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AI Impact on Customer-Facing Value Chains in Banks

Reshaping old business capabilities into new AI-powered value chains.

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AI/ML is being rapidly implemented in customer-facing value streams. Your IT team is trying to understand its role in AI/ML.

Business and IT capabilities are being delivered very differently. AI/ML have very different requirements than traditional business capabilities that are then impacting IT capabilities.

The entire bank is transforming, and IT capabilities need to keep pace. The entire bank is adopting AI/ML, and IT doesn’t have a comprehensive view or understanding of the AI/ML plan, which makes planning and modernization unnecessarily complex.

Our Advice

Critical Insight

Old capabilities must be transformed. Existing IT processes and capabilities appear increasingly unsuitable for delivering and supporting AI/ML.

You likely need new skills and capabilities. As AI/ML requirements reshape IT capabilities, you realize that you will need new skills and substantial training.

The need for data has never been greater. Do you choose an AI/ML provider first? What about data? How does the new AI/ML fit into your existing infrastructure?

Impact and Result

Use the retail banking reference architecture to reveal the areas that require change, to help you determine where you should deploy it within your bank.

Begin to explore AI vendors and uses cases, to maximize the return on your AI/ML investment.

Use the AI for Small and Midsized Retail Banks report to achieve exponential outcomes and returns.


AI Impact on Customer-Facing Value Chains in Banks Research & Tools

1. AI Impact on Customer-Facing Value Chains in Banks Deck – Assess your current state and formulate a new long-term strategy.

Use this report to better understand AI’s impact on customer engagement. Also, see an example of an AI-powered product or service using the retail banking reference architecture.

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Reshaping old business capabilities into new AI-powered value chains.

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Author

David Tomljenovic

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