Artificial intelligence for banking: challenges and risks

The challenges of AI for banking

1. Automation of banking processes

AI automates repetitive tasks: verifying transactions, processing loan applications, managing accounts. 44% of chief risk officers in the banking sector are already using AI for process automation. BNP Paribas has reduced the processing time of credit applications by 80% thanks to AI, and had 780 use cases in production by mid-2024, with the objective of reaching 1,000 in 2025.

2. Personalization of customer services

Through data analytics, AI offers personalized recommendations and tailored services. Chatbots and virtual advisors provide 24/7 support. Only 16% of banking institutions use AI for this personalization, while more than half of customers could leave their bank for more personalized services elsewhere.

3. Real-time fraud detection

AI algorithms analyze transactions in real-time to identify suspicious activity and prevent fraud. In banking and insurance, analytical AI detects and prevents money laundering (AML) schemes. LLMs automatically analyze thousands of pages of regulatory documents.

4. Predictive risk analysis

AI uses predictive models to anticipate customer behavior, assess credit risk, and optimize investment portfolios. Crédit Agricole uses AI for predictive credit risk analysis, reducing default rates by 23% in some segments. Read our article on risk management to learn more.

5. Optimizing compliance

AI makes it easier to manage regulations by automating monitoring and reporting, reducing the risk of non-compliance and costly penalties. The interim general counsel plays a key role in this compliance.

6. Impact on banking employment

Automation transforms jobs more than it eliminates them. AI serves as a knowledge base for onboarding and skills transfer, allowing the advisor to focus on the customer relationship. With a bank advisor turnover rate of 10.2% in France, AI helps to compensate for departures and accelerate the integration of new arrivals.

The European AI Act: what banks need to know

The AI Act is the European regulation on artificial intelligence, which is gradually coming into force. It classifies AI systems by risk level:

• Unacceptable risk : prohibited systems (social scoring, behavioural manipulation)
• High risk : systems subject to strict obligations – such as credit scoring, fraud detection and automated decisions in banks
• Limited risk : transparency obligations (chatbots must identify themselves as AI)
• Minimal risk : no specific obligation

French banks must adapt their systems to ensure transparency, explainability, and human oversight of their algorithms. This framework is in addition to the GDPR and the Digital Operational Resilience Act (DORA).

The risks of AI for banking

• Data privacy and security : The massive collection of sensitive data exposes it to cyberattacks and leaks. Large-scale GDPR compliance is a legal and technological challenge for the IT department
• Algorithmic biases : Algorithms can amplify biases in historical data, leading to discriminatory credit or pricing decisions
• Technology dependency : Excessive automation leaves banks vulnerable in the event of an outage. The balance between AI and human intervention remains necessary
• Implementation costs : AI integration can be costly, especially for mid-sized institutions
• Regulatory compliance : the AI Act, the GDPR and DORA impose a demanding framework that requires constant monitoring

To learn more about the impact of AI in other industries, check out our articles on AI in agribusiness, AI in manufacturing , and the 5 sectors most impacted by AI.

Why use Wayden

Wayden supports banks and insurance companies in the adoption of AI thanks to interim managers specialized in digital transformation and compliance. Our experts help institutions take advantage of AI opportunities while managing regulatory and operational risks.

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Frequently asked questions

How is AI transforming the banking industry?

AI is transforming banking in several areas: process automation, personalization of customer services, real-time fraud detection, predictive credit risk analysis, and optimization of regulatory compliance.

How much are French banks investing in AI?

BNP Paribas is targeting €750 million in value generated by AI by 2026, with 780 use cases in production. Societe Generale has a target of €500 million. Generative AI could save the global industry $300 billion.

What is the European AI Act?

The AI Act is the European regulation on artificial intelligence. It classifies systems by risk level and imposes obligations of transparency, explainability and human oversight. Banks must adapt their scoring, fraud detection and automated decision-making systems.

What are the risks of AI for banks?

The main risks are the protection of sensitive data (GDPR), algorithmic biases, technological dependency, implementation costs and compliance with new regulations (AI Act, DORA).