Liquidity constraints force corporate banking shift

5 February 2025

Corporate lenders face a liquidity crunch as businesses struggle to maintain cash flow amid rising costs and tighter credit conditions. Credit constraints have worsened, with 5% of middle-market borrowers now heavily leveraged and unable to refinance, according to credit rating firm KBRA. At the same time, rising fraud and outdated payment infrastructures are compounding the liquidity challenge.

Payment fraud losses are expected to reach $26.4bn by 2028, according to GlobalData, making cash flow forecasting even more unpredictable. Increasing cyber threats, unauthorised fund transfers and fraudulent transactions directly impact liquidity buffers, forcing businesses to enhance treasury functions.

Slow settlement cycles and outdated infrastructure continue to choke liquidity, restricting businesses’ ability to manage cash flow. To stay competitive, lenders must rethink their support for corporate clients by ensuring faster access to funds, smarter risk controls and seamless financial integration.

The pressure to deliver faster, more secure and smarter financial solutions is increasing. Innovations such as real-time payments (RTPs), artificial intelligence (AI)-driven risk models and embedded finance address these needs by enhancing liquidity management, improving credit allocation and streamlining cross-border transactions. Lenders that fail to adapt risk losing corporate clients to more agile competitors.

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AI reshapes liquidity strategy

AI is transforming liquidity management, shifting from a compliance and fraud detection tool to a key driver of treasury optimisation. Lenders are using AI-powered forecasting to improve treasury operations, helping businesses anticipate cash flow needs, automate funding decisions and optimise capital allocation.

HSBC’s AI-driven treasury solutions have improved forecasting accuracy by 92%, reducing liquidity risk for businesses operating across multiple markets. JP Morgan has also adopted AI-driven liquidity forecasting, enabling clients to optimise cash reserves and enhance working capital efficiency.

AI optimises liquidity management while strengthening security, helping lenders counter fraud and financial crime in an increasingly digital landscape. Lenders are leveraging AI’s predictive power to detect anomalies and security threats before they escalate.

Fraud detection remains a key priority as financial crime becomes more sophisticated. Many lenders are deploying AI to enhance fraud detection and risk mitigation. For instance, Mastercard and Stripe use AI-driven risk models, analysing over 1,000 transaction data points per second to detect fraud in real time.

Integrating AI into treasury services not only enhances operational efficiency but also positions lenders as strategic partners, offering data-driven insights that strengthen corporate client relationships.

Real-time payments drive liquidity optimisation

RTPs are now central to working capital strategies, not just a speed upgrade. Corporate clients increasingly expect instant settlements and real-time liquidity visibility as standard banking features.

The global RTP market is projected to surpass $700tn by 2028, according to GlobalData, as demand grows for seamless cross-border transactions, reduced credit dependency and faster cash conversion cycles. This shift is critical for treasury and finance teams, which require greater control over cash positions to navigate fluctuating market conditions.

Payment infrastructure providers such as Swift GPI and Visa B2B Connect have already streamlined high-value international transactions, reducing settlement times from days to minutes. These advancements are reshaping corporate banking priorities, with lenders expected to embed real-time payment capabilities within their broader treasury services.

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Embed finance or lose relevance

Corporate banking is shifting away from traditional, bank-led services as embedded finance transforms how businesses access payments, liquidity and credit directly within their operational platforms. By integrating financial products within enterprise platforms and enterprise resource planning (ERP) software, companies reduce dependence on external bank portals.

GlobalData forecasts that corporate embedded finance will exceed $7tn by 2030, driven by demand for frictionless cash flow management, instant access to financing and automated treasury functions. Businesses are embedding banking services within their digital ecosystems, integrating payments, lending and cash management into their core platforms.

Major banks are already adapting. Goldman Sachs and Citi have developed embedded lending and treasury tools that integrate directly into ERP systems, enabling businesses to initiate payments, access credit and manage liquidity without switching platforms.

Banks that fail to embed financial solutions risk losing visibility over corporate transactions. Institutions that successfully integrate embedded finance into their offerings will strengthen corporate relationships and secure long-term revenue streams. Conversely, delaying digital integration may result in businesses managing financial operations independently within their own platforms, reducing banks’ role in liquidity management.

How lenders must adapt to the liquidity shift

The future of corporate banking is being shaped by AI-driven treasury solutions, real-time payments and embedded finance—all of which are rapidly transitioning from competitive advantages to industry standards.

For banking leaders, this shift demands immediate action.

Corporate clients are no longer just looking for lenders – they need strategic partners who can provide seamless liquidity management, intelligent forecasting and embedded financial solutions.

Banks that embrace these innovations will strengthen corporate relationships, drive new revenue models and maintain relevance in a shifting financial landscape. Those that hesitate risk being replaced by more agile, tech-driven competitors offering faster, smarter and more integrated financial services.

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Sarah Rizvi
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