Banking Research & Consulting | TABInsights

Leveraging AI/ML in Retail Banking

May 2023
USD 300

The increasing demand for relevant, immediate, and interactive customer engagement on a large scale, within a secure and trustworthy environment, is driving the adoption of AI and Machine Learning (ML) applications. These technologies have significant implications for financial institutions in four key areas: marketing and decision making, operational efficiencies, customer experience, and fraud and credit underwriting.

AI and ML models are now being utilized not only for fraud detection and prevention but also in a broader range of use cases that directly impact the customer experience. These models empower banks to achieve cost and time efficiencies. However, many banks face challenges when it comes to scaling advanced AI and real-time capabilities beyond selected use cases, hindering their ability to generate substantial business benefits throughout the organization. This report identifies the key emerging trends and specific use cases in AI and ML adoption within financial institutions, highlights the challenges they face, and outlines a strategic roadmap for scaling the adoption of AI-driven advanced analytics.

Publication date:

May 2023

Delivery:

The file is directly delivered into your account provided soon after online payment is received. The file contains a pdf A4 file  (28 pages).

The report includes:

1.Summary of key trends in data analytic in banks

2.Adoption of AI/ML applications and use cases

3.Key challenges and requirements for scaling AI

4.Roadmap to develop advanced AI and ML analytics

This report answers:

1.What are the current trends in AI and Machine Learning in retail banking?

2.How can financial institutions leverage on these capabilities and what are the use cases?

3.What is the impact on business growth and the customer experience?

4. What is the roadmap we see financial institutions take to build AI/ML capabilities?

  • 01. Key macro trends in data analytics across banks
  • 02. Adoption of AI and ML applications in banks
    • 2.1 Precision marketing
    • 2.2 Customer service management
    • 2.2.1 Conversational AI
    • 2.3 Fraud and risk management
    • 2.4 Operational efficiency
  • 03. Key challenges and requirements for scaling AI
  • 04. Roadmap to develop advanced AI and ML analytics
  • Financial Institutions interested in integrating AI and ML into their operations can use the information to inform strategic decisions and guide the implementation of these technologies.
  • Companies developing AI and ML solutions could use the report to understand the specific needs and challenges faced by banks and other financial institutions.
  • Investors in technology, financial institutions, or fintech startups could use this report to assess market trends and potential investment opportunities.
  • Fintechs looking to disrupt the financial industry with AI/ML technology could use this report to understand the landscape and recognize opportunities in partnering with banks.
  • Risk management professionals could use the report to understand the state of AI and ML usage in fraud detection.

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