What is a Robo Advisor?
Robo advisors are rapidly becoming the biggest disruptor to the traditional wealth management industry. Existing and future investors expect easier to use, cost-efficient tools. Now is the time to invest in the opportunity to apply robo advisory technology and services.
Customer offerings fall into three categories:
Pure Robos – Algorithms recommend stocks and manage portfolios
Clients = investors who don’t wish to take advantage of advisory services and want to take advantage of low fees while making some investments
Hybrid Robos – Combine pure Robos with on-demand advice from an investment advisor
Clients = Existing investors looking for more flexibility
Advanced Robos – Use more complex algorithms to create and actively manage the portfolio
Clients = wealthy investors
Implications – achieving growth, staying profitable and staying competitive.
Achieving growth – broaden the market to clients whose assets are below the minimum required by traditional investment advisors.
Staying profitable – automated platforms are cost effective and allow firms to remain profitable.
Staying competitive – the younger generation aka digital natives are accustomed to online apps. Digital savy investors or those who want more personal control over their portfolio or want lower fees, prefer to use some level of robo technology. Online brokers, asset managers, wealth manager, insurance firms are working towards using more electronic services and automated investment solutions.
Competition is gearing up
The number of robo advisors is growing rapidly. We estimate robo advisors will manage around $8 trillion of total global AUM by 2020.
How to go Robo?
Wealth managers need to start the digital transformation journey. This requires a rethink of which strategies to best capture the current and next generation of customers, while competing against other digital players who offer new investment platforms using advanced robo technology.
Successful digital transformation depends on how firms manage the transformation, this goes beyond just implementing new technology. At the heart of the design is the customer experience, as well as a rethink of traditional operational processes in order to use the best digital capabilities and get a profitable ROI.
CVA Services help firms to translate their digital needs into actionable strategies, creating cutting edge solutions and services. The Digital Strategy team work with clients to understand the gaps between current and target states and to create a plan to deliver the desired digital experience. We will also guide you through decisions to build, buy or partner with robo technologies.
What is Artificial Intelligence?
An AI solution can be found in many areas of finance such as AML, Fraud, Credit Risk assessment and financial services Chatbots. In the trading world an AI system can scan for trading opportunities across different markets, back test millions of market strategies before optimizing the result and use neural networks to learn from results to create new strategies and patterns. An AI system quickly adapts, without emotion to changing market conditions to automatically execute trade orders to generate profits.
The investment in AI systems will lower the cost of operations and increase value, creating alpha in the new world of digital technology. An AI system can be used to model compliance and regulations workflows, detect fraud from big data, improve cyber security, improve and automate credit scoring workflow, lending and insurance quotes.
Types of AI
Weak AI/Narrow AI – focussed on one narrow task e.g. automated answer machines at banks, Siri
Applied AI – deep learning models, intelligence limited e.g. biometrics recognition, machine engineering, self-driving cars
General AI – intelligence but not limited to a narrow field, attempts to improve full congnitive behaviour, learning, reasoning and predictive analytics
Training the models – AIaaS
AI as a service provides working models of trained machine learning/AI algorithms for some use cases. The reach the full potential of AI models will depend primarily on two things, training the models and access to vast amounts of data. Existing financial institutions have an advantage over newcomers to the market due to their existing and available big data.
How can CVA Services help with AI projects?
It can take a large amount of time to train the technology on a new data set before it can be put to practical use for whatever business process is to be converted into algorithms and AI. CVA Services can help manage projects, help with vendor selection and provide suitable data scientists to ensure coherence and quality standards for data and testing to support the decision owners and processes.