The Future of Wealthtech: Artificial Intelligence, Machine Learning, and Big Data Analytics


By Natasha Lane

Wealth management industry is swiftly changing with the emergence of new business models and modern technology. Artificial intelligence (AI), machine learning (ML), and big data are spearheading this dynamic evolution and fostering the growth of wealthtech.

More and more players are employing these tools in order to simplify business processes and help clients reach sound financial decisions through personalized advice. Indeed, this practice is linked to incredible benefits: it saves humans a wealth of time and ultimately, improves the investment outcomes.

Business intelligence reaches new heights

We live in the age of big data and information transparency, where cutting-edge tech tools can be applied to the entirety of the management value chain.

First off, thanks to rapid advancements in ML, the AI algorithms of today are capable of collecting, processing, and finding patterns in vast amounts of incremental data. So, risk assessment questionnaires are no longer the primary source of insights on clients’ historical info, present situation (credit score), and financial goals for the future.

Now, the social media, texts, news, media info, business documents, transcripts, and even natural language pose valuable pools from which data can be extracted. That is to say, AI and ML dramatically expand the business intelligence capacities. They allow wealth managers and advisors to accurately assess the strengths and weakness of clients and come up with actionable advice.

Analytical excellence within reach

Furthermore, big data and predictive analytics give rise to highly-sophisticated methods like sentiment analysis, data visualization, and heatmaps. Systems powered by them are able to analyze global macro and raw data and evaluate changing portfolio circumstances.

Coupled with data on all assets and liabilities, these operational innovations pave the way for a new kind of wealth management. Namely, complex financial projections can be made with a much higher degree of certainty. It is possible to give customers advice regarding retirement and long-term investment plans.

Of course, tech implantation is never frictionless and not all tools are created equal. Those who really mean businesses must recognize the importance of versatile, custom software solutions developed by trusted brands. Taking the time to shop around and investing funds in them is the key to making most of the available data and fueling algorithmic decisions.

Revolution is underway

Transformation of the traditional customer service is a great example of dividends tech pays. The role of human agents and representatives is shrinking, which reduces the overheads. The gaps are filled with chatbots and smart search features that take the customer experience to the next level.

Clients no longer have to spend a ton of time sifting through white papers and other lengthy documents. AI and ML-enabled systems answer most common customer queries and produce recommendations around the clock. At the same, time the risk of human error and diagnosis guesswork is decreased.

But, we are not announcing some imminent robot takeover here.  The majority of customers still want a human touch. So, for now, the combination of human and artificial intelligence will remain standard practice. In the future, though, the balance is likely to be tilted in favor of the later.

Conclusion

The future of wealthtech is here to stay, unfolding through the synthesis of three crucial technologies— AI, ML, and big data analytics. Forming the core of wealthtech systems, they lead to more custom-tailored products, generate data-backed financial strategies, and improve the overall consumer experience.


Natasha Lane is a designer, lady of a keyboard and a tech geek. Her expertise could be summed up in IT, branding and business growth-related topics.