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      "text": "Data quality and provenance remain the most important data usage risk in the eyes of CROs.",
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      "text": "As banks make significant investments in large-scale change initiatives, many of them technology-driven, it's no surprise that CROs are prioritizing the risk implications of transformation and innovation strategies. The increased use of artificial intelligence (AI), which has hugely disruptive potential, could present as much downside risk as it does potential to create value. It has only heightened CRO awareness of risks related to technology modernization and data enhancements. Machine learning (ML), cloud computing, quantum computing, and other technologies, along with their growing interdependencies, will present similar risk and challenges in the future.\n\nCROs are certainly embracing AI and ML within their own teams and operations. Data analysis and automated analysis of documentation are the most common use cases. While CROs no longer see talent as the top constraint for adoption of AI and ML, skill gaps are a factor in their concerns about methodology and programming (e.g., building models, implementing them and managing the associated risk).",
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      "text": "Data quality and provenance remain the most important data usage risk in the eyes of CROs. No doubt business leaders would agree, given that complete, current and accurate data is critical for the smooth functioning of both customer-facing and back-office processes, as well as enabling successful adoption of new technologies.\n\nThe importance of growth and innovation strategies are also reflected in CROs' talent priorities; they are seeking to strengthen their scenario modeling and analytical capabilities and their overall digital acumen. Improving their skills and knowledge in these areas will certainly help them advise and challenge leaders across the enterprise as more of the banking business is digitized.",
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