The past few years have been a race for relevance for wealth managers, with the financial services sector undergoing massive changes. Customer expectations, regulatory developments and the increasing impact of technologies are driving a paradigm shift in the market. Therefore wealth management organizations are assessing their growth strategies and identifying ways to capitalize through new opportunities such as deployment of Artificial Intelligent (AI) led solutions.
There has also been a constant transformation in investment patterns, customer awareness and subsequently customer expectations from wealth managers in the Indian market. For instance, a lot of Indian investors are now relooking at their investment priorities, with many of them willing to consider beyond traditional financial asset classes such as Fixed Deposits, gold and assets —to more sophisticated instruments of investment. This trend will likely lead to more innovation, increasing risk appetite and overall growth in the ecosystem.
Amidst these evolving trends, wealth managers, across the globe, not India alone, are challenged with tons of data generated, that they need to decipher to keep abreast with market and customer requirements – i.e. news from media, trading insights, regulatory trends, company developments and so on. This has led to wealth advisors proactively adopting AI to support them in deriving insights from information.
To add, multiple financial technology companies with a completely non-traditional approach to wealth management, are disrupting the dynamics of this market. Players such as Shubh Loans, MoneyTap and Fino PayTech are just a few examples. Along with these tech-driven players and start-ups, are organizations and banks who want to be more innovative and agile in their approach and services to customers. In many ways, it’s probably the most fascinating time to be in the wealth management space.
AI: The ultimate tool to deliver financial wellness
If early predictions are anything to go by, 80 percent of ‘heritage financial services firms’ will go out of business, become commoditized or exist only formally but not competing effectively by 2030 (Gartner). The agency further forecasts that these firms will struggle for relevance as global digital platforms, fintech companies and other non-traditional players gain greater market share, using technology to change the economics and business models of the industry.
Adoption of digital technologies will thus become the most effective tool for incumbents and new players to build and sustain a competitive edge. Yet, wealth management is considered to be one of the least ‘tech-literate’ sectors of financial services (PwC). But, that is going to change.
So far, organizations have been focusing their efforts and investments in leveraging AI for improving operational efficiencies, streamlining processes, and to a large extent in reducing costs. Robo-advisors are already mainstream in the industry. They have been very effective in providing reliable investment management services online, with minimal human intervention and at reduced cost.
New applications emerge
Year 2019 is considered to be critical for AI and ML as several companies are looking to expand their use cases to broader applications. According to a Deloitte survey conducted last year, about 53 percent of executives in the financial sector who are familiar with AI say that their institutions are developing or have already launched commercial deployments or pilots of AI applications.
The rise of popular robo-advisor platforms is a great case in point. The potential of AI goes beyond this aspect to offer further customization, through digital services by adopting a hybrid model. This allows advisors to better serve both High Net Worth and mass affluent clients through appropriate channels. While robo-advisory platforms are one side of the story, firms need to focus on more tools and apps to deliver an automated, intelligent and predictable experience.Some new trends, beyond robo-advisors are here to stay.
- AI for personalization and engagement: AI can help financial advisors to gain insights for their clients and provide personalized recommendations by taking into account clients’ goals, trends in financial trading and risk appetite. For example – AI can track media news and alert wealth advisors regarding market events and regulations that can benefit the clients.
- AI for future trends and growth: Let’s take this a step further, with support from AI/ML based approaches, wealth advisory firms can train their models to correlate between events (such as new IPOs or annual reports) and past choices of the customer. The software may then prompt advisors when similar opportunities arise in the future.
- Better client profiling: wealth advisors can also use AI to create profiles of clients. They will be able to generate and maintain profiles with ML and natural language processing (NLP).
- Decrease customer complaints: AI can enable an assessment of frequent complaints and support resolution of these issues and increase the overall customer experience. This process can also support mapping a suitable wealth manager to a client based on traits and nature of complaints.
- Risk Management: Advanced algorithms can complete analysis of unstructured data, without expensive resources, within minutes or even seconds. This allows wealth managers to focus on their clients better and manage client risk assessment simultaneously.
In India, it’s encouraging to see that AI is already a key investment area for banks and financial services companies.
The evolving role and contribution of wealth managers in an AI driven economy has been a topic of much debate and discussion and wealth managers will need to expand their horizons, by not only focusing on AI but also changing the way they engage with customers.
AI is already an integral part of investment firms’ technology and business agendas today. Nevertheless, success rates of AI projects will be determined by the interplay of human expertise and algorithms. For instance, would wealth managers be held responsible in case of portfolio underperformance due to AI-led recommendations? Or would they not be accountable as they are merely following the recommendations of the system. In either case, wealth managers need to justify the need behind these technologies to their clients and also educate them about the implications.The author is the chief analytics officer & vice president of data sciences and analytics at Envestnet|Yodlee.