Most articles and reports about AI focus on its generative capabilities, which are admittedly more exciting to discuss when it comes to creating content and handling tasks traditionally thought strictly as ‘human’. However, AI has been around for years in various algorithms and solutions used by advisors to help them be more efficient, responsive, and comprehensive with their roles and customers.
#Automation, Accuracy and Efficiency
Like many other industries, financial advisers are overworked, so a significant portion of the industry are automating various back-end functions and customer-related tasks like portfolio management. AI can automate strategies that align with modern portfolio theory, selecting investments to maximise overall returns within an acceptable level of risk, establishing optimised passive indexed portfolios.
The technology can also alert investors when allocations fall outside parameters. AI can then continuously scan and rebalance portfolios with minimal user input – whether that be a financial advisor or an independent trader.
Another key component of using AI is digital twins for simulating various economic and market conditions to predict potential trends, disruptions, and risks. AI tools can be applied to automate reconciliation, invoice processing, fund accounting, and #compliancemanagement – processes that have traditionally manual, tedious, and prone to human error. For example, EY’s solution SARGE allows wealth management firms to extract the most important information from governing contracts and automatically detect liabilities, saving up to 75% of compliance management teams' time.
In the past few years, ESG investing strategies have become significantly more popular, and with the sheer volume of data relevant to investment strategies, AI is the only way to analyse sentiments in real time. MarketPsych Analytics, for example, provides financial sentiment and ESG software to users, leveraging data from 4000+ news and social media outlets while tracking all major asset types and covering over 30,000 companies globally.
Everything from customer processing through to cybersecurity can integrate AI to improve performance and scalability. As AI technologies become more intelligent and capable across back-end analytics and front-end generative functions – there’s significant potential for these technologies to improve advisors’ relationship management from end to end.
With the support and efficiency of intelligent technologies, advisors can provide more bespoke advice, recommendations, and ongoing communication that puts #customerexperience first. At its simplest, automating various functions and tasks should free up time and resources that can be dedicated to customers’ engagement, satisfaction, financial security, and strategic decision making.
In the next post, I’ll look at generative AI and the customer-facing functions being automated via intelligent technologies.
