Consumer Banking is undergoing a profound transformation driven by artificial intelligence (AI). Financial institutions must accelerate AI readiness to maintain competitiveness and unlock new growth and efficiency opportunities.
The adoption of AI is poised to be a critical driver for growth and innovation within the banking sector in the immediate and longer term. AI, by market cap within the banking industry, is expected to grow from $26 billion in 2024 to up to $380 billion within the next ten years.1 Additionally, capital expenditures on AI investment by financial services companies are expected to reach almost $100 billion by 2027.2 The substantial investment in AI technologies highlights the industry's belief in AI's potential to deliver significant returns and enhance banking operations.
The ongoing digital transformation and evolving customer expectations further accelerate AI adoption. Consumers are increasingly comfortable with AI-driven services, with 77% already using AI technologies, such as virtual assistants and chatbots, for banking and other financial needs.3 Moreover, 50% of retail banking consumers are dissatisfied with their current banking options,4 highlighting the demand for enhanced customer experience that AI can deliver.
Opportunities
Enhanced Customer Experience and Personalization
AI enables hyper-personalized banking experiences, anticipating customer needs and fostering stronger relationships. For instance, AI could proactively recommend balance transfers based on account activity, offer personalized savings plans aligned with a customer's stated financial goals, or even anticipate cash flow issues with timely short-term credit offers. 46% of financial firms report improved customer satisfaction after AI integration.5 AI-powered chatbots can now handle complex inquiries, providing tailored assistance. Real-time data analysis allows for the personalization of marketing campaigns and can anticipate and predict customer needs. This level of personalized interaction, driven by AI's analytical capabilities, allows banks to move beyond standardized service models and cultivate deeper, more meaningful connections with their customers.
Improved Operational Efficiency and Cost Reduction
AI facilitates the automation of routine yet critical tasks such as automatically verifying a customer's identity against regulatory databases during online account opening, using AI-powered chatbots to answer frequently asked questions about loan applications or account fees, and intelligently extracting data from loan applications, thereby freeing up valuable human resources to focus on more strategic and complex initiatives. On average, the implementation of AI in financial services has demonstrated a reduction in operational costs ranging from 22% to 25%, achieved through process automation and the minimization of human errors.6 For example, Ankura’s proprietary AML tool, powered by AI, significantly decreases the number of transaction monitoring alerts. This AI-driven efficiency has resulted in a substantial 50% to 80% average reduction in the time required to generate suspicious activity reports. This type of enhanced efficiency not only translates to significant cost savings but also allows for a more effective allocation of resources and an overall improvement in the bank's bottom line.
Enhanced Fraud Detection and Risk Management
AI significantly enhances fraud detection and risk management capabilities within consumer banking. Currently, 71% of financial institutions use some level of AI for fraud detection.7 AI systems excel at identifying patterns and anomalies within vast datasets of transaction information in real-time, such as flagging transactions with unusual geospatial discrepancies or detecting deviations in a user's behavioral biometrics, enabling financial institutions to intervene immediately and prevent potential losses. Embracing predictive risk management through AI empowers banks to identify potential threats by predicting high-risk customers based on their data profiles and forecasting potential fraud outbreaks to implement preventative measures, thereby bolstering both the security of the institution and the confidence of its customers.
Risks and Challenges
While the opportunities presented by AI in consumer banking are substantial, financial institutions should be aware of and prepared to address the potential risks and challenges associated with its adoption.
Data Management and Integration
A growing number of financial institutions identify data management as their primary obstacle to AI adoption.8 This stems from banks managing incomplete datasets that have been collected from various disconnected systems, which creates difficulties in accessing, cleaning, and effectively integrating data to be used by AI. Additionally, many banks continue to operate using legacy systems that may lack the necessary scalability, flexibility, and processing power required for the deployment of advanced AI. Overcoming these challenges necessitates investment in modernizing data infrastructure and establishing robust data governance frameworks to ensure the quality and accessibility of information that fuels AI applications.
Data Privacy
As banks increasingly leverage AI to drive personalized customer experiences and improve risk management, they should evaluate the protection of sensitive customer and company data. There are a number of regulations, such as the Gramm-Leach-Bliley Act (GLBA), General Data Protection Regulation (GDPR), and California Consumer Privacy Act (CCPA) that should be considered. To ensure AI readiness and manage emerging risks, banks should implement robust data and AI governance frameworks that balance the benefits of AI-driven innovation with the need to safeguard customer data and maintain regulatory compliance.
Talent and Internal Skill Gap
The successful implementation and management of AI solutions requires a skilled workforce with specialized talent and expertise, which currently presents a significant challenge for the banking industry. This talent gap is not limited to IT professionals. Areas such as risk and compliance, internal audit, operations, and beyond also require individuals who understand the unique implications of AI within their domains. In fact, one-third of financial institutions report that they are facing difficulties in both finding and retaining individuals with the necessary AI skills, highlighting a critical skills gap within the sector.9 This talent gap is exacerbated by the fact that banks are competing for AI talent with tech giants and startups. To bridge this gap, banks should consider investing in employee training and development programs and adopt innovative recruitment strategies to attract top AI talent.
Governance
Beyond the foundational challenges of data and talent, financial institutions must also navigate potential governance and risk considerations as they integrate AI into their operations. The increasing capabilities of agentic AI demand an evolution of today's model risk management and governance frameworks. Relying on traditional methods that emphasize understanding the model's internal mechanics will become challenging with these more autonomous systems. The future of risk management should adapt to AI, where the internal processes are less transparent, moving beyond a focus on just inputs and outputs. Managing risk in this new era requires a fundamental shift in our approach.
Banks typically govern AI through a combination of central oversight and decentralized implementation. Central AI governance bodies establish overarching principles, policies, and risk frameworks that apply across the entire organization. Individual business units then leverage AI solutions tailored to their needs, operating within these centrally defined guardrails. These guardrails encompass robust risk management, regulatory compliance, and strong data governance practices. Furthermore, banks often incorporate transparency measures and human oversight to provide responsible and trustworthy AI deployment. This multi-layered approach allows for both consistent control and business-specific innovation in the rapidly evolving AI landscape.
Conclusion
As the consumer banking sector continues to evolve, accelerating AI readiness is no longer a strategic advantage but an imperative for survival. While the opportunities presented by AI are vast, financial institutions must also address the evolving risks and challenges associated with its adoption. By prioritizing investments in data management and integration, data privacy, talent acquisition and development, and governance, banks can unlock the full potential of AI and drive innovation, efficiency, and growth.
How Ankura Can Help
Ankura brings deep industry knowledge and a proven track record of guiding financial institutions through complex transformations. We understand the unique challenges and opportunities within the consumer banking sector and are positioned to partner with your organization on its AI journey. Our comprehensive approach will empower your financial institution to maximize the benefits and mitigate the risks of AI. We provide strategic guidance, operational support, and technical expertise across the entire AI implementation lifecycle. This includes defining and implementing AI governance models, as well as advising on data privacy and cybersecurity leading practices.
[1] https://www.precedenceresearch.com/artificial-intelligence-in-banking-market
[2] https://thefinancialbrand.com/news/artificial-intelligence-banking/ai-and-the-future-of-financial-services-the-view-from-davos-186139
[3] https://www.allaboutai.com/resources/ai-statistics/finance/
[4] https://www.pymnts.com/artificial-intelligence-2/2024/72percent-of-finance-leaders-use-ai-in-their-operations/
[5] https://www.allaboutai.com/resources/ai-statistics/finance/
[6] https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-market
[7] https://www.pymnts.com/artificial-intelligence-2/2024/72percent-of-finance-leaders-use-ai-in-their-operations/
[8] State of AI In Financial Services Annual Report – 2024 | NVIDIA
[9] State of AI In Financial Services Annual Report – 2024 | NVIDIA
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© Copyright 2025. The views expressed herein are those of the author(s) and not necessarily the views of Ankura Consulting Group, LLC., its management, its subsidiaries, its affiliates, or its other professionals. Ankura is not a law firm and cannot provide legal advice.
