Financial institutions industry outlook

AI’s true value in banking

Sales and marketing and risk management functions are ripe for opportunity

Feb 27, 2024

Key takeaways

AI can provide value in customer service management, pricing and promotion and churn reduction.

The technology can also help detect and prevent fraud as well as money laundering schemes.

Institutions deploying AI tools should consider data availability and technology selection.

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Financial institutions
Risk consulting Financial services Automation Economics

ChatGPT may have sparked the initial buzz around generative artificial intelligence just a little over a year ago, but plenty of businesses have already either made it through or are approaching the implementation stage with AI tools. Global spending on AI is expected to top $500 billion in the next two years, according to International Data Corp., which identified banking as one of the top industries likely to garner investment.

For financial institutions, AI holds significant potential impact and opportunity in two areas: sales and marketing, and risk management.

Sales and marketing

Customer service management is likely the area within the sales and marketing function where AI will be able to provide the most value to institutions.

Take, for instance, Ally Bank, which made waves in 2023 by creating cloud-based platform Ally.ai. The first major product the organization derived from this initiative was directly related to customer service. Call center representatives at institutions are required to take notes during customer calls and then create a quick summary once the call is complete. Ally uses its AI technology to transcribe the conversation in real time, allowing the customer service rep to be more efficient and provide more accurate records—a critical point, given that accurate notes are required for regulatory compliance.

Beyond enhancing transcribing and note taking, AI can help use real-time voice recognition algorithms to redirect calls from distressed customers to experienced handlers. It can also optimize call center capacity planning by managing call volumes and predicting average handling times. Finally, the technology can increase customer satisfaction and reduce handling costs for institutions by routing requests to call centers based on multimodal data.

Channel management, pricing and promotion, marketing budget allocation, churn reduction, personalized offerings and lead generation are other key areas that AI can improve.

Risk management

Another area in which AI may add considerable value is the risk department. AI has become a critical tool in efforts to detect and prevent fraud as well as money laundering schemes.

One multinational bank developed an AI platform that encompasses a range of tools and services. Within its payments division, the bank deployed a machine learning model trained on internal data to identify transactions that would be considered an anomaly. The transaction is then routed to an employee to determine the true nature of the transaction. This machine learning model has helped the institution prevent and detect many fraudulent transactions. 

In addition to identifying potentially fraudulent activity, AI can enhance debt analytics. Determining accurate reserves for defaults has consistently been a largely subjective task for many banks. By deploying the appropriate models and generative AI tools, institutions can create an early warning system that more accurately predicts defaults.

CONSULTING INSIGHT: The middle market AI playbook

Artificial intelligence is changing how organizations do business, with tools and applications creating valuable opportunities for increased productivity and deeper insights. But before you can implement an effective AI strategy, you must understand how to align rapidly evolving solutions to your business processes and goals. Learn more about successfully deploying an effective AI strategy in our new guide.

Deploying AI in your institution

Sales and marketing and risk management are just two of the many areas in which institutions can harness AI. Depending on a given organization’s focus and strategy, AI applications in other departments—such as credit, accounting, human resources, compliance and information technology—may have just as much potential.

Depending on an organization’s focus and strategy, AI applications in other departments—such as credit, accounting, human resources, compliance and information technology—may have just as much potential.
Angela Kramer, RSM US financial services senior analyst

TAX TREND: Artificial intelligence tools

Financial institutions may choose to develop AI tools in-house or license them from a third party. The tax and accounting implications of each approach should be weighed in the overall decision-making process.

A business that licenses software can generally deduct the cost of that software in arriving at taxable income The tax treatment of software development expenses became less favorable for tax years beginning after Dec. 31, 2021. The Tax Relief for American Families and Workers Act of 2024 may restore the more favorable treatment, however, ultimate passage of this legislation is uncertain.

To determine where AI can provide the best value at your institution, consider the following key factors:

  • Use cases. Just because AI has made a large impact on a specific area within the banking industry doesn’t mean it’s the right fit for your institution. Analyze all the opportunities and determine where AI can be the most effective.
  • Data availability. Most AI tools train on data before being deployed. Your institution needs to identify key internal data sources that can help with a use case. Similar to any other area in the bank, the successful use of AI hinges on the quality and accuracy of the data.
  • Technology selection. Many institutions have developed AI tools internally, but not all companies have the capacity and resources to work through this process. For those seeking external resources, numerous technologies are available for purchase and implementation. Determining which will be the best fit is crucial.
  • Talent. Although AI is a rapidly growing industry, a limited number of people have the experience and expertise needed to deploy AI tools. If creating a team of specialized employees with the right talent is not within the institution’s strategy, determining the right third party with the skill set needed for AI implementation would be the next step.

RSM contributors

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