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Balancing the Risks and Rewards of AI in Finance<\/p>\n
Survey data<\/a> shows that business leaders are positive about the potential of AI<\/a>. In related research<\/a> conducted by CDW<\/a>, more than half of respondents said their company is leveraging AI to improve cybersecurity (55%), speed up innovation (52%) and improve the customer experience (51%).<\/p>\n Financial institutions are seeing those benefits<\/a> in specific ways:<\/p>\n But Sridharabalan also identifies three risks that can impact AI adoption: regulation, reputation and operation.<\/p>\n Regulation risks focus on compliance<\/a>. For example, are AI operations aligned with industry, government and international expectations? In financial services, that means meeting stringent requirements for data residency, auditability, model explainability, consumer protection and third-party risk \u2014 often across multiple jurisdictions.<\/p>\n Reputational concerns<\/a> are centered on data misuse. Even if this misuse is unintended and entirely accidental, it can negatively impact client and consumer perception. A single biased lending model or opaque underwriting decision can erode trust that took decades to build.<\/p>\n Operational risks are tied to the efficacy of AI deployments. If financial institutions have committed significant resources to AI but are stuck in preproduction, they stand to lose both time and money, and they run the risk of falling behind more agile competitors.<\/p>\n \u201cIf you put all of that together, compliance is the leading concern,\u201d she says. \u201cBusinesses need to think about compliance and governance more proactively. As a result, we\u2019re seeing a shift in the market.\u201d<\/p>\n EXPLORE:<\/strong> Demystify artificial intelligence adoption in your organization.<\/a><\/p>\n IBM\u2019s watsonx AI Platform for Banks, Insurers and Investment Firms<\/p>\n IBM is no stranger to AI. \u201cWe\u2019ve been in the field of cognitive solutions and AI for quite a few years,\u201d says Sridharabalan. \u201cWe saw momentum with ChatGPT. Our watsonx AI and data platform enables customers and partners to develop, improve, and govern generative AI and machine learning models<\/a>.\u201d<\/p>\n For financial services IT leaders, that means you can pursue generative AI and ML initiatives without compromising the controls that regulators and your own risk teams require.<\/p>\n The watsonx platform follows suit with a sophisticated approach to AI that includes three core components:<\/p>\n Sridharabalan notes that it\u2019s a priority for IBM to meet customers where they are.<\/p>\n\n
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