Artificial Intelligence in the World of Financial Services

Written by Samee Zafar

Edited by ChatGPT

The fascination surrounding Artificial Intelligence (AI) lies in its potential to master machines and design algorithms that can perform tasks more efficiently than humans. This encompasses everything from piloting driverless cars to analysing intricate legal documents, activities that are already prevalent today. Looking forward, we envision a future where intelligent robots dutifully serve as assistants, fulfilling orders and tending to our needs.

Simultaneously, there is apprehension surrounding a dystopian vision, akin to Mary Shelley's tale of Frankenstein, where our intelligent creations turn against their well-intentioned but perhaps foolish creators. The film Blade Runner also conjures up fears, depicting "replicants" living amongst us, requiring identification and retirement.

This article, along with a series of forthcoming pieces in our newsletter, does not delve into the realm of monsters or replicants but rather explores the practical applications of AI in financial services. The objective is not for machines and algorithms to seize control of the financial world, but to become more valuable and efficient tools than ever before.

At the core of AI's potential lies its ability to assist in decision-making by analysing extensive sets of complex and unstructured data, continually learning, adapting, and improving.

The application of AI in financial services can be viewed from two angles. First, there's the "process-side," enhancing an entity's internal processes, rendering them more efficient and rendering internal decisions more pertinent and precise. Second, AI-trained applications function on the "client-side," helping the entity comprehend client behaviour, resolve customer service issues, and provide clients with advice on intricate matters such as asset allocation strategies in wealth management.

Process-Side AI:

AI can play a vital role in transactional risk management, allowing payment companies to identify and predict fraud. Online merchants often grapple with fraud prevention systems that flag legitimate transactions as fraudulent, leading to revenue loss.

Lending to businesses can also benefit from AI, as it can analyse various data sources to make credit decisions. This enables better predictions of which businesses pose higher lending risks and whether credit limits should be adjusted to prevent defaults.

Insurance companies can determine premiums with greater precision by assessing customer profiles and behaviour. Similarly, banks can continually refine pricing frameworks to reflect changing risk patterns.

Marketing analytics represents another area that could significantly benefit from AI. By analysing patterns, AI tools can lead to more successful marketing campaigns, boosting product sales and customer acquisition.

Client-Side AI:

AI-powered customer service agents or bots have the potential to significantly enhance customer service. Unlike current bots, AI bots can answer client queries with relevance, employing intuitive natural language interfaces rather than relying on keywords.

Robotic advisory agents, previously hyped in futuristic articles, have not fully met their promises. AI-powered applications can offer customised advice on complex "high-touch" matters, providing clients with the understanding and relevance they seek.

AI can also play a role in designing customer and employee incentives based on customer behaviour and preferences.

While there is considerable excitement surrounding AI, fuelled by successes like ChatGPT, progress has been gradual but promising. Investors now eagerly await tangible results showcasing AI's direct impact on banking and payments, leading to increased revenues and cost savings.

Concerns about AI potentially causing job losses are not unique, as past innovations and inventions have raised similar alarms. Challenges in the short term often lead to new opportunities and employment avenues in the future.

The content of this article does not reflect the official opinion of Edgar, Dunn & Company. The information and views expressed in this publication belong solely to the author(s).