In the dynamic arena of banking, artificial intelligence (AI) has emerged as a potent force, reshaping the industry’s contours. The year 2023 bore witness to a notable infusion of these cutting-edge technologies, notably in the realms of fraud detection and the augmentation of customer experiences. The inherently data-driven landscape of the banking sector provides an ideal backdrop for the rapid and effective implementation of AI, setting the stage for a transformative journey in the industry.
As we step into 2024, there is a foreseeable surge in the adoption and efficacy of AI, with the banking sector continuing to lead the charge in the practical application of AI technologies. Beyond the established domains, banks are poised to leverage AI in financial literacy support, savings and investment planning, and overall optimization of financial situations for individuals and businesses alike.
This broader implementation includes enhancing customer experiences through personalized insights and bolstering security in banking apps, a crucial support mechanism as traditional brick-and-mortar bank branches decline in number, giving way to increased digital engagement channels.
As banking intertwines with various aspects of life, the expansion of AI in this sector will inevitably face heightened scrutiny and calls for increased regulation and adherence to best practices to ensure ethical and responsible technology usage.
Here are the leading trends in AI for banking in 2024:
1. Generative AI:
The ascent of generative AI heralds a new era of innovation, efficiency, and personalization within the banking sector. This technology has the potential to revolutionize banking operations and services, ushering in novel and unique offerings. McKinsey estimates that generative AI could contribute an additional $200 billion to $340 billion annually across the banking industry, unlocking efficiencies in backend operations and providing customers with improved support and unique experiences.
2. Responsible AI:
As the adoption of AI in banking and finance continues to rise, there is an escalating need for explainable AI models that are readily understandable, analyzable, and subject to regulation by business stakeholders and regulatory authorities. The imperative of ensuring unbiased and equitable outputs from these models becomes paramount, given the significant obstacles of trust and bias in the widespread adoption of AI. The establishment of AI “explainability” emerges as a critical component for banks, enabling the cultivation of trust, rectification of potential flaws, and mitigation of vulnerabilities within the models.
3. AI Governance:
Governments and regulatory bodies worldwide are actively developing robust AI governance frameworks to harness the full potential of AI while safeguarding against unintended consequences. The banking sector will witness an intensified focus on stringent governance and compliance processes to ensure the safe and responsible use of AI.
4. AI to Realize Financial Wellbeing:
Explainable AI will play a pivotal role in achieving financial wellbeing for both banks and financial institutions. From managing end processes to intra-day liquidity forecasting and sentiment analysis, AI will provide substantial benefits to customers, helping forecast cash flow, navigate financial difficulties, and make informed decisions regarding mortgages and wealth advice.
5. Expanding Data Sources:
As the Internet of Things (IoT) and social media continue to increase, an abundance of data becomes available about the banking industry and its customers. AI will be instrumental in extracting value from unstructured social media data and vast volumes of IoT data, merging this information with customer banking data. This integration will empower banking apps to offer novel and unique services, reshaping the banking landscape for years to come.