I. Executive Summary
The global banking sector stands at a pivotal juncture, grappling with the imperative to modernize its foundational IT infrastructure. For decades, IBM z/OS mainframes and COBOL-based applications have served as the unwavering bedrock of core banking operations, renowned for their unparalleled reliability, security, and capacity to process immense transaction volumes. However, the relentless pace of digital transformation, fueled by evolving customer expectations for real-time services, hyper-personalization, and seamless digital experiences, increasingly exposes the inherent limitations of these legacy systems in terms of agility and cost-effectiveness. Modernization is no longer a discretionary IT upgrade but a strategic imperative to sustain competitiveness and ensure regulatory adherence.
Analysis of current trends (2020-2025) reveals a pronounced shift towards modern architectures, including cloud-native platforms, distributed systems, and hybrid cloud solutions. Banks are predominantly adopting incremental migration strategies, often employing dual-run validation techniques, to mitigate the substantial risks associated with large-scale transformations. While the Total Cost of Ownership (TCO) of mainframes remains a complex calculation, often underappreciated in its value generation, cloud migration introduces its own intricate and frequently underestimated hidden costs. The modernization journey is fraught with risks such as operational disruption, data integrity challenges, and critical skill gaps. Nevertheless, the compelling benefits of enhanced agility, scalability, accelerated innovation, and improved customer experience continue to drive this fundamental industry shift.
For Bank Mizrahi-Tefahot, a successful modernization trajectory necessitates a phased, meticulously risk-managed approach that is intrinsically aligned with the bank's strategic objectives. Key recommendations include a thorough assessment of the existing mainframe estate, strategic investment in talent development and upskilling, judicious leveraging of AI-powered tools for code and data transformation, and unwavering adherence to the Bank of Israel's evolving regulatory landscape, particularly concerning cloud adoption, data residency, and cybersecurity. This report aims to equip technical decision-makers, architects, and COBOL developers with the comprehensive understanding required to navigate these complex discussions and chart a future-proof course for the bank's core systems.
II. The Enduring Legacy: Mainframes and COBOL in Core Banking
Historical Context: Why COBOL and Mainframes Dominated Banking
The enduring presence of COBOL and mainframes in the financial sector is deeply rooted in their historical development and inherent design principles. COBOL, or Common Business-Oriented Language, emerged in the late 1950s with a deliberate focus on commercial, financial, and administrative applications. Its design prioritized readability and the clear expression of business logic, making it highly accessible to business-oriented programmers and suitable for complex financial calculations. Indeed, COBOL was the first programming language specifically tailored for financial transactions and interbank transfers. Over the decades, COBOL underwent significant evolution, with versions like COBOL-61 Extended, COBOL-65, and COBOL-70 introducing critical functionalities such as sorting, report writing, enhanced arithmetic, debugging capabilities, and inter-program communication. These enhancements solidified its position as a robust language for intricate business applications.
Concurrently, mainframes began their integration into banking in the 1960s and 1970s, rapidly becoming the central nervous system for data processing and transaction management. Their architecture was engineered for high-volume, high-speed transaction processing, providing the foundational infrastructure for critical banking functions like customer account management, loan processing, and financial reporting. Mainframes excelled at handling millions of transactions daily with minimal downtime, offering unparalleled reliability and robust security frameworks essential for protecting sensitive financial data.
The deep entrenchment of COBOL and mainframes is not merely a consequence of inertia; it stems from their foundational design principles that prioritized stability, security, and transaction integrity at a time when alternative technologies simply could not match these capabilities. These systems have consistently met the non-negotiable demands of banking for decades, establishing a proven track record of dependability. This historical context underscores the inherent resistance to change, as any replacement must demonstrate equivalent or superior capabilities in delivering certainty and reliability. The industry's cautious approach is a direct reflection of the success and critical nature of these long-standing systems.
Current State: Mainframe Dominance and Persistence
Despite the emergence of more modern and flexible programming languages and computing paradigms, mainframes and COBOL continue to play a critical role in global finance. As of 2024, a significant 43% of international banking systems still rely on COBOL code, and an estimated 95% of all ATM transactions are powered by it. The sheer volume of COBOL code in active use is staggering, with estimates suggesting approximately 800 billion lines globally. Major financial institutions, including JPMorgan Chase, American Express, Bank of America, and Visa, continue to depend heavily on COBOL for their daily operations.
Mainframes remain the backbone for core banking operations, demonstrating exceptional capabilities in high transaction processing, security, and continuous availability. IBM Z mainframes, for instance, are reported to process around 30 billion transactions daily and handle 87% of all credit card transactions, showcasing their critical role. Their reputation for hardened security is a significant draw, with the ability to process up to 12 billion encrypted transactions a day. Furthermore, these systems are noted for maintaining decade-long business continuity, with high availability features like IBM Parallel Sysplex ensuring continuous operation even during maintenance.
III. Migration Strategies and Approaches
Banks generally choose between phased (incremental) modernization and big-bang (full replacement) strategies – or a combination. A hybrid "strangler" pattern is common: keep the existing COBOL core running while slowly migrating functionality to new services. The trade-offs are well-documented. Incremental upgrades (greenfield pilots, microservices APIs, facade layers) are lower-risk and allow continuous operation, but they extend dual environments and require careful integration. Full replacement promises a clean break to new architecture, but involves massive data migration and organizational change, as seen in high-profile failures.
One analysis breaks modernization into the "5 R's" of migration:
- Rehost/Re-platform (Lift & Shift): Move COBOL workloads to a non-mainframe environment (e.g. AWS with Micro Focus runtime) with minimal code change. This is quick and minimally invasive, often yielding immediate cost savings.
- Refactor/Rewrite: Convert COBOL applications to a modern language (Java, C#, etc.) or microservices architecture. This is complex but enhances agility and maintainability long-term.
- Replace/Repurchase: Adopt a packaged modern core banking system (e.g. Temenos, Finastra, Thought Machine Vault) and migrate data into it. This can fast-track new features but risks vendor lock-in and lengthy implementation.
- Retire: Decommission obsolete modules and consolidate functionality (often feasible only for minor apps or batch jobs).
- Retain: Keep certain legacy components (perhaps in mainframe) if no viable alternative exists – effectively delaying migration on those parts.
IV. Technical Comparison: Legacy vs. Modern Architectures
Classic core banking runs on monolithic mainframes: COBOL/CICS batch and on-line transactions, IMS/DB2 or VSAM data stores, and tightly-coupled codebases that process overnight batch cycles. These systems often rely on batch processing, updating transactions in overnight cycles rather than in real time, making true 24/7 digital services challenging. By contrast, modern architectures use cloud-native microservices: stateless services in containers, decoupled data stores (SQL/NoSQL), and continuous integration pipelines. New designs favor asynchronous messaging, real-time streaming (Kafka/Confluent), and RESTful APIs.
Key technical differences include:
- Processing: Mainframes are optimized for high-throughput batch and transactional I/O; new systems aim for low-latency, on-demand processing. Legacy cores are typically not built for the open, connected financial ecosystem of mobile and open banking.
- Language/Runtime: COBOL/PL/I on z/OS vs. Java/.NET/Python on Linux containers or serverless. Migrating often involves converting business logic or wrapping it in new languages.
- Integration: Legacy tightly integrates using CICS, MQSeries, or proprietary interfaces. Modern systems use APIs and message buses (Kafka, RabbitMQ) for interoperability across cloud services.
- Deployment: Monolithic mainframe deployments with scheduled downtime, vs. continuous deployment in cloud with blue/green deployments and auto-scaling.
V. Cost Analysis and ROI Considerations
Maintaining a legacy mainframe entails high fixed and variable costs: specialized hardware leases, software licensing, and very high-caliber COBOL/CICS talent (often commanding high salaries). By contrast, modern platforms typically use commodity servers or public cloud (lower hardware costs) and pay-as-you-go licensing, with a larger pool of Java/.NET developers. Surveys corroborate big savings: organizations modernizing their mainframes report average cost reductions, and studies estimate significant cuts in operating expenses.
However, modernization requires significant upfront investment: development resources, new licenses or cloud credits, and potentially redundancy during parallel running. Total Cost of Ownership (TCO) analyses must account for migration effort (often 1–3+ years) versus ongoing savings. Banking leaders advise viewing modernization as a business transformation, not just an IT upgrade, ensuring benefits (agility, new revenue) offset migration costs.
Table: Quantifiable Benefits of Core Banking Modernization
| Benefit Category | Specific Metric/Benefit | Source/Context |
|---|---|---|
| Operational Efficiency | 40% average reduction in operational costs | Industry average |
| 40-80% straight-through processing automation | Industry average | |
| 37% higher operational efficiency ratios | McKinsey's Banking Efficiency Index | |
| 20% improvement in employee productivity (DBS Bank) | DBS Bank case study | |
| 20% savings on regular computerization and development costs (Bank Leumi) | Bank Leumi case study | |
| Cost Reduction | 30-40% reduction in IT maintenance costs | Industry average |
| 25-35% decrease in infrastructure expenses | Industry average | |
| 15-20% reduction in overall operational costs | Industry average | |
| $1.5 billion saved in fraud prevention, trading, operational efficiencies (JPMorgan Chase) | JPMorgan Chase AI initiatives | |
| Agility & Innovation | 60% acceleration in new product launches | Industry average |
| 10x faster product cycles | Temenos Transact | |
| 90% reduction in account opening time (DBS Bank) | DBS Bank case study | |
| Customer Experience | Improved customer satisfaction (general) | Industry trend |
| 35% increase in customer satisfaction scores (DBS Bank) | DBS Bank case study | |
| Risk Mitigation | Up to 30% reduction in operational risk | Modernized core platforms |
| 47% reduction in fraud-related losses | Deloitte study | |
| 98% accuracy in AI-driven fraud detection (JPMorgan Chase) | JPMorgan Chase AI initiatives | |
| Performance | Income verification from days to seconds (Lloyds Banking Group) | Lloyds Banking Group case study |
| Unplanned ML platform downtime cut to zero (Lloyds Banking Group) | Lloyds Banking Group case study |
VI. Key Risks, Benefits, and Tradeoffs of Modernization
Core banking modernization is a transformative journey that presents a complex interplay of risks, benefits, and inherent tradeoffs. Understanding these dynamics is crucial for informed decision-making.
Risks
The path to modernization is fraught with potential pitfalls that can derail projects and incur significant costs.
Operational Disruption: Core system changes inherently carry substantial operational risk. Even brief periods of downtime can severely disrupt customer access, erode trust, and trigger intense regulatory scrutiny. "Big bang" approaches, which attempt a full system replacement at once, significantly amplify this risk, often leading to prolonged implementation timelines, budget overruns, and unexpected technical issues. The TSB Bank meltdown serves as a stark reminder of the catastrophic consequences of such disruptions.
Data Integrity and Consistency: Migrating vast volumes of sensitive financial data from complex, often undocumented mainframe formats presents a formidable challenge. Ensuring absolute data integrity and consistency across distributed services is paramount. The shift from strongly consistent ACID models to eventually consistent BASE models in microservices introduces new complexities, requiring careful application-level handling of temporary inconsistencies and sophisticated reconciliation processes.
Cybersecurity: While modern cloud providers offer advanced security controls, migrating sensitive financial data to new environments necessitates a fundamentally different security posture. Inadequate security measures in the cloud can lead to compliance violations and devastating data breaches. An emerging threat is the potential for quantum decryption, which could compromise classically encrypted communications, necessitating advanced protection like fully homomorphic encryption offered by some mainframes.
Table: Key Risks and Mitigation Strategies in Core Banking Modernization
| Risk Category | Description of Risk | Impact on Banking Operations | Mitigation Strategy |
|---|---|---|---|
| Operational Disruption | Unplanned downtime or service interruptions during migration or due to new system instability. | Loss of customer access, reputational damage, financial losses, regulatory scrutiny. | Incremental/phased migration approach. Rigorous testing (functional, performance, security, regulatory). Robust fallback/rollback plans. Dual-run/parallel proving. |
| Data Integrity & Consistency | Data corruption, loss, or inconsistencies during migration or in distributed systems. | Inaccurate financial records, regulatory non-compliance, customer distrust, fraud. | Meticulous data cleansing and validation. Phased data migration. Dual-run/parallel proving with field-by-field comparison. Implementing Saga patterns for distributed transactions. |
| Cybersecurity | Increased attack surface in hybrid/cloud environments, data breaches, compliance violations. | Financial losses, reputational damage, regulatory fines, legal liabilities. | Built-in security and compliance in architecture. Advanced security controls (encryption, IAM, threat detection). Regular security audits and risk assessments. Adherence to BoI cybersecurity directives. |
| Skill Gap | Lack of mainframe experts to maintain legacy systems, or cloud experts to manage new systems. | Slowed migration, increased costs for external consultants, operational inefficiencies, technical debt accumulation. | Upskilling existing staff through training programs. Cross-training mainframe and cloud teams. Leveraging AI-powered tools to automate code transformation and documentation. |
| Cost Overruns | Unforeseen expenses, underestimation of complexity, hidden cloud costs. | Budget depletion, project delays, negative ROI, missed strategic opportunities. | Thorough pre-migration assessment and planning. Detailed TCO analysis considering hidden costs. Continuous cost monitoring and optimization post-migration. Phased budgeting. |
| Undocumented Code | Critical business logic embedded in undocumented COBOL/JCL, making understanding and transformation difficult. | Increased refactoring time, higher risk of errors, project delays, difficulty in knowledge transfer. | Automated documentation generation tools. AI-powered code analysis and explanation. Investing in subject matter experts (SMEs) for knowledge extraction. |
| Vendor Lock-in | Over-reliance on a single cloud provider or proprietary tools. | Limited flexibility, potential for increased costs, difficulty in switching providers. | Multi-cloud strategy. Adopting open standards and open-source technologies. Careful vendor selection and contracting. |
Benefits
Despite the risks, the benefits of modernization are compelling and strategically vital for banks.
Agility and Faster Innovation: Modern architectures enable banks to launch new products, implement updates, and adapt to compliance changes significantly faster. This capability supports an unprecedented pace of innovation, crucial for staying competitive.
Scalability and Resilience: Cloud-native and distributed systems allow for independent scaling of services, ensuring seamless performance even during peak transaction periods. They are designed to contain failures within isolated services, minimizing system-wide impact and enhancing overall resilience.
Enhanced Customer Experience: Modern systems support real-time access to information, personalized financial products, and seamless digital experiences across various channels, meeting and exceeding evolving customer expectations.
Tradeoffs
The decision to modernize core banking systems inherently involves navigating a complex set of tradeoffs, where there are no universally "right" answers, but rather optimal balances based on a bank's unique context and risk appetite.
Short-term Disruption vs. Long-term Gain: Banks must weigh the initial complexity, significant costs, and potential operational disruption of modernization against the promise of long-term operational efficiency, accelerated innovation, and competitive advantage.
Control vs. Flexibility: Retaining full, granular control over on-premises mainframes offers a sense of security and direct oversight. However, this comes at the cost of the flexibility, scalability, and agility offered by public cloud environments, which operate under shared responsibility models.
Strong Consistency (ACID) vs. Eventual Consistency (BASE): This is a fundamental architectural tradeoff in distributed systems. Maintaining strong ACID consistency across distributed microservices can introduce performance bottlenecks and complexity, while embracing eventual consistency (BASE) requires careful application design to handle temporary data discrepancies, which is a significant paradigm shift for traditional banking systems.
VII. Major Vendors, Toolchains, and Frameworks
The core banking modernization landscape is supported by a diverse ecosystem of major vendors offering specialized tools, platforms, and frameworks. A critical evaluation of their offerings provides insight into different strategic approaches.
AWS Mainframe Modernization
AWS Mainframe Modernization is a comprehensive service designed to facilitate the migration, modernization, running, testing, and operation of mainframe applications in a cloud-native, fully-managed runtime environment on AWS.
- Assess: The service offers application intelligence, knowledge, and analysis capabilities to help migration teams understand large application portfolios. This includes highlighting application dependencies and complexities, which is crucial for scoping and planning modernization projects.
- Refactor (AWS Blu Age): This solution automates the transformation of legacy programming languages, including COBOL, PL/1, NATURAL, and RPG/400, into agile Java services and modern web frameworks. It aims to preserve the original business functions while accelerating the transition to newer languages and data stores.
- Replatform (Rocket Software & NTT DATA): AWS offers replatforming capabilities through partnerships with Rocket Software and NTT DATA. These solutions enable the porting of COBOL and PL/I applications onto a mainframe-compatible managed runtime in the AWS Cloud with minimal source code changes.
- AWS Transform for mainframe: This offering leverages agentic AI, trained on AWS's extensive migration experience, to accelerate mainframe modernization from years to months. It streamlines core phases, from initial analysis and planning to code refactoring and migration.
Google Cloud Mainframe Modernization
Google Cloud offers a suite of solutions aimed at comprehensive mainframe modernization, covering assessment, reverse engineering, rewriting, replatforming, augmentation, and de-risking of mainframe applications.
- Mainframe Assessment Tool (MAT): Enhanced with Google's Gemini models and mainframe-specific agentic workflows, MAT helps thoroughly assess and analyze the entire mainframe estate. It generates a comprehensive knowledge base, including detailed code explanations, application logic, dependency insights, automated documentation, and generated test cases, empowering informed modernization strategy decisions.
- Mainframe Rewrite: This solution leverages Gemini models with mainframe-specific context to transform legacy mainframe code into modern languages like Java or C#. It provides an Integrated Development Environment (IDE) for developers to iteratively modernize, test, and deploy applications in Google Cloud.
- Dual Run: A critical de-risking mechanism, Google Cloud Dual Run captures and replays live production events originating on the mainframe onto the modernized cloud application. It then meticulously compares the outputs from both systems to ensure the correctness, completeness, and performance of the updated business logic throughout the modernization journey and prior to go-live.
IBM z/Hybrid Approaches
IBM's strategy for mainframe modernization is centered on evolving the z/OS mainframe into a central, highly integrated component of a hybrid cloud architecture, rather than advocating for its replacement.
- IBM z16 and zIIP Processors: The latest IBM z16 mainframes offer advanced security features, including fully homomorphic encryption, which protects data even when it is in use. A key element of IBM's cost-effectiveness strategy is the IBM z Integrated Information Processor (zIIP). This dedicated specialty processor is designed to operate asynchronously with general processors, offloading new workloads written in languages like Java or Python, managing containers, facilitating system recovery, and assisting with analytics.
- watsonx Code Assistant for Z: This AI-powered tool is designed to accelerate mainframe application modernization at lower cost and risk than traditional alternatives. It can assist developers by generating code and content, streamlining the modernization process.
- Hybrid Cloud for IBM Z: IBM positions its mainframe hybrid cloud architecture as a strategic imperative for banks, balancing the mainframe's proven resilience and security with the agility and innovation of cloud computing.
Table: Major Vendor Offerings for Mainframe Modernization
| Vendor Name | Key Offerings/Solutions | Primary Migration Strategy Supported | Technical Highlights | Critical Evaluation/Value Proposition |
|---|---|---|---|---|
| AWS | Mainframe Modernization Service (Assess, Refactor with Blu Age, Replatform with Rocket/NTT DATA, Application Testing, Data Replication, AWS Transform) | Rehost, Replatform, Refactor, Data Augmentation | Agentic AI (AWS Transform), Automated COBOL/PL/1 to Java conversion, Managed Runtimes, Cloud-native testing, Near real-time data replication. | Comprehensive suite aiming to automate and accelerate code transformation, reducing manual effort. Success depends on legacy code quality and AI validation. |
| Micro Focus | COBOL Conversion Tool (via Royal Cyber), Host Access Analyzer 2.0 | Replatform (within mainframe ecosystem), Analysis/Assessment | Converts Micro Focus COBOL to IBM COBOL, identifies dependencies, real-time usage data for risk/compliance. | Focuses on optimizing and modernizing within or from the mainframe environment, appealing to risk-averse banks. Supports incremental improvements. |
| IBM | IBM z/Hybrid Cloud, IBM z16, zIIP Processors, watsonx Code Assistant for Z | Hybrid Cloud Integration, Selective Modernization, Augmentation | Pervasive encryption (z16), Specialty processors (zIIP) for cost optimization, AI-powered code modernization, Linux on Z, containerization. | Positions mainframe as the secure, resilient core of a hybrid cloud. Challenges "off-mainframe at all costs" narrative by demonstrating continued innovation and value. |
| Google Cloud | Mainframe Modernization (Assessment Tool (MAT), Mainframe Rewrite, Dual Run, Mainframe Refactor, Mainframe Connector) | Rewrite, Refactor, Data Augmentation, De-risking | Gen AI (Gemini models) for code analysis & transformation, automated code conversion to Java/C#, parallel run testing (Dual Run), direct mainframe data integration. | Strong emphasis on AI-driven automation for code transformation and detailed assessment. Dual Run provides critical de-risking for functional equivalence. |
| Microsoft Azure | Mainframe Azure Migration Roadmap, Azure Migrate, Royal Cyber Modernization Suite | Rehost, Replatform, Refactor, Rewrite, Integration | Comprehensive roadmap, automated COBOL conversion, integration with Azure cloud-native services (AKS, API Management, DevOps), robust security features. | Offers a holistic ecosystem for the entire modernization lifecycle, emphasizing integration with a broad range of cloud-native services and a structured approach. |
VIII. Regulatory, Compliance, and Cybersecurity Concerns in Israeli Banking
The Israeli banking industry operates within a dynamic and stringent regulatory environment, with the Bank of Israel (BoI) playing a pivotal role in shaping directives related to IT, cloud computing, data protection, and cybersecurity. These regulations significantly influence the feasibility and methodology of core banking system modernization.
Bank of Israel Directives and Guidelines
Cloud Computing Regulations: The Bank of Israel's stance on cloud adoption for core banking systems has evolved. Initially, the BoI issued directives that prohibited banking corporations from using cloud services for their "core activities and core systems". This cautious approach reflected concerns about material operational risks related to information security, business continuity, and command and control of IT assets. However, subsequent directives, such as Directive 362, eliminated this outright injunction, allowing "material systems" to transition to cloud computing, provided strict risk management and governance frameworks are in place.
Data Residency and Localization Requirements: While earlier directives were strict about data storage "in Israel", the BoI has adapted its stance. Current regulations permit sensitive data (e.g., customer data, confidential business information) to be stored, transferred, or processed on a cloud outside the borders of the State of Israel, provided the cloud service provider maintains a level of protection that complies with the European Union General Data Protection Regulation (GDPR).
Cybersecurity Framework and Risk Management: The Bank of Israel places paramount supervisory priority on upgrading banks' risk management capabilities. Directive 364 consolidates previous directives on IT management, cybersecurity, and data protection, establishing a unified, technology-neutral framework for managing cybersecurity and data protection risks.
Specific Requirements for Bank Mizrahi-Tefahot
For Bank Mizrahi-Tefahot, the Bank of Israel's directives and the broader Israeli fintech landscape directly shape the strategic considerations for core banking modernization. Bank Mizrahi-Tefahot's strategic plan for 2025-2027 emphasizes providing "personal, human banking services, supported by advanced digital technology," aiming for a multi-channel approach that optimally combines human bankers with digital channels. The plan also highlights "continuing the automation of operational processes" and "adjusting periodically the operational model to the challenges of the future".
The Bank of Israel's directives on cloud computing, data residency, and cybersecurity directly impact how Mizrahi-Tefahot can pursue its digital transformation goals. The elimination of the injunction against using cloud for "material systems" is a critical enabler, allowing the bank to consider cloud solutions for components previously restricted. However, this permission comes with stringent requirements including risk assessment and governance, data protection and residency, third-party accountability, cybersecurity controls, and open banking readiness.
IX. Conclusion and Recommendations for Bank Mizrahi-Tefahot
The migration of core banking systems from IBM z/OS mainframes and COBOL-based applications to modern architectures is not merely a technical upgrade but a fundamental strategic imperative for banks globally, including Bank Mizrahi-Tefahot. The enduring legacy of COBOL and mainframes is rooted in their historical reliability and security, which have served the banking sector for decades. However, the escalating costs of maintaining aging, undocumented systems, coupled with a looming skills gap and the imperative for digital agility, necessitate this complex transformation.
The industry is moving towards cloud-native, distributed, and hybrid solutions, driven by the promise of faster innovation, enhanced scalability, and improved customer experiences. This shift involves a profound re-evaluation of architectural paradigms, from monolithic applications with ACID consistency to microservices with distributed data stores and eventual consistency. This transition demands new technical skills and a different approach to transaction management and data integrity.
For Bank Mizrahi-Tefahot, the modernization journey must be meticulously planned and executed within the specific context of Israeli banking regulations. The Bank of Israel's evolving directives, which now permit the use of cloud for "material systems" under strict governance, data residency, and cybersecurity controls, are paramount. Open banking mandates further necessitate API-driven architectures and secure data sharing.
Recommendations for Bank Mizrahi-Tefahot:
- Conduct a Comprehensive, Granular Assessment: Initiate a detailed assessment of the entire mainframe estate, including all COBOL applications, JCL, and data structures (VSAM, DB2). Leverage AI-powered assessment tools (e.g., Google Cloud Mainframe Assessment Tool, AWS Mainframe Modernization Assess) to rapidly analyze code, identify dependencies, and generate documentation for undocumented logic. This foundational understanding is critical for accurate planning and de-risking.
- Adopt a Phased, Incremental Modernization Strategy: Prioritize a progressive modernization approach over a "big bang" replacement. Begin with less critical, well-defined workloads to build internal expertise and demonstrate early successes. Gradually expand to more complex core components, always prioritizing business continuity and minimizing operational disruption. This aligns with the industry's most successful transformations.
- Invest Heavily in Talent Transformation: Address the looming COBOL skills gap proactively. Implement comprehensive training and upskilling programs for existing COBOL developers in modern languages (e.g., Java, Python), cloud-native architectures (microservices, containers), DevOps practices, and distributed data consistency models (BASE). Foster cross-functional teams where legacy and modern developers collaborate to facilitate knowledge transfer and ensure a smooth transition.
- Leverage AI and Automation Judiciously: Explore and pilot AI-powered code transformation tools (e.g., AWS Blu Age, Google Cloud Mainframe Rewrite, IBM watsonx Code Assistant for Z) to accelerate COBOL code conversion and refactoring. Understand that these tools are "code helpers" requiring human validation and oversight. Automate testing (e.g., AWS Mainframe Modernization Application Testing, Google Cloud Dual Run) and data migration processes to ensure functional equivalence and data integrity.
- Prioritize Data Modernization and Consistency: Develop a robust data migration strategy that accounts for the complexities of mainframe data formats (VSAM, DB2) and the shift to cloud-native databases. Implement rigorous dual-run and parallel proving techniques for critical data sets to ensure absolute functional equivalence and build trust in the new systems. Design applications with a clear understanding of ACID vs. eventual consistency tradeoffs, implementing application-level compensation mechanisms where necessary for financial transactions.
- Ensure Unwavering Regulatory Compliance and Cybersecurity: Integrate compliance with Bank of Israel directives (e.g., Directive 362, 364), Israeli Privacy Protection Law, and international standards (GDPR) into every phase of modernization. Prioritize robust cybersecurity controls, including encryption (at rest and in transit), strong authentication, and continuous monitoring, especially when engaging cloud service providers. Leverage the AWS Israel (Tel Aviv) Region for sensitive data requiring local residency.
- Develop a Holistic TCO Model and Continuously Optimize: Move beyond simplistic cost comparisons. Develop a comprehensive TCO model that accounts for mainframe value generation (e.g., zIIP savings, reliability benefits) and the full spectrum of hidden cloud migration costs (e.g., egress fees, refactoring, over-provisioning). Implement continuous cost optimization strategies post-migration to avoid "cloud shock" and maximize ROI.
- Embrace Hybrid Cloud as a Strategic Imperative: Recognize that the mainframe can evolve into a critical, integrated component of a hybrid cloud architecture, rather than being fully replaced. This allows Bank Mizrahi-Tefahot to leverage the mainframe's unparalleled security and reliability for core, high-volume transactions while offloading innovative and variable workloads to the cloud for agility and scale. This approach aligns with IBM's strategic vision and offers a pragmatic path forward.
By adopting these recommendations, Bank Mizrahi-Tefahot can navigate the complexities of core banking modernization effectively, transforming its legacy infrastructure into a flexible, agile, and secure digital platform that supports its strategic goals and positions it for sustained growth in the evolving financial landscape.