What impact can AI have on the bottom line in banking and how?

"1. Workforce acceleration

A marginal gains approach to deploying many productivity improvements across the human workforce. At the most basic level, this will include automation of repetitive tasks such as data entry and analysis, search and query, draft production of many varieties of operational content (meeting minutes, communications) and summarizing large documentation. This is the type of text and images productivity support perhaps most associated with GenAI, particularly among newer users.

2. Engineering transformation

Specifically, to benefit bank's large technology functions, GenAI can already generate and optimize software code, reducing the time to write, while improving quality. As many software engineers in banking information technology (IT) tend to be relatively inexperienced and requiring oversight from senior engineers, GenAI co-pilots have the ability to accelerate production releases and make maintenance less onerous.

3. Loss avoidance

Risk management, fraud prevention, cyber, legal and other brand protection functions have high potential for improvement through AI. These functions tend to be improved by speeding up processes, expanding scope of processes, and providing wider sets of data inputs to improve process performance - all of which AI readily supports. Specifically, AI-enhanced credit risk management improvements can result in fewer loan impairments and write-off charges. Fraud prevention and FinCrime processes can be accelerated and expanded using AI to review a wider set of input data sets to uncover new insights on actors and ultimately reduce losses.

Growing revenues through new capabilities and improved retention

1. New capabilities for growth

a. Insight-driven pricing: real-time customization of pricing to make highly competitive offers to target customers based on enhanced measurement of their credit risk.

b. Hyper-personalized marketing: improved conversion rates based on insightful identification of individual prospect and customer/client needs, and highly-tailored communication.

c. Next generation trading algorithms: trading income uplift from enhanced market insight and automated trading decisions.

2. Customer experience and retention

AI-powered digital agents can reduce customer wait times by addressing an increasing range of complexity of customer requests. While certain customer journeys must remain as personto-person interactions, the improved responsiveness of digital customer service agents can improve customer experience and retention rates. Increasingly, the quality of AI interaction with humans will improve as AI technology develops-adjusting the AI agent's behavior according to the behavior/ emotions of the customer"

Author

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