quantum computers will one day become powerful enough to break many cryptographic algorithms used across financial services systems to protect data and communications. Financial institutions are therefore exploring the need to transition their systems to quantum-safe cryptography with a quantum-literate workforce.

Read more on the topic: 

• Fintech Magazine: Bank complexity costs industry $50bn annually

• Snowflake: AI in Investment Banking

• McKinsey Global Banking Annual Review 2024

• CEO Insight: Blockchain in banking

• BNP Paribas: Fintechs: the partnerships reshaping investment banking

• IBM Quantum Safe: financial services