July 8, 2016
Although some suggest that consumers resist robo-advisors, over the past years, the technology has been attracting substantial attention and investments. Financial decision-making is increasingly reliant on algorithms applied to wealth management, personal finance management, investment management, risk assessment and other areas of the financial services industry.
Rapidly advancing robo-advisors allow analysts to look into the future and continuously trade securities and other assets based on long-term predictions they are able to build based on a real-time stream of data and machine learning capabilities.
Among the drivers of automated algorithms adoption in financial services are lower account minimums, lower fees, upgrading technology and demographic advantage. Assets managed by robo-advisors are estimated to increase by 68% annually and reach ~$2.2 trillion in five years. Other estimations suggest that robo-advisors will be managing $8 trillion globally by 2020.
A new research paper published on Wednesday by SEI emphasizes one of the trends shaping the investment industry as ‘Watsonization’, which refers to cognitive computing systems that can interpret massive quantities of data, learn as they go, and will hold an information advantage over today's analysts. They will also give investment firms powerful new tools for interacting with investors, assessing risk, enhancing cybersecurity and more.
The study suggests that cost-efficient robo-advisors that will use sophisticated algorithms to made decisions about funds allocation will make a big wave in the industry and grow to $7 trillion in AUM by 2025.
The growth and development of the robo-advice industry not only has positive financial implications as a result of lower fees, but also automated systems facilitated inclusion for mass market consumers with < $200K. Those consumers can now afford a tailored advice for better use of their funds.
Robo-advice powered by technology diminishes the barriers for market entry to a range of whole new types of players. As Deloitte emphasizes, Both financial and non-financial services firms can take advantage, bringing new levels of competition and innovation to the industry. For instance, we will likely see more asset management and insurance firms adding wealth advice to their distribution and effectively entering wealth management; non-financial service firms with access to large numbers of retail investors and leading-edge technology firms will likely also enter wealth management through a robo-advice model.
With the pace of improvement that AI, machine learning and overall technology goes through, robo-advice has the potential to become highly personalized and specific over time, meeting particular needs of different groups. Algorithms don’t have an affluence towards a particular task like fund allocation; the very idea here is that automated advice can get to the point where it can be tailored to analyze any stream of data by demand and become a highly personalized personal assistant in anything.
Recognizing a multi-trillion-dollar opportunity, a range of institutions are already investing in the exploration of big data analytics, machine learning and AI application across industries: in customer acquisition, marketing, customer retention, loyalty programs, risk management, etc.
In the example of marketing and customer retention, analytic solutions that combine historical transactional data coupled with external information sources can boost the overall conversion rate. Firms are effectively leveraging these solutions to increase the cross-sell and upsell opportunities, understanding customer requirements and providing customized packaging. Card-linked offers, customized reward solutions are some of the offerings that are being provided by financial technology firms.
Robo-advising is not a proprietary breakthrough for investment management, it is a chance for a range of industries to leverage the power of machines in order to jump to the next level of customer service.