Innovation: Artificial Intelligence (AI) Is Making Its Way Into Wealth Management!

Improvement of portfolio management practices, better assessment of the risk profile, personalized and up-to-date customer service, lower production costs… Artificial Intelligence is definitely on the way to revolutionizing the wealth management sector. This is the decryption of the week!

AI in Wealth Management: From Buzzword to Critical Competitive Advantage

Like many technological breakthroughs, AI has long suffered from the “prototype” syndrome. In other words, this innovation did not manage to confront the reality of the business world, except in certain pioneering Tech firms in the field. Today, AI supports marketers, financial analysts and other Data Scientists on a daily basis. What about wealth management?

• Rationalization of decision-making
• Ways to improve the offer
• A more personalized customer experience
• A substantial reduction in risk
• A reduction in the cost of production thanks to the automation of tasks.

Concretely, AI makes it possible to optimize portfolios, to formulate forecasts with a lower margin of error and to save time than repetitive tasks. It can also automate and deepen the establishment of the risk profile, analyze the “sentiments” of the market, provide Insights on events likely to impact performance, better understand risk management and possibly refine customer profiles.

Also Read: Giving Meaning To The Artificial Intelligence Landscape

AI to make the numbers speak

According to PWC, the impact of AI in wealth management mainly occurs in the processing of Data. More trivially, AI allows operators to make the numbers speak and then make informed decisions. “ Data is the raw material that AI converts into predictions and automation opportunities ,” reads the report.

In essence, the activity of the wealth management advisor is based on well-defined and therefore easily modelable use cases. AI can therefore intervene in the automation of tasks to reduce costs . Machine Learning, coupled with AI, is able to learn from past events and model them to then adapt to any type of data, even unstructured, without requiring human intervention. The advisor can then focus on more promising actions such as customer service, training and possibly prospecting .

AI to test and model risks

In addition to portfolio analysis and optimization, AI is increasingly popular in trading. Indeed, Artificial Intelligence can refine the choice of times, volumes and investment values. It fills in some gaps in traditional risk management, as shown by the dizzying fall in share prices in March 2020 in the United States. That month had seen one of the most dramatic crashes in history, with the US S&P 500 stock index falling more than 30% along with other asset classes.

Concretely, Artificial Intelligence Services makes it possible to refine risk management by testing and validating risk models upstream. Finally, it is able to extract data to generate precise forecasts, particularly from the point of view of market volatility, future trends and the risk of crisis in a given sector.

Better understand the risk profile of an investor

We’re not there yet, but it won’t be long. Experts predict that AI will become part of the daily life of the wealth manager, particularly from the point of view of the precise analysis of investment habits but also of customer consumption. An analysis that could lead to the thorough identification of the investor’s risk profile with a result that is much more relevant than the current forms.

AI to boost customer service

Thanks to developments in automatic text generation and NLP (automatic natural language processing), Artificial Intelligence is able to hold a conversation with the customer like an advisor would. Chatbots “powered” by AI and Machine Learning are now able to conduct an intelligible and coherent conversation with customers. They are also able to hand over to humans at the appropriate time to optimize workflows . We are therefore far from the archaic chatbots which were content to reproduce rigid and robotic conversational scenarios.

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