From Human to Algorithm: How AI is Transforming Financial Advice

In the last couple of years, artificial intelligence (AI) has evolved from a new technology to a well-known term, integrating itself into various sectors. In fact, Capgemini research predicts that explosive GenAI adoption will only continue with three in five organisations seeing innovative work as the largest benefit of the technology. 

As AI becomes a permanent fixture, it is the responsibility of business owners and professionals to determine how to integrate it into their daily operations. Financial advisors, in particular, encounter a distinct opportunity and challenge in leveraging these tools to manage their businesses and assist clients.

What are AI primary use cases for financial advisors? 

One of the primary uses of artificial intelligence is the automation of routine tasks - and the financial advisory industry is not an exception. This automation frees up time, allowing people to focus on more complex and personalised aspects of client service.

AI can also be used to provide financial recommendations with a personal approach. By analysing large amounts of data, AI algorithms can identify trends and insights that advisors can make use of to offer tailored advice that aligns with each client's unique financial goals and risk tolerance.

Additionally, AI-powered chatbots can be used to deliver recommendations and consultations to clients, who, in turn, can receive immediate assistance and answers to common questions at any time, leading to greater customer satisfaction. Furthermore, the use of AI chatbots enables 24/7 availability for basic consulting. 

AI tools can also prove very valuable in terms of market analysis and forecasting. They can process and analyse large datasets at high speeds, helping advisors make informed predictions about market movements and investment opportunities. This enhances the advisors' ability to develop investment plans for their clients.

Lastly, there is risk analysis. AI can assess potential risks quickly and more accurately than traditional methods. This includes, among other things, credit scoring, where AI can provide a swift and precise evaluation, helping advisors to make better-informed decisions about lending and investment.

Room for improvement. How can AI limitations be addressed?

One of the most significant limitations is that AI lacks ethics and empathy. Unlike human advisors, it cannot understand the emotional context of a client's situation, which can be crucial in decision-making and performing a fiduciary duty. This absence of this human quality can lead to technically correct recommendations that do not align with the client's broader values and needs. 

This issue can be addressed through a hybrid model, where AI and human advisors work together. In such a model, AI can handle routine tasks, data analysis, and preliminary recommendations, while human advisors review and approve these actions, ensuring they align with ethical standards and the client's personal circumstances. 

Transparency in AI algorithms is also crucial in fostering client confidence. Financial institutions must openly communicate how their AI systems operate, what data is being used, and how decisions are made. This way, clients can better understand the role of AI in their financial planning and feel more assured that their interests are being safeguarded.

Aligning AI with current human ethical standards is a complex matter, and AI researchers and enthusiasts still have a lot of work ahead of them to address it.