March 2026
The Strategic Value of Data and Deal Management In Bank Modernization
Enrico Camerinelli
Prepared for: CSG International
Executive Summary
Clients move away from banks whose technology can’t keep pace with their expectations, shifting dramatically the competitive landscape for financial institutions . 80% of midsize and large corporate clients now partner with fintech providers, and 54% of small to large businesses have adopted alternative payment solutions. This client migration threatens traditional banking relationships, and it's not about pricing. It's about technology gaps that banks still haven't addressed.
Recent market research shows a troubling disconnect: while 100% of U.S. mid-tier banks plan moderate to significant investments in payments technology and banking application ecosystems over the next 24-36 months (most allocating $US 5-20 million), many struggle to see real returns on these investments. The problem goes beyond how much they're spending. It's how they're deploying these resources across the modernization landscape.
Corporate clients increasingly switch to providers offering better functionality and tighter integration with their internal systems. For banks, delivering these capabilities profitably requires more than incremental modernization, it demands integrated data across the system estate and pricing models that reflect how services are consumed and valued. Without these foundations, investment scale alone cannot prevent client attrition. As a result, two capabilities have become critical to competitiveness: comprehensive data management and end-to-end deal lifecycle management.
Banks that continue to treat these capabilities as back-office concerns will struggle to compete in a market where data-driven pricing, payments, and integration define client choice.
Two capabilities matter most for reversing client attrition and unlocking the value of digital transformation: comprehensive data management and end-to-end commercial lifecycle management to monetize the value of integrated data. Banks that master these disciplines create competitive advantages across multiple dimensions: real-time payment orchestration; ISO 20022 compliance; automated pricing workflows; and revenue optimization. Banks that keep treating these as back-office functions will find themselves unable to compete.
The numbers make this urgent: 32% of bank corporate clients already use ISO 20022 messaging formats, with another 43% planning adoption. Many are proceeding with or
without their bank's support. Forty-five percent of mid-tier bank business customers expect their real-time payment usage to increase in the next 12 months.
This report shows how banks can learn from other highly regulated industries that have successfully navigated similar transformation challenges. As an example, telecom operators mastered data integration and commercial lifecycle management while managing comparable legacy complexity and regulatory constraints. The path forward requires technology investment united to organizational commitment, strategic vision, and systematic execution informed by proven approaches to modernization.
The key findings from this paper follow:
• Data management serves as foundational infrastructure enabling banks to extract, transform, and route transactional data across systems, supporting real-time orchestration, quality controls, rule-based validation, and ISO 20022 compliance that corporate clients increasingly demand.
• Banks can accelerate transformation by adopting proven data integration strategies from other highly regulated industries that offer blueprints for modernizing data integration, lifecycle management, and cloud environments while maintaining infrastructure compatibility without operational disruption.
• Deal lifecycle management addresses fragmented pricing structures, lengthy manual approval processes, and revenue leakage through comprehensive solutions that span across negotiation, pricing, approval workflows, implementation, and performance tracking.
• The combination of data management and deal lifecycle capabilities creates multiplier effects, transforming operational efficiency gains into strategic advantages in client acquisition, retention, and revenue optimization
Introduction
The banking industry and its clients are modernizing, accelerating the need for all stakeholders to be fully prepared for the transition. Alongside large financial institutions (FIs) pouring billions into digital transformation, mid-tier banks are also actively participating in the broader industry push toward payments modernization. They all plan to make at least a moderate investment in commercial payments technology over the next 24 to 36 months (Figure 1), with the majority allocating between US$5 million and US$20 million
Q. How much investment in commercial payments technology to improve payments do you expect your institution to make in the next 24 to 36 months?
(Base: 45 bank executives at mid-tier banks who contribute/are responsible for commercial payments strategy)
Significant degree of investment
Moderate degree of investment
Source: Datos Insights survey of 200 bank executives, Q2 2024
Yet the gap between investment and value keeps widening. The real threat isn't coming from traditional competitors. It's client behavior: 80% of corporate clients (irrespective of their company’s revenue size) now work with nonbank payment providers for one or more cash management or payment services. 55% of mid-to-large organizations have already adopted fintech solutions for their basic banking operations (Figure 2)
Figure 1: Investment In Commercial Payments Technology To Improve Payments
Figure 2: Corporate Users Partner With Non-FIs
Q. Does your organization currently work with any fintech firms (directly for cash management or payment services
Smaller mid-market organizations (less than 500 employees)
Larger mid-market organizations (up to 1,000 employees)
Yes, for 1 cash management or payment service
Yes, for 2 or more cash management or payment services
No, but plan to
Large organizations (over 1,000 employees)
Source: Datos Insights survey of 1, 036 midsize and large businesses, Q3 2025
These migrations hit revenue immediately and put entire relationships at risk. Corporate clients are moving business elsewhere, and they're clear about why: "better functionality" and "better integration" (Figure 3).
Figure 3: Why Organizations Work/Plans To Work With A Fintech Firm
Q. What are the main reasons your organization works/plans to work with a fintech firm in addition to its financial institution?
More payment options
Better or automated payment reconciliation
Better functionality
Better integration with internal systems
Easier to submit a payment file
Access to real-time payments
Better reporting
Source: Datos Insights survey of 1, 036 midsize and large businesses, Q3 2025
Technology has replaced rates and fees as the main competitive differentiator. Banks that fail to modernize face disintermediation from critical client touchpoints. They risk becoming commoditized service providers while fintech vendors capture the valuable interfaces and data insights.
This paper examines what banks need to do now and identifies the operational capabilities required to compete in this transformed environment. Three market trends are converging to create immediate pressure on how data is managed (and monetized):
1. ISO 20022 migration is accelerating ahead of bank readiness
2. Real-time payment adoption is driving new infrastructure requirements
3. Legacy modernization is meeting the reality of cloud migration
This report is written for bank executives, technology leaders, and strategic planners who need a framework for understanding how data management and commercial lifecycle capabilities can transform competitive disadvantages into client retention strategies. The stakes are significant. Institutions that master these capabilities can compete without matching the capital investments of larger competitors. Those that delay face a compounding disadvantage as client expectations keep outpacing institutional readiness.
Methodology
This report draws upon proprietary 2025 Datos Insights market research data including: Q2 2024 survey of 200 global payments banks and product executives in North America, Europe, and Asia-Pacific; Q3 2025 survey of 1,036 midsize and large businesses generating annual revenue of at least US$ 20 million; Q1 2025 survey of 1,004 U.S. SMBs generating revenue between US$100,000 and US$ 20 million.
Wide-ranging conversations with industry experts, solution providers operating in data management and deal management domains, and practitioners; Analysis of telecommunications industry transformation patterns; The author's extensive market knowledge and research.
Market Trends That Are Creating Transformation Pressure
ISO 20022 isn't just another compliance checkbox. While it is a new messaging standard banks need to adopt, its real impact lies in how financial institutions communicate, process and derive value from transaction data. The standard lets banks transmit richer, more structured data with payment instructions. That means automated processing, easier reconciliation, and analytics that used to be a nightmare to pull off or achieve at scale. The challenge is timing. Corporate clients are moving faster than the banks themselves. Right now, 32% of bank corporate clients already use ISO 20022 formats. Another 43% plan to adopt it. And they're not waiting around (Figure 4)
Figure 4: Organizations’ Plans Concerning ISO 20022
Q. Please select the statement that best describes your organization's plans concerning ISO 20022
My organization already uses ISO 20022 messaging formats
My organization has a plan to utilize ISO 20022 in the future
My organization is waiting to learn more about ISO 20022 from our partners before making a decision on deploying it
Source: Datos Insights survey of 1, 036 midsize and large businesses, Q3 2025
These clients are implementing ISO messaging through their treasury management systems and third-party platforms whether their banks are ready or not. This creates a growing disconnect between client expectations and bank capabilities.
Banks that treat ISO 20022 as a surface-level format conversion risk falling further behind as volumes increase and real-time schemes become the norm Fast execution is no longer enough. Banks that process transactions quickly but take forever to extract usable data are losing clients to competitors who do both well. On the flip side, institutions that nail fast execution while making data immediately useful turn speed into something more than an operations metric. It becomes a reason clients stick around
As messaging standards evolve and new requirements are introduced, banks without a scalable, technology-backed data foundation face repeated remediation cycles, higher operational costs, and longer delays to value. By contrast, banks that embed ISO 20022 into their core data architecture, treating it as an enterprise data standard rather than an external interface, turn compliance into a strategic asset. Banks that get this right strengthen their role at the center of corporate financial ecosystems. Those that don’t risk being sidelined by providers that already have.
Real-Time Payment Adoption Drives Infrastructure Requirements
On average, 40% of mid-to large tier bank business customers expect to use real-time payments more in the next 12 months (Figure 5). This rapid adoption compresses timelines across the entire transaction lifecycle, from initiation and settlement to reconciliation and reporting, and leaves little tolerance for fragmented or batch-oriented systems.
Figure 5: Plans To Utilize Real-Time Payments
Q. What are your plans to utilize real-time payments in your organization?
Smaller mid-market organizations (Base= 324)
Larger mid-market organizations (Base= 370)
Large organizations (Base= 342)
Source: Datos Insights survey of 1, 036 midsize and large businesses, Q3 2025
Already use
Plan to use in next 12 months
Plan to use in next 13 to 24 months
Plan to use in more than 24 months
That means banks need real time payments connectivity now, along with the operational infrastructure to actually support these rails. But connecting to the rails is just the start. Corporate clients expect real-time payments to integrate seamlessly into existing processes, including treasury operations, reconciliation workflows and accounting platforms. They want instant transaction visibility, immediate settlement confirmation, and confidence that downstream processes can keep pace with real-time execution Delivering on these expectations requires sophisticated data management infrastructure that can orchestrate transactions, validations, and data flows continuously and at scale. Banks without this infrastructure are falling behind, and the gap keeps growing. As more businesses adopt real-time payments, fintech providers are stepping in with specialized solutions, but many still rely on delayed data extraction, manual reconciliation, or disconnected systems that often create friction where clients expect speed and clarity
Providers that combine fast execution with immediately usable data turn real-time payments into a differentiated service rather than a commodity feature.
This gap creates opportunities for fintech providers and specialized platforms that wrap real-time payments in clean integrations, analytics, and value-added services. The reality is that competitiveness in real-time payments encompasses the entire data and operational ecosystem that makes those capabilities actually work, and generate profitable results.
Banks that fail to address this holistically risk being reduced to processors, while those that do can use real-time payments to strengthen client relationships, unlock new revenue models, and reinforce their role at the center of corporate financial workflows.
Legacy Modernization Meets Cloud Migration
Reality
Most banks know their old systems are holding them back. Eighty-six percent of mid-tier banks are moving to hybrid cloud strategies. Sixty percent want public cloud deployments (Figure 6) These shifts reflect more than a preference for new technology; they signal a growing recognition that existing architectures are no longer fit for the pace of change banks' face.
Figure 6: Preferred or Target Operating Model For Payments Processing
Q. What is your preferred or target operating model for payments processing? Select all that apply (Base: 119 mid-tier banks)
Source: Datos Insights survey of 200 financial institutions, Q2 2024
These aren't small tweaks to how banks think about technology. Banks aren't doing this because they love new tech. They're doing it because legacy systems make everything harder: launching new products takes too long, integrating with fintech partners is costly and complex, and IT teams spend disproportionate effort maintaining aging systems rather than enabling growth. As costs rise and client expectations accelerate, banks can
no longer afford multi-year delays every time they introduce a new service, pricing model, or payment capability. Banks are starting to experience the benefit of cloud platforms let mid-tier banks compete without spending like the big players do. They get access to sophisticated tools that scale up or down as needed.
Other highly regulated industries (e.g., in the telecom sector) have navigated this transition. They modernized by introducing flexible data and integration layers that decoupled innovation from core platforms. Now they can launch new services in weeks instead of months. Their fraud detection improved. Customer analytics got better. They proved that hybrid approaches can be used while still modernizing, without forcing disruptive “big bang” transformations.
Banks can learn from what worked for them. Modernization must accelerate change, not delay it. Institutions that establish scalable data and integration foundations alongside their legacy environments can move faster and monetize new capabilities sooner. Those that do not risk falling into a permanent holding pattern, investing heavily in time-intensive transformation programs while competitors and fintech players continue to outpace them.
Data Management Is The Foundation For Competitive Advantage
Data management used to be a back-office function. Now it determines whether banks can translate their digital transformation spending into real business outcomes The ability to extract, transform, and move transactional data across systems affects everything, from compliance, to operations, to customer experience, down to revenue growth.
This matters because data management is the foundation for everything else banks are trying to build. It is not possible to run native ISO20022 transactions, or real-time payments in a fragmented environment that is dependent on real-time data orchestration. Analytics and AI are only as good as the data fed into their algorithms. Better customer experiences demand integrated views across all of a FI’s systems. And compliance requires solid governance and the ability to audit at scale. Without strong data foundations, a bank’s modernization projects will underperform no matter how much money is invested.
As the pace of change accelerates, the gap between banks with strong data capabilities and those without continues to widen. FIs that rely on batch-oriented data movement, manual reconciliation, or tightly coupled legacy integrations find that every new initiative takes longer, costs more, and delivers less value than expected. By contrast, banks with modern data orchestration layers can introduce new payment types, pricing models, and partner integrations without waiting for core-system timelines. For these banks, data is not just an enabler; it is a competitive advantage
Leading banks get this. They're hiring C-suite data executives who push these initiatives forward and keep them tied to business goals. Formal governance committees show they're serious about accountability and getting different departments to work together. Structure matters just as much. High-performing banks either create dedicated data organizations or use federated models with clear responsibilities. They put data analysts and experts inside business units so the insights actually stay relevant and useful
Structure and governance alone are not enough. To turn strategy into execution, banks need data management capabilities that operate across legacy and modern environments, support real-time use cases, and give business teams confidence that data is accurate, timely, and actionable. Those that succeed in building momentum will use data to
accelerate transformation. Those that do not risk repeated reinvestment with diminishing returns, as competitors move faster and clients gravitate toward providers that can deliver both speed and insight.
Transactional Data Management Is A Collection and Orchestration Engine
Transactional data management is where strategy becomes execution. As organizations respond to industry demands like ISO 20022 adoption, real-time payment support and legacy modernization pressures, FIs increasingly rely on transactional data management platforms that consolidate information from disparate sources across the organization. These platforms handle both real-time and batch processing at enterprise scale, applying business logic to format and route data appropriately for each target application. The most effective implementations combine real-time orchestration with rigorous quality controls, rule-based validation, and adherence to industry standards. Done right, transactional data management transforms regulatory compliance into a competitive edge, and paves the way for profitable results.
Modern banking environments are inherently complex. They involve multiple interconnected platforms for core banking, billing, and product delivery. Corporate clients engage through various channels: online banking portals; mobile applications; API integrations with treasury management systems; file-based transmission protocols. Transaction data flows through clearing networks, payment rails, and intermediary processors. Each adds layers of structured and unstructured information. Without a unifying orchestration layer, this complexity becomes a barrier to speed, transparency, and control.
Transactional data management platforms provide centralized capability to ingest data regardless of source, format, or protocol. The platforms align data structures, enrich with additional context, perform aggregation and transformation, and route output to target applications in required formats. This operates at massive scale, handling billions of events efficiently while maintaining data integrity and processing speed across hybrid legacy and cloud environments.
The business payoff is tangible. Banks with sophisticated data management capabilities detect fraud patterns before escalation and identify credit risks earlier in lending cycles. They ensure regulatory compliance through automated monitoring and reporting. Customer experiences improve through immediate data availability. What used to be nice-
to-have features are now table stakes as regulatory environments evolve and customer expectations increase
For banks, transactional data management is no longer an infrastructure concern. Rather, it’s a prerequisite for competing in a real-time, ecosystem-driven market. FIs that invest in technologies for orchestration and control gain the flexibility to scale new payment types, integrate partners faster, and extract value from data as it moves. Without these investments, banks risk remaining constrained by fragmentation, manual workarounds, and delayed insight, even as transaction volumes and expectations continue to rise.
Modern banks are in a constant state of change, integrating new platforms, onboarding fintech partners, responding to regulatory shifts, and expanding digital capabilities. Good data management provides a foundation to support this evolution, helping to manage change without disrupting operations or slowing innovation This takes on increasing importance when pursuing M&A opportunities. Financial institution M&A is picking up again after years of quiet, which makes this especially relevant right now. Regulatory easing makes M&A easier and reducing time to realize benefits. Stabilization of interest rates makes M&A more favorable. Stable rates increases valuation accuracy and makes it easier to agree on purchase prices. There is an opportunity to acquire digital capabilities, APIs, and fintech partnerships. Data integration helps to stay competitive in a rapidly digitizing financial landscape, and determines how quickly the benefits are realized
Other highly regulated industries learned this the hard way during their big consolidation period. Those that survived realized something important: mergers succeed or fail based on how well data is integrated As an example, telecom operators had to combine customer bases, align product catalogs, consolidate billing systems, and harmonize everything between organizations that had been separate. The operators that succeeded built integration platforms that could map between different systems, transform data formats, apply business rules, and keep service running during the transition.
Banks hit the same problems during acquisitions. They're consolidating customer information across different core banking systems. They're aligning product structures and pricing, and integrating transaction histories while maintaining regulatory compliance. FIs with mature data capabilities get through this faster and with fewer operational disruptions. They realize cost synergies quicker than banks still working with outdated infrastructure.
Beyond M&A, the same capabilities allow banks to respond faster when regulations change. They deploy new products quicker. They integrate fintech partnerships more
smoothly. They can experiment with new business models at lower risk because their data infrastructure gives them controlled environments for testing without disrupting production. And they get better results from analytics and AI because their data quality and accessibility actually let the algorithms work properly
Cloud and Platform Approaches Represent The Technology Advantage
The widespread shift to hybrid cloud architectures reflects a practical reality, not a passing trend. If eighty-six percent of mid-tier banks have moved to hybrid cloud approaches (Figure 6), they're not doing this because it's trendy. They know modern data management needs infrastructure that can flex and scale. Traditional on-premises systems struggle to keep pace. Implementations take longer, cost more, and new capabilities cannot be adopted nearly as fast.
For data‑intensive use cases (e.g., ISO 20022 processing; real‑time payments; ecosystem integration), these limitations can become structural constraints, making it difficult to support real time orchestration, rapid onboarding of partners, or continuous change. As a result, FIs tied too closely to legacy deployment models find that even well designed data strategies are slowed by the underlying technology foundation.
Cloud platforms change this equation. FIs can spin up new data processing without dropping budgets on infrastructure. When volume spikes, they scale up. When it drops, they scale down. No need to buy capacity that will be rarely used. Standard APIs mean that banks can actually connect with the fintech ecosystem instead of building custom integrations for everything. Updates happen continuously, so there’s no more need to shut down for weekend upgrades. Cloud platforms level the playing field, providing access to advanced tooling, proven architectures, and specialized expertise without requiring banks to overbuild infrastructure or lock capital into long term capacity decisions. Mid-tier banks don't need to match the capital spending of Tier1 institutions. They subscribe to platforms that give them sophisticated functionality at a fraction of the cost. They get specialized expertise and tested playbooks. Less risk, faster results.
Other highly regulated industries have already demonstrated the impact of this shift. Telecom operators use cloud and platform strategies to decouple innovation from infrastructure . They launched services in weeks instead of months. Their fraud detection got better. Customer analytics improved. And when regulations changed or competitors moved, they could respond fast.
Banks making the same moves see the same benefits when cloud adoption is paired with modern data management capabilities This isn't about picking a technology vendor. It is about creating a technology environment that supports continuous change, real time data orchestration, and scalable integration. In a market defined by speed, ecosystems, and data driven services, cloud enabled platforms are no longer optional. It's about becoming agile enough to survive.
Deal Lifecycle Management Monetizes Data And Strengthens Relationships
With modern data management in place to support ISO 20022, real time payments, and platform modernization, banks face a second, equally critical challenge: converting operational capability into sustainable revenue while managing increasingly complex commercial relationships Modern corporate and business banking has evolved far beyond simple transactional services. Clients now expect flexible pricing, tailored product bundles, and commercial terms that reflect the size and scope of their business
The challenge for most banks lies not exclusively in customer demand, but in operational complexity. Historically, relationship banking was achieved through significant manual calculations, spreadsheets, and fragmented approval processes, leading to inevitable mistakes, revenue leakage, and lack of scalability. This meant most FIs were less able to offer profitable bespoke deals and nurture relationships effectively with high-growth and mid-tier companies. Precisely the segments showing greatest willingness to explore alternative providers (see Figure 2.)
The challenge grows as corporate banking relationships span multiple products and services. Each comes with its own pricing model, discount approach, and volume requirements. Banks without centralized deal lifecycle management can't keep negotiated agreements aligned with contracts and the systems that actually implement pricing. The likely result is money slipping through the cracks. Pricing errors go unnoticed. Relationship managers can't see the full picture of what a client is worth, and bundled deals don't deliver the returns they should. Approval workflows add to the problem. Complex deals need sign-off from relationship managers, product specialists, risk officers, compliance, and executives. When approvals run manually, deals can take weeks or even months to close. Corporate clients who get quick decisions from other vendors find banks painfully slow by comparison. Banks that can't speed up lose business.
Experience shows that data disconnect is one of the major causes that prevent performance visibility and persists after the agreements are signed. Banks need to track actual performance against projections, monitoring transaction volumes, evaluating product usage, comparing realized revenue to forecasts, and identifying opportunities for adjustment or expansion. Manual data gathering from multiple sources limits the ability to
conduct proactive relationship management or identify issues before they impact client satisfaction.
The inability to scale personalized commercial approaches does not help with corporate clients that- instead- value arrangements that reflect their specific circumstances. Manual processes constrain banks to standardized offerings for most relationships, reserving bespoke structures for only the largest clients. Banks that have built out deal lifecycle management don't run into these problems. When negotiation, pricing, approvals, implementation, and performance tracking all live in one place, nothing falls through the cracks and revenue doesn't leak out quietly. The same pricing and bundling discipline that works for top-tier clients can be pushed down into mid-market and growth accounts, where the margin opportunity is often underestimated. Done right, deal management drives new business, keeps existing clients from walking, and protects margins.
The same dynamic playing out in data management is showing up in deal management too, and the distance between banks getting it right and those that aren't keeps growing. Banks still running deals through disconnected spreadsheets and email chains can't keep up, and they're leaving money on the table as client needs get more complicated and volumes climb. Banks that modernize deal lifecycle management actually use the data they have, closing deals faster, holding margins, and building the kind of client relationships that don't walk at renewal time, which matters more in a market where being slow or rigid is enough to lose.
Deal Lifecycle Management Is A Comprehensive Solution
As commercial relationships grow more complex, deal lifecycle management is critical in determining whether banks can scale relationship banking profitably or remain constrained by manual processes. With modern data foundations in place, deal lifecycle management is where banks convert operational capability into consistent commercial outcomes.
Deal lifecycle management platforms address these challenges through comprehensive solutions spanning the complete commercial lifecycle, from initial opportunity identification through negotiation, pricing, approval, implementation, and ongoing performance management. The most effective implementations create single source of data-integrated truth for negotiated terms, ensuring consistency between proposals, contracts, pricing systems, and operational platforms. Deal lifecycle platforms provide data
integrated environments where relationship managers negotiate commercial terms with complete visibility into customer context, comparable transactions, margin implications, and approval requirements. They access market benchmarking showing how proposed arrangements compare with industry peers of similar size and profile, enabling corporate treasurers and CFOs to make informed decisions and scale complex deals while ensuring banks maintain competitive positioning without increasing risk, margin leakage or operational friction.
These platforms support sophisticated pricing structures, such as tiered pricing based on volume, flat pricing with commitment thresholds, bundling across product categories, relationship-based discounts, and custom arrangements reflecting client-specific requirements. Relationship managers model pricing scenarios in real-time, seeing projected revenue, contribution margin, and competitive positioning before finalizing proposals. Utilizing market benchmarking provides perspective on how pricing compares with peers of similar size and profile, to help institutions maintain competitive positioning. Most critically, negotiated terms flow automatically from pricing environment into downstream systems. What appears in proposal documents matches what drives actual pricing and service delivery, eliminating manual data entry and associated error risks. This data-driven consistency builds client confidence and reduces disputes arising from misalignment between negotiated agreements and operational implementation and creates a more reliable foundation for long term relationships and expansion.
Deal lifecycle platforms enable more proactive relationship management. When a client's volumes spike or tank beyond projections, something's changed in their business, banks gain early visibility into meaningful changes in client behavior. Smart banks don't wait for quarterly reviews. They see the shift and call. "Your FX volumes doubled, what's happening?" or "Trade finance is down, finding better options elsewhere?" These conversations uncover real client needs and competitive threats. It's proactive, not reactive. Relationship teams can engage immediately to understand evolving needs, identify competitive threats, and adjust commercial arrangements accordingly.
Banks that operate with this level of visibility and control strengthen retention, protect margins, and expand relationships over time. Those that rely on fragmented, manual deal processes remain reactive, often discovering issues when it is too late, after revenue declines or competitors intervene. As with data management, deal lifecycle management increasingly separates institutions that can translate complexity into advantage from those constrained by the limits of their operating model.
Integration Matters More Than Individual Capabilities
Data management and deal lifecycle management both matter on their own, but integration is where things get interesting. It is their integration that determines whether banks can translate modernization investments into a long-term competitive advantage. When these systems work together, they create a closed loop between commercial intent and operational execution, where deals configure systems, systems generate data, and data continuously informs commercial decisions.
Data management platforms sit between the systems that capture deals and the systems that execute pricing. They're the connective tissue. They convert deal data into whatever format each system needs, send pricing updates to the right places depending on product type, check that everything implemented correctly, and watch for pricing errors across operational systems. When banks cut out manual work, they stop losing money to pricing mistakes. Client disputes drop because charges are correct. And automation just makes everything run smoother. Operational data feeds into commercial decisions enabling banks to adjust terms, identify risks, and respond to change in near real time.
Other highly regulated industry sectors have shown why integration matters. While FI and non-FI industries differ in specific products and services, they share fundamental characteristics. As an example, the telecommunications transformation experience can be directly applicable to banking contexts. Both industries, for instance, operate missioncritical systems requiring continuous availability and absolute transaction accuracy. Both maintain decades of legacy infrastructure that cannot be replaced wholesale without unacceptable service disruption. Both must integrate new capabilities with existing platforms, managing gradual modernization while maintaining operational continuity. Both face pressure to reduce operating costs while simultaneously investing in innovation. Telecom operators have managed these tensions by developing strategies for selective platform replacement, investing in integration layers that enable coexistence of old and new systems, and adopting cloud technologies to gain agility without complete infrastructure overhaul.
When commercial agreements finalize, corporate non-FI agreements mirror banking relationships in commercial complexity: multiple products and services, relationship-based pricing, negotiated terms, approval requirements, and ongoing performance tracking. The deal management platforms that- as a practical example- telecommunications companies
developed address challenges banks now confront: centralize commercial data across disparate systems; automate approval workflows while maintaining governance; ensure consistency between contracts and operational systems; provide relationship managers with tools for effective negotiation and performance tracking. These platforms evolved through years of refinement in non-FI environments before vendors adapted them for banking applications, giving banks access to mature capabilities rather than firstgeneration solutions.
Regulators scrutinize industries heavily, and the compliance headaches look remarkably similar. Comprehensive documentation is mandatory either way. Policy application has to be consistent. Pricing needs to be transparent. The compliance management function faces regulatory requirements that keep changing, so it’s constantly adapting while trying not to break what's already working. When examiners show up, they want to see the organization’s control environment and they want audit trails that actually make sense. Successful telecom operators figured out early on that they needed compliance baked into their commercial management systems. They built governance frameworks directly into deal lifecycle platforms. Every decision was documented. They created systematic processes for regulatory reporting because they had no choice. Regulatory compliance became part of everyday operations rather than treating it as an afterthought.
Banks can learn from this instead of reinventing everything. Take what other industries have already proved works; banks can modernize without losing control, scale complexity without increasing risk, and turn data into action rather than friction, skipping the painful trial-and-error phase.
Speed, flexibility, and clients who expect more than they used to aren't new pressures, but they're intensifying. And at some point, data management and deal lifecycle management stop being tools and start being the thing that holds everything else together. Banks that get both right can actually move when a client opportunity shows up, price it properly, and follow through without the deal falling apart in execution. Banks that don't are stuck managing the friction while others take the business.
Conclusion
Modernization in banking is no longer set by executive timelines, it is being dictated by corporate clients. Enterprises are moving ahead with new payment models, data standards, and integration expectations regardless of whether their banks are ready to support them. Nearly 80% of midsize and large corporate clients now partner with fintech providers. Seventy-five percent of corporate clients either use or plan to use ISO 20022 messaging formats, many proceeding regardless of bank readiness. Expectations for real-time payments continue to rise, with roughly 40% of mid-tier to large bank clients anticipating increased usage in the coming year. When close to half of corporate clients cite better functionality and tighter integration with their own systems as reasons for exploring alternatives, the message is clear: technology capability now outweighs many traditional banking differentiators in shaping competitive outcomes.
In this environment, a wait-and-see approach carries unacceptable risk. Corporate clients do not pause innovation while banks deliberate. They implement ISO 20022 messaging through treasury management systems and third-party platforms. They adopt real-time payments through fintech partners that offer speed, transparency and data visibility. They spread business across institutions that demonstrate technological sophistication and execution readiness. Each delay widens the gap between banks investing strategically in foundational capabilities and those falling behind, turning hesitation into lost relevance and eroding long-term client relationships..
In today’s environment, competitive advantage in banking doesn’t come from individual modernization projects. It comes from connecting data, commercial decisions, and operational execution in a way that creates speed, protects control, and translates capability into revenue and stronger client relationships.
Financial Institutions:
• Prioritize data management infrastructure as the foundation for all modernization efforts. Without the capability to extract, transform, and route transactional data across systems, investments in ISO 20022, real-time payments, and digital services will deliver limited value.
• Modernize deal lifecycle management platforms to centralize commercial relationships. Move away from spreadsheets and fragmented systems to gain complete visibility into pricing agreements, approval workflows, and relationship performance
• Integrate data management with deal lifecycle platforms to create closed-loop systems. Connect commercial agreements directly to operational platforms, automate pricing implementation, monitor for discrepancies, and use transaction data to inform relationship management decisions.
• Adopt hybrid cloud strategies that enable gradual modernization without service disruption. Follow other industry sector patterns of selective platform replacement, integration layers that bridge old and new systems, and phased approaches that maintain operational continuity. The Telecom industry represents a good reference.
• Use relationship performance data for proactive, consultative engagement. Track actual usage against projections, identify optimization opportunities, and position deviations as chances for relationship enhancement rather than retrospective problemsolving
Fintech Vendors
• Position data management solutions as strategic infrastructure rather than operational tools. Help banks understand that data orchestration capabilities directly impact regulatory compliance, customer experience, and revenue growth, not just back-office efficiency.
• Emphasize integration capabilities that connect deal lifecycle management to datacentric operational systems. Banks need solutions that eliminate manual pricing updates, validate implementation through confirmation loops, and maintain consistency between agreements and actual charges.
• Highlight mature industry-proven frameworks adapted from other industry sectors. Banks value mature capabilities over first-generation solutions, so highlight successful implementations in similarly complex, regulated environments with legacy infrastructure constraints.
• Build compliance and audit capabilities into core product design. Banks require comprehensive documentation, consistent policy application, and complete audit trails to meet regulatory requirements and demonstrate disciplined commercial management.
The real question for banks is no longer whether to modernize, but how to ensure those investments pay off. Integrating data management and deal lifecycle management allows institutions to move faster, protect margins, and adapt as expectations evolve. Without that connection, transformation becomes expensive, incremental, and increasingly hard to justify.
About CSG
CSG helps banks, insurers, and fintechs manage the complexity of modern revenue models. Its revenue, data, and deal management solutions enable financial institutions to price, charge, and bill accurately across complex products and services.
The platform supports dynamic pricing, bundled offers, automated workflows, and end-toend revenue assurance. This allows institutions to manage the full pricing-to-billing lifecycle in a more integrated and controlled way.
CSG’s cloud-ready, AI-enabled platforms help financial institutions modernize legacy environments, close revenue gaps, and support new growth initiatives without disrupting core operations.
By replacing spreadsheets, siloed systems, and manual processes with integrated platforms, CSG helps institutions accelerate deal cycles, improve margins, reduce operational risk, and create better experiences for both customers and internal teams.
About Datos Insights
Datos Insights is the leading research and advisory partner to the banking, insurance, securities, and payments industries both the financial services firms and the technology providers that serve them.
In an era of rapid change, we empower firms across the financial services ecosystem to make high-stakes decisions with confidence and speed. Our distinctive combination of proprietary data, analytics, and deep practitioner expertise provides actionable insights that enable clients to accelerate critical initiatives, inspire decisive action, and de-risk strategic investments to achieve faster, bolder transformation.
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Author information
Enrico Camerinelli ecamerinelli@datos-insights.com
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