PUBLISHED DATE: 2025-08-25 08:11:07

Next-Gen Transaction Banking: Unlocking Working Capital with AI

Introduction: The Shifting Landscape of Transaction Banking

In the ever-changing realm of transaction banking, the efficient management of working capital has emerged as a pivotal focus. The pursuit of unlocking working capital has gained substantial momentum in recent times, propelled by a market landscape that demands adaptability and innovation. Pressures on costs and prices for companies will put further stress on cash positions and working capital for businesses, underscoring the importance of accurate liquidity forecasting.

Several banks have embarked on the exploration of artificial intelligence to harness their data resources to deliver more sophisticated customer experiences and solutions. This landscape presents an extraordinary opportunity for banks: first, to expand their working capital franchise by helping companies run more efficient balance sheets; and second, to seamlessly integrate into the client’s ERP system without requiring coding, resulting in substantial time and cost savings, and facilitating the transition from traditional banking to invisible finance.

Market Overview

Evolving Corporate Expectations

Corporates now expect a 360-degree view of cash management and fast time to funds. Key statistics include:

This complexity emphasizes the need for integrated, seamless, and embedded tools to efficiently manage diverse banking connections and aggregate data into a unified platform. Financial institutions are increasingly incorporating open banking APIs, enabling effortless integration with their corporate clients’ ERP systems. Corporations prioritize swift access to working capital finance and real-time visibility into account balances across all banking relationships.

The Rise of Fintechs in Transaction Banking

The transaction banking landscape is being transformed by fintechs leveraging advanced technologies to address long-standing industry pain points. Their agility and customer-centric approach have enabled rapid traction, especially in payments, cash management, and supply chain finance. Fintechs are setting new standards for speed, transparency, and efficiency, using AI, machine learning, and data analytics to offer tailored solutions. This has intensified competition and prompted traditional banks to accelerate their digital transformation initiatives.

Venture capital investments in B2B transaction banking fintechs in the U.K. constitute 12% (£22 billion) of the global funding pool (£180 billion). Key areas of investment include embedded payments, insights as a service, B2B BNPL, and Gen AI TMS.

Selected Examples of Traditional Banks Innovating in Working Capital Solutions

Navigating Working Capital Challenges: The Top Three Hurdles

  1. Legacy Technology and Data Quality Issues Hinder AI Innovation
    • 51% of banks cite fragmented and siloed technology as the primary impediment to growth.
    • 40% cite scalability limitations of existing systems as major challenges.
    • 52% have yet to provide open banking services.
    • Outdated technology and data quality issues hinder the realization of a connected ecosystem.
    • Building in-house AI solutions is costly and time-consuming, with a shortage of top-level professionals and significant computing resources required.
  2. Client Experience and Efficiency Expectations Are Not Being Met
    • Corporates struggle to consolidate technology stacks and aggregate external business arrangements.
    • 62% seek a single, real-time view of their company’s bank balances.
    • 65% highlight onboarding and KYC processes as the biggest challenges.
    • 51% desire seamless integration of bank and corporate processes.
    • 23% report their bank does not offer ERP integrations; 25% say their bank lacks an experienced relationship team.
  3. Inadequate Servicing Support and Sales Tools Are a Barrier to Growth
    • 42% of corporate treasurers consider digital servicing and experience important.
    • 44% are contemplating changing providers for better digital experience.
    • 48% rate their digital servicing experience as “average to poor.”
    • Cross-selling of working capital products is below 29% in Western Europe; 14% of banks see existing cross-selling as a hindrance to growth.

Corporates expect seamless interactions through invisible channels and product categories across their multibank relationships and are fast adopting open banking as it evolves towards an embedded framework for ERP Banking.

A Game-Changing Vision for Managing Working Capital

Embedded Banking and Generative AI: ERP is the New Digital Bank for Corporates

Effective working capital optimization provides immediate relief from liquidity challenges and positions organizations for growth. Corporates often struggle to consolidate technology infrastructure and aggregate working capital positions, especially with multiple banking relationships. For example, a mid-to-large enterprise may need to issue credentials to hundreds of employees across more than 10 online banking systems, making manual calculations of total working capital labor-intensive and inefficient.

62% of corporations are actively seeking a unified, real-time overview of their company’s bank balances and seamless interactions across channels and product categories. They are rapidly embracing open banking and open finance as key enablers for embedded lending experiences. Corporate clients expect a single dashboard displaying real-time working capital positions by aggregating data from banks and third parties.

A personalized, AI-powered dashboard with multibank integrations, generated in minutes and embedded as a plug-and-play ERP-agnostic widget, can provide a comprehensive ERP banking solution. By merging generative AI and embedded banking, the ERP system evolves into a cutting-edge digital bank for corporate clients. The client experience follows these stages:

  1. Access Gen AI ERP app builder via online banking: Clients use a Gen AI tool and prompts to quickly architect a personalized dashboard, minimizing or eliminating the need for engineering integrations. Data sources (multiple banks and ERP) are identified, visualizations selected, and the app deployed in the ERP.
  2. Embed custom AI-dashboard app in ERP: Clients see past and future working capital in one place, with real-time access via ERP and mobile channels. Authorized signatories can approve payment requests via push notifications.
  3. Receive AI-based proactive forecasts & solutions: The dashboard provides AI-based forecasts, alerts, and solutions, such as notifications of anticipated working capital shortfalls and personalized suggestions to fill cashflow gaps.
  4. Get pre-approved working capital finance: Smart alerts inform clients of pre-approved products to solve or optimize working capital. The dashboard enables cross-sell and upsell of personalized products, such as trade order credit extensions and letters of credit.
  5. Secure same-day credit decisions & funding: Underwriting is fully automated for pre-approved invitations, facilitating real-time credit decisions and same-day disbursement.

Outcomes

Value Enablers

This transformational client journey underscores the potential of embedded banking and generative AI, revolutionizing how clients manage their finances, make data-driven decisions, and optimize working capital in a fast-paced, competitive landscape.

Delving Deeper: The No-Code Vision

The Gen AI ERP App Builder: How Does It Work?

Offering corporate clients access to a Gen AI chat interface and prompts to efficiently create a customized, intelligent, multibank dashboard that can be embedded into any ERP system as a widget is a groundbreaking proposition. The entry point is the primary bank’s secure online banking channel. This approach automates secure and cost-effective API integration, eliminating the need for coding and potentially for hiring engineers.

Clients can quickly establish connections with all data sources, integrate their ERP system with multiple banks, and tailor data visualizations by selecting layouts and components on the fly. The result is a customized, scalable solution providing a single point of entry for working capital management in minutes.

Proposed Workflow:

  1. OpenAI integrations: Gen AI tooling, guardrails, and enabler platform setup. Use prompts and an LLM-powered approach to build the custom dashboard. Identify data sources (open API integrations with multiple banks and ERPs). Create a dataset with a library of dashboard components.
  2. Data visualization: Custom dashboard creator. Pick components from a library using prompts and an “insights miner” to select key visualizations. Implement logic to fetch and process data, render visualizations, and handle real-time updates. Enable the AI dashboard to connect with multiple banks and one ERP system. Generate a cloud-based approach that can be embedded into an ERP system.

A Smart Dashboard: One-Stop Shop ERP Banking Solution

  1. Total working capital
  2. 30-60-90 day projection of financial position
  3. Top five banking relationships
  4. Top five clients
  5. AI-based forecasts and smart notifications
  6. Personalized suggestions and solutions
  7. Intelligent upsell and cross-sell of pre-approved deals
  8. Conversational AI

Customization, speed, cost reduction, competitive edge, and scalability are all enabled by leveraging proprietary data and machine-to-machine integration.

Responsible Use of Generative AI

While 67% of senior IT leaders are prioritizing generative AI for their business within the next 18 months, concerns remain:

Recommendations to address these challenges include focusing on intellectual property, data security, and liability.

Gen AI ERP App Builder → AI Generated Dashboard → ERP

Channels: Web, mobile, call center, branch, AI-as-a-Service
Direct and assisted channels, APIs/3rd party integration

Core Functions: Identity and access management, product pricing engine, credit risk analysis, credit decisioning & underwriting, AML & fraud, KYC/Personal ID&V, CRM, marketing, sales & origination, customer support, intelligent workflow orchestration

Industrialized AI: Enterprise modeling services, shared AI services, data core, data management, finance & accounting, general ledger, support systems (HR, service center, workspace collaboration, etc.), Gen 4 core, domestic & international payments, check and cash management, document and collateral, collection and recovery, communication, cloud foundation

Key Layers of the Value Chain

  1. Applications: End user-facing B2B and B2C applications integrating generative AI models
  2. APIs: Access to generative AI models through APIs
  3. Models: Three types of AI engines powering products, available as proprietary APIs or open-source checkpoints
  4. Infrastructure: Accelerator chips optimized for model training and inference, exposed in a cloud deployment model
  5. Regulatory compliance: Training data and model outputs to mitigate risks, address privacy, and ensure legal compliance

Case Study Examples (Redacted)

Illustrative Use Case

  1. Applications: Distribute end-user application (e.g., Kasisto, Flagright, JPMorgan)
  2. API layer (AI OS): AI model as a Service (e.g., Kasisto, Monstarlab API)
  3. Models: Generic AI, specific AI, hyperscale AI (e.g., Kasisto, Flagright, Trade Ledger, JPMorgan)
  4. Infrastructure: Compute, hardware, cloud platform (e.g., AWS, NVIDIA, Google, Oracle, Microsoft)
  5. Regulatory compliance: In-house responsible Gen AI framework (e.g., Flagright, Trade Ledger, JPMorgan)

Value Chain Ownership: Bank & Partner

Value for Bank:

Speed of Market Entry:

Value for Bank’s Corporate Clients:

Quantifying the Benefits: AI-Model-as-a-Service (Illustrative Example)

A strategic investment of £12M-£15M could yield an estimated total benefit of £110M+ over three years:

Imperatives for a Value-Driven Strategy

AI-First Value Proposition: Building a Working Capital Solution One-Stop Shop (Illustrative Example)

Our value proposition comprises three interconnected product initiatives forming the foundation for ERP banking and new revenue streams. Every financial transaction originates and concludes within the management software, seamlessly integrated into the ERP system—the new face of digital banking.

The Gen AI ERP App builder generates a personalized AI-powered dashboard embedded in the client’s ERP, serving as a comprehensive hub for working capital solutions. By proactively forecasting future working capital gaps and suggesting remedies, the bank can intelligently promote a wide range of pre-approved finance deals to eligible clients. Scalable distribution and a proprietary AI model enable AI-as-a-Service licensing and expansion through partners, generating additional revenue streams and exponential growth.

Illustrative Three-Year AI-First Strategy:

Driving Impact: Working Capital Solutions

The Proposal

Publicis Sapient can develop a product strategy leveraging generative AI as the game-changer for your business.

  1. Define your value chain ownership: Determine the business model and investment case, exploring roles within the generative AI modular capability stack.
  2. Shape a unique value proposition: Develop a vision tailored to your business needs, identifying key value components to drive benefit potential.
  3. Target strategic roadmap: Create an incremental roadmap to capture the vision and sequenced building blocks of the holistic value proposition.
  4. Conceptual target architecture: Provide a target architecture aligned with strategic direction for a generative AI-driven enterprise, facilitating unbiased vendor assessments for a successful PoC.

Next Steps: The First Engagement

Publicis Sapient recommends an initial 12-week engagement to develop the essential components of a digital vision, linking with a progressive technology modernization strategy and launching you into the coreless era.

Contact

To find out more about how we can help your working capital and generative AI strategy, please contact:

Manas Saha
Head of Commercial Banking and Capital Markets
Manas.saha@publicissapient.com

Special thanks to all contributors for their invaluable insights and support in shaping this playbook: Ronnie Mitra, Varun Mathur, Hari Sahay, Korbinian Krainau, Cristina Carion, Iason Gkomozias, Joel Huang

About Publicis Sapient

Publicis Sapient is a digital transformation partner helping established organizations get digitally enabled, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting and customer experience with agile engineering and problem-solving creativity. As digital pioneers with 20,000 people and 53 offices around the globe, our experience spanning technology, data sciences, consulting and customer obsession—combined with our culture of curiosity and relentlessness—enables us to accelerate our clients’ businesses through designing the products and services their customers truly value. Publicis Sapient is the digital business transformation hub of Publicis Groupe.

For more information, visit publicissapient.com

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