AI Impact on Customer-Facing Value Chains in Banks
Reshaping old business capabilities into new AI-powered value chains.
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.
Member Testimonials
After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this blueprint and what our clients have to say.
10.0/10
Overall Impact
$34,250
Average $ Saved
20
Average Days Saved
Client
Experience
Impact
$ Saved
Days Saved
Sun Community Federal Credit Union
Guided Implementation
10/10
$34,250
20
It's great to talk to David when we need to focus on strategy. Discussing what technology is helping banks have a competitive advantage in the mar... Read More
AI Impact on Customer-Facing Value Chains in Banks
Reshaping old business capabilities into new AI-powered value chains.
Analyst Perspective
AI is redefining the value chain throughout banking.
 |
The use of artificial intelligence (AI) and machine learning (ML) in large banks has been active for almost two decades. A considerable amount of it was not directly customer facing. Over the last few years, AI/ML have been moving progressively closer to direct interactions with customers and this is having a significant impact on how banking value streams are organized and executed. The broader categories of business and IT capabilities required to deliver modern customer-facing interactions in banking have appeared to not change at a surface level. However, this is not to say that there have not been far-reaching implications on how business and IT capabilities are executed because of the increasing use of AI/ML. The use of AI/ML across customer-facing activities has already had a profound impact and IT departments need to transform the way they deliver their service and capabilities. IT needs to invest its time to understand the overall banking AI/ML strategy and prepare itself to be able to address the rapidly shifting requirements with new people, processes, technologies, and data. David Tomljenovic MBA LL.M CIM |
Executive Summary
Your Challenge |
Common Obstacles |
Info-Tech’s Approach |
|---|---|---|
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. |
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? |
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/ML for Small and Midsize Banks report to achieve exponential outcomes and returns. |
Info-Tech Insight
The investment your bank will make into customer-facing AI/ML capabilities will also have a positive impact on your bank’s internal operations. By using the six-part external and internal framework, you can be sure to have a holistic view of AI/ML within your back office. As your AI/ML maturity grows and you can connect external and internal AI/ML benefits, your bank will be able to achieve exponential returns on its investments.
Gen AI is a revolutionary innovation in deep learning
Generative AI (Gen AI)
A form of ML whereby, in response to prompts, an AI platform can generate new outputs based on the data it has been trained on. Depending on its foundational model, a Gen AI platform provides different modalities and use case applications.
Machine Learning (ML) and Deep Learning
The AI system is instructed to search for patterns in a dataset and then make predictions based on that set. With repeat searches, the system learns to provide more accurate content over time but requires a supervised intervention if the data is inaccurate. Deep learning is self-supervised and does not require intervention.
Artificial Intelligence (AI)
AI is a multidisciplinary research field aiming to make machines intelligent. Applied to specific tasks like computer vision, speech recognition, and language translation, AI has advanced exponentially in the last few years.
Info-Tech Insight
Generative artificial intelligence empowers businesses to automate and enhance content creation personalization, allowing businesses to efficiently develop engaging, tailored content, optimize targeting, and improve overall campaign effectiveness.
Banks adopt AI/ML for multiple purposes
AI is being rapidly deployed throughout customer interactions.
AI is seen as vital to customer experience. |
AI is playing a major role in customer interactions. |
AI-powered transaction are already dominant. |
94% of financial services organizations say that improving CX was a key factor when launching AI initiatives.1 |
50% of bank survey respondents reported that at least 40% of their customer interactions are powered by AI.1 |
80% of customers are having AI-enabled interactions weekly.1 |
Info-Tech Insight
The impact of AI on customer engagement has significantly accelerated in the last year.
1 The Financial Brand, “Banks Benefit from AI”
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