💡 Insights from Accenture's 'Banking on AI - Banking Top 10 Trends for 2024'

You're busy - I've read the report so you don't have to.

This week I'm highlighting the key insights from the latest Accenture report - 'Banking on AI - Banking Top 10 Trends for 2024'.

What's included?

• A simplified exec summary

• Top five key insights from the report

• Stand out statistics

• Clearly defined next steps

• Cross-reference with other industry commentators

📌 Simplified Exec Summary

This report analyses the profound impact generative AI will have on the banking industry in 2024 and beyond. Accenture's analysis indicates banking may be more impacted by generative AI than any other sector, with up to 30% productivity gains and 6% revenue uplift potential.

Key trends include leveraging AI for personalised pricing, modernising legacy systems via AI-assisted code conversion, transitioning to cloud-based and engineering-centric operating models, and rethinking workforce roles alongside AI co-workers.

Challenges exist around regulatory recalibration, mitigating emerging risks like cyber threats, and driving the required cultural transformation. However, banks that successfully combine AI with cloud, data, re-engineered processes, and upskilled talent will be positioned for sustainable competitive advantages.

The report emphasises a holistic embrace of generative AI as a transformational force that will redefine banking's cost structures, customer experiences, and growth trajectories in the coming Age of AI.

What's the purpose of this report in less than 30 words?

The report aims to provide a comprehensive analysis of the top trends shaping the banking industry in 2024, primarily driven by the adoption of generative AI.

📌 Top Five Key Insights:

1. Generative AI will have a profound impact on the banking industry, with the potential to boost productivity by 22-30% and increase revenue by 6%.

2. Banks will need to adopt a "cloud-first" approach and modernise their legacy systems to fully leverage the benefits of AI and other emerging technologies.

3. Pricing optimisation through AI will become a key competitive advantage, allowing banks to offer personalised pricing and maximise profitability.

4. The role of the IT function will shift from technology management to engineering, with a focus on product innovation and service design.

5. Banks will need to rethink their operating models, workforce, and culture to adapt to the changes brought about by AI and emerging technologies.

📌 Important Statistics

1. Analysis of 19,265 tasks across 900 job families in 19 industries found that banking is likely to be more extensively impacted by generative AI than any other industry, with almost three-quarters of all work being well-suited for automation or augmentation.

2. Banks' cost-to-income ratios have remained in a tight band of 50-60% over the past quarter of a century, despite efforts to improve efficiency (see image below).

3. Goldman Sachs reports that, in some cases, it has been able to write as much as 40% of its code automatically using generative AI.

4. A global bank increased its auto-loans sales by 50% and achieved a double-digit reduction in costs by reinventing the dealer and customer experiences using AI.

📌 Recommendation of Next Steps

Based on the insights and trends outlined in the document, it is recommended that banks take the following steps:

1. Develop a comprehensive generative AI strategy that addresses not only technology implementation but also workforce transformation, cultural change, and operating model redesign.

2. Prioritise cloud migration and modernisation of legacy systems to enable the effective adoption of AI and other emerging technologies.

3. Explore opportunities for pricing optimisation and personalisation through the use of generative AI and data analytics.

4. Foster a culture of innovation and continuous learning, encouraging collaboration between IT and business functions to engineer new products and services.

5. Engage with regulators and industry associations to promote a more effective and agile regulatory framework that keeps pace with technological advancements.

📌 In-Depth Cross-Reference and Analysis

The rise of generative AI presents a transformative opportunity for the banking industry to drive productivity, revenue growth, and innovation. Accenture's analysis aligns with expert predictions from McKinsey & Company, which estimates that AI could potentially free up nearly $1 trillion in annual wages for the global banking industry (McKinsey). However, capturing these gains requires a comprehensive strategy that extends beyond technology implementation.

Banks must prioritise cloud adoption, workforce upskilling, and operating model redesign to foster a culture of innovation and continuous learning. As Satya Nadella, CEO of Microsoft, stated, "The AI revolution is not just about technological prowess, but about enabling people and organisations to achieve more." (Microsoft). Effective regulatory collaboration is also crucial, as highlighted by the World Economic Forum, which calls for a "new generation of smart policies" to govern AI's ethical development and deployment (WEF).

By embracing a holistic approach to generative AI, banks can unlock unprecedented opportunities for efficiency, personalisation, and customer-centric innovation, ultimately redefining the industry's competitive landscape.

Sources: McKinsey & Company: "The economics of artificial intelligence in banking"; Microsoft: "The Age of AI"; World Economic Forum: "Shaping a Multiverse of Responsible AI"

But wait! I'm a CMO, why should I care about this report?

A Chief Marketing Officer should care about Accenture's "Banking on AI" report for several key reasons:

1. Customer Experience and Personalisation: The report highlights how generative AI can help banks improve customer experiences and enable personalised interactions across digital channels. This is crucial for CMOs as it can lead to increased customer engagement, loyalty, and cross-selling opportunities.

2. Revenue Growth Potential: According to the report, banks can potentially increase their revenue by 6% within three years by leveraging AI to enhance wealth advisory, tailor products, and streamline onboarding processes. This directly impacts marketing efforts and the ability to drive revenue growth.

3. Pricing Optimisation: The report emphasises the power of AI in optimising pricing strategies, allowing banks to offer personalised pricing and maximise profitability. This can significantly influence marketing campaigns, promotions, and product positioning.

4. Data-Driven Marketing: The adoption of AI and cloud technologies will enable banks to better leverage customer data and analytics for targeted marketing campaigns, audience segmentation, and real-time decision-making.

5. Branding and Differentiation: As the report suggests, AI can help banks reinforce trust, loyalty, and differentiation by delivering authentic, personalised experiences akin to face-to-face interactions. This aligns with CMOs' goals of building strong brand equity and competitive positioning.

By understanding the transformative potential of AI in banking, CMOs can align their marketing strategies, resource allocation, and organisational structures to capitalise on these emerging trends and drive customer-centric innovation.

🔗 Read the Report

As always I recommend reading this report as they dive into more detail around market opportunities and how businesses can benefit by being early adopters of this tech.

Read the report here

And thanks to the author - Michael Abbott and his Research Team: Dariusz Orynek, CFA, Francesca Caminiti, Alejandro Borgo, Mauro Centonze, Pilar Monteagudo, Jan Steinmetz, Corrine Vitolo, Rocío Pérez-Aubá del Campo

📌 Want more insights?

Previously on the Smart CMO: Check out my last summary of Deloitte's report 'Tokenization: Realizing the vision of a future financial ecosystem'.

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