According to a survey conducted by KPMG, 75% of bank customers surveyed by KPMG said that they were very likely to consider financial advice from a Robo-advisor.

Making a mark in the fields of banking, wealth management and other financial services is not a short term project, but a long one. However, Robo-advisors have changed the way how we look at the financial landscape by providing automated financial planning services using a set of algorithms fed by data with minimal human intervention. The fact that the existence of robo-advisors is only known since a decade provides for the need to intervene and make sure that the algorithms are defect free and are those which incorporate as many test scenarios and data points as possible.

Robo-advisors: The Talk of the Finance Town

How Robo-advisors work: Robo-advisors run on a pre-determined algorithm where once the customer enters all their financial information such as net worth, annual income and risk tolerance, it proceeds to provide an investment portfolio and a solid wealth accumulation strategy.

Where Robo-advisors win: When compared to traditional advisors, Robo-advisors offer the opportunity of a lower minimum investment at a lower cost and with minimal amount of time being spent on time and research.

Challenges that need to be countered: Where human advice wins is in the area of emotional intelligence. Technological experts have to take into account the lack of emotional intelligence in Robo-advisors and counter accordingly.

The Ultimate Aim of Robo-advisors: Robo-advisors should always have an upward growth curve where financial success is guaranteed with the minimal use of time and research.

Why it is necessary to make it defect free: Complicated tax planning, real estate investment planning and multiple stage retirement planning are some of the many different complex scenarios that robots would have to provide suggestions about. Also, Robo-advisors would have to be prepared to incorporate unexpected economic meltdowns such as the economic meltdown of 2008. For such reasons, it is vital that Robo-advisors are defect free and provide the perfect recipe for wealth accumulation amongst its customers.

Prerequisites to a Robo-advisory’s QA Process

To understand the intrinsic details of a QA Process, it is always important to connect the dots from the functionalities itself. So what are the different functionalities that one can foresee to improvise with in the distant future? To understand that, one has to understand the priority requirement of Robo-advisors. Robo-advisors were brought into existence to remove wealth management inefficiencies.

At present, a few options have grown into a myriad of options as they build on systematic financial planning strategies. However since their inception, Robo-advisors have been offering quite a few options in the financial spectrum. The basic functionalities include those such as online onboarding, customer profiling, portfolio selection and tax loss harvesting. These functionalities require a proper automated testing cycle with a proper strategic testing framework. Test cases need to be written and executed properly to prevent the very thing that allowed the existence of Robo-advisors, inefficiencies.

Successful Implementations

Financial corporations like Fidelity launched Fidelity Go, a digital financial advisor which was designed to appeal to the millennial crowd with a low minimum balance and portfolio rebalancing options. Since then banking services like JP Morgan Chase, Morgan Stanley, Wells Fargo and Merrill Lynch have all rolled out Robo-advisors to compete and succeed in this digital era. This is also to clear out the defects in the banking and financial sphere that are becoming more and more evident to the customers.

The need of the hour!

Robo-advisors have to be treated like any other digital technology, (i.e. with intense automated quality assurance processes) and there has to be a particular strategy to ensure monetary security for those who invest in mutual funds and in the stock market or draw capital based on the advice of a robot.

Each customer to whom a financial advice or sound solution is provided has to be considered as a test case scenario. Each of these scenarios has to be structured with a strong algorithm fed by several data points which can be understood through the techniques of machine learning. This will ensure a gradual curve in the growth of Robo-advisors and their role in efficient investment solutions paving the way for maximum returns obtained through minimum risks.

Future Projections

So where does it go from here? The future of Robo-advisors hinges on particular factors and a corporation’s success in attaining them. The first pointer would be to understand a client’s needs. The second would be to pitch in a solution. The third would be to implement a solution and the fourth and final factor would be to monitor the results and adjust the solution accordingly. Through several iterations, each Robo-advisor would be able to predict and provide accurate solutions tailored for each client.

Conclusion

Robo Advice is a concept which since its inception in 2008 has garnered mostly positive responses. Young customers prefer to follow Robo suggestions and feedback concerning financial planning. However a slight irregularity in its functioning can scale up the losses on a massive scale, affecting thousands of customers. Since Robo advice is a fairly novel concept, the path forward would be an upward growth curve. However it’s going to be a messy curve and not a linear one. In order to propel the use of Robo-advisors, there has to be a significant increase in the wealth accumulation by the client as well as the returns generated by the banks and other financial services. This will allow for a profiting relationship to be forged for parties on both sides of the table.

The success of a Robo-advisor can only be achieved with zero defects. A defect rate of 0% can only be achieved through a comprehensive quality assurance framework that provides for every aspect and scenario that occurs or that which will occur in the future. Therefore a quality testing solution is the answer to a successful Robo financial advisor.

Ashish Ninan Cherian

Ashish Cherian is a marketing enthusiast who has an extreme interest in analytics and in studying customer behaviour. He wants to progress deeply in these areas and is keen on learning something new every day. He also loves to read, travel, and debate and is a huge foodie.