How analytics makes wealth management unbiased?

Investment managers of today are out chasing the alpha. They are expected now, more than ever, to justify their management fees by giving a superior return on investment. This is especially the case when there are so many free and cheap passive investment avenues out there for investors to invest in. Only a market-beating return will satisfy customers of today and investors are looking at analytics aided improvements to achieve these performance improvements especially through the debiasing of investments.

Through advanced analytics, investment managers are able to rely less on instinct and more on data, thereby reducing the chances of making sub-optimal trading decisions. The ‘debiasing’ effect that analytics is playing can help bring about a lot of positive change, in the highly competitive and sometimes opaque industry.

Analytics increasingly becomes popular as wealth managers are recognizing the risk of relying purely on instinct for their decision making. It has come to the fore that human beings are incapable of being purely rational. Behavioral economics has proved that biases and irrational considerations based on our lived experience affect all of our decisions including those such as investments. Hence it is essential for us to rely on ‘Artificial intelligence’ that is sophisticated and data-driven as a way to counteract bias.

How does bias affect decision making?

In a study conducted by McKinsey, it was observed that traders were overcommitted to the positions they held and tended to hold on to them even when contrary evidence was presented. This was due to endowment effects and confirmation bias. The ‘endowment effect’ referred to the cases in which owners of a certain asset held on to it, despite any change in conditions and ‘confirmation bias’ refers to how our stereotypes lead us to discount beliefs that go contrary to our own.

How can Analytics help?

Using a digitized wealth management platform with Robo advisory and actionable analytics, that uses pure data to drive conclusions, can help temper the bias in investment management. Machine learning algorithms that learn from swathes of historical data and investment patterns help decision-makers get better and more scientific. The consistent biases and the emotions that made investment managers hold on to bad investments and stay away from certain industries due to ‘lived experiences’ could be neutralized by the power of Analytics and Robo/AI based investing.

What gives investment managers using analytics an edge?

When investment managers are using a digitized wealth management platform, they benefit from the huge data sets and patterns that the AI has been able to analyze over time. Big data is compiled about the investment performances and patterns of millions of users over millions of trades. This factors into the recommendations that the AI-driven Robo advisor makes.

It also factors in a number of variables such as the investment horizon, risk tolerance, preferred investment types and more to help arrive at the perfect investment strategy for you. Biases such as overconfidence, loss aversion, endowment effect are all erased as the AI relies purely on performance data collected from thousands of variables.

Looking ahead

Analytics will definitely impact the decision making of wealth managers for the better. This will help wealth managers make more profitable decisions for their clients and increase the value of their portfolios. A study conducted by Mckinsey revealed that debiasing using analytics helped fund managers gain potential improvements between 100 and 300 basis points.

Wealth management firms that leverage this cutting-edge technology will consistently outperform others in the market. They will create a lot of value for their investors and will fare much better than traditional firms without the analytics edge. It has become evident that only the firms that are willing to change with the times and adopt technology will capture the major share of the market, especially the tech-savvy and millennial one.

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Predictive analytics in wealth management The new normal

The wealth management landscape is ever-evolving and wealth management firms of today are increasingly adopting cutting edge technology to cater to tech-savvy millennials. The expectations and preferences of today’s clientele such as increased insights, automation, and 24X7 customer service can only be met by leveraging smart tech.

Investment managers of today are investing in wealth management platforms with AI-enabled advisory and predictive analytics to cater to these demands. The latest report by BCG on the wealth management landscape stated that 75% of wealth management firms are investing heavily in big data and analytics to meet evolving customer demands.

One of the major innovations in the space in the last decade is predictive analytics, which basically means the use of historical data to determine and predict the relationships between different variables in the wealth management process. Predictive analytics helps build models and processes that optimize the wealth management process, introduce high automation, and predict asset failure.

Predictive analytics is a space that is seeing huge growth in the market due to the value they provide to wealth managers in terms of cost savings and process efficiency. Using predictive analytics at different stages of the customer funnel is helping wealth management firms keep pace and deliver the coveted ‘high touch’ experience that clients have come to expect.

Here’s how predictive analytics is transforming the wealth management space:

Aligning business strategy

Predictive analytics helps wealth management firms anticipate investor demand, life events, attrition, investment patterns and more. This can help firms align their business and their product offerings according to this data to limit attrition and improve investor retention. It also helps firms understand investors with the highest risk of leaving and the highest lifetime value, so the managers can take appropriate action and effort to minimize the risk to AUM.

Data-driven intelligence

Robo advisory is being offered as part of the wealth management services which recommends portfolios for each financial goal by blending Robo capabilities with human intelligence. This automation helps in streamlining the process for wealth managers by eliminating redundant tasks.

Smarter client acquisition

Predictive analytics enables wealth management firms to customize their products and offer more targeted services to their clients. It enables them to recognize HNI clients and create custom investment opportunities for them. It also helps drive customized, personalized.  and intelligent customer communications. From email communications, sales calls or message communications, analytics helps personalize them to offer a seamless experience leading to higher client acquisitions.

Exceptional customer service

Predictive analytics helps wealth managers give customers contextual advice. It helps wealth managers predict customer needs and approaches them with the right solution at the right time. Big data can be used to mine customer behavior through surveys, market patterns, risk levels and more to help provide tailored advice that customers appreciate. It also helps wealth managers make real-time recommendations, investment ideas, and financial plans in minutes, instead of hours.

Helps the research process

Predictive analytics and NLP can help asset managers make sense of vast unstructured and structured data sets. It can help managers understand patterns and trends in the data and make smarter decisions based on this research. This helps asset managers save on hours of time that they would have spent parsing through the data.

Higher visibility into operations and reduced costs

Digitized wealth management platform will help wealth management firms optimize processes and reduce back-office costs through better human capital management (optimizing hiring process), optimal demand management (optimizing effort based on customer lifetime value), and reduce due diligence costs through next-generation digitized KYC. These optimizations will help keep firms competitive and help the bottom line in this cut-throat market.

What does the future look like?

As wealth management platforms grow more and more sophisticated, the high investment in AI-based models means that they will become even more accurate. This means that investors can expect more personalized and better service from their advisors. Wealth management firms will be able to leverage these insights to create better opportunities and drive superior performance for investors. Firms that fail to leverage analytics will underperform and eventually will not be able to keep up with their tech-savvy competitors. However, those who do invest heavily in AI at this stage will capture a lion’s share of the millennial investor base.