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  "documentTitle": "Banking on AI Banking Top 10 Trends for 2024",
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      "text": "When Commonwealth Bank of Australia replaced its core banking system, it took five years and cost almost US$750 million.",
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      "text": "While innovation flourished in many parts of the organization, the foundation remained fundamentally unchanged. The enhancements that were introduced to banks' core systems had a perverse effect: they invariably increased the coupling, complexity and fragility of these systems and architectures (where little decommissioning took place) and often introduced vulnerabilities that were not present in the original version. Adding to the problem is the millions of lines of COBOL code that handle most banking data and processing—it is not only outdated; it also tends to be poorly documented and difficult to change. It didn't help that, as banks digitized their front ends and client engagement layers, processing volumes (especially at peak times) increased significantly. A final factor contributing to this perfect storm was that the pool of professionals familiar with the legacy core—mainframe experts and COBOL engineers and programmers—has for years been drying up. The time, effort and risk involved in a full-scale digital core modernization was therefore daunting, and left banks in a cycle of bare maintenance that hindered the adoption of new technologies that would enable the business and improve productivity. Proof of this could be seen in the market. When Commonwealth Bank of Australia replaced its core banking system, it took five years and cost almost US$750 million. It's hardly surprising that many a CEO would have opted to put off a project of this scale, preferring to leave it to their successor.",
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      "text": "Today, the capabilities, scalability and increasing maturity of next-gen technologies may offer the key to breaking the traditional cycle. Composable and coreless architectures and approaches that use thinner next-gen core banking platforms enable the integration of best-of-breed solutions and the co-existence of legacy and modern core systems. This hybrid approach dramatically reduces the risk of core modernization while enabling timely business outcomes, and control over the modernization speed and path. In 2024 generative AI will join this impressive arsenal, help unlock the shackles of banks' legacy systems, and allow them to transition more swiftly and securely to a modern, fit-for-purpose digital core.",
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