The ongoing advance of AI, machine learning, and data analytics is affecting buy-side traders, wealth managers, and developers. So what are the industry trends to watch and what are the challenges for Fintechs?

Fintech development has impacted various financial sectors. Technologies have fast-evolved trading workflows, helped in the fight against financial crime, and advanced the digitization of wealth management.

The application of technology in the world of finance is not something that we need to fear. It will not replace human expertise or knowledge, rather it will enhance it, helping financiers to make informed decisions using vast swaths of information and data.

So let’s take a look at some of the big questions in fintech and the expert responses of those who are working in fintech.

What will be the biggest hurdles to the adoption of AI in financial services in 2020 and beyond?

Talent, adaptation, and infrastructure are the main challenges that face the development of the fintech industry moving forward.

The level of knowledge and skills required to enhance the capabilities of AI and machine learning tools is small. Not enough people know how to make the technology that is in demand, and how to work with it in real-world applications.

Another issue is legacy systems that are not optimized for data-driven technologies. This is especially prevalent in traditional big banks, who also do not have the talent pools to understand the new technologies and how to adapt them to the existing technology.

It is one of the main reasons that fintech start-ups are thriving, and are likely to continue to do so. Such startups are not challenged by company culture and archaic infrastructure.

How will trade automation, trade performance analytics, AI, and machine learning impact trading professionals?

It is generally agreed by fintech experts that technology will only enhance human knowledge, unpinning decisionmaking.

In regards to trading, technology is playing a massive role in the dissemination of information and tracking, but it is still ultimately humans making decisions.

When it comes to banking regulation, financial stability, and corporate finance, technology cannot replace the commonsense aspect of human decisionmaking.

The tools that are provided by the advance of technology compliment the decisions that humans make, not replace them. An over-reliance on technology to do the work of traders would be potentially harmful to the trader and their clients, as machine learning and Ai are not yet adept that the nuances of lateral thinking.

How do customization and enhanced data tools change the roll of wealth advisors?

Such tools have changed the skills that wealth advisors need to acquire to excel in their job. Advisors need to understand how AI and machine learning technology reach the proposals set forth, rather than rely on the data analytics completely.

Advisors will need to broaden the range of their knowledge to include not only the financial but also the technical aspects of their business to remain competitive. It will not be enough to simply regurgitate the analysis and follow the solutions of machines, they will need to understand the processes and determine if the solution or solutions offered are, in fact, correct for the unique set of circumstances.

What will make the greatest impact on financial markets in 2020?

Politics. The global impact of Covid-19, if US President Donald Trump is re-elected or impeached, the US/China trade wars, Brexit, unemployment, and the collapse of airlines is going to test the economies of nations and the global economy.

Wealth disparity is becoming increasingly large, and the pandemic is going to force that gap wider as people are unemployed or forlorn, while others profit from a scramble to manufacture personal protection equipment and research a vaccine.

Behind all of this is technology. Companies switched from manufacturing machines to making ventilators. Researchers dropped other studies to focus on coronavirus. Clothing manufacturers and plastics manufacturers are producing PPE.

The overall effects of the pandemic will not be known for many years, with pollution set in increase and young people held in unemployment for long periods post-academic graduation.

Technology will be used to create models and forecast potential outcomes, but before vaccination is discovered and administered to a critical mass of the population, such conjecture serves little purpose as the variables are too large.

Will sustainable wealth be data-driven in 2020 and beyond?

Data could be leveraged to enable sustainable development in various ways.

People are interested in investing in ventures with a focus on sustainability and ethics. Data is already being applied to inform investment choices.

Sustainability data is already being used to inform financial decisions, and it looks likely to continue to underpin many investment decisions.

People want to see data that shows that companies are acting ethically, and if the company can prove their actions with blockchain technology for example, they are more likely to attract investments.

Such data can be used to expose unethical behavior as well. Suppliers, consumers, and regulators are all looking far more closely at businesses who are not conforming to the standards that people are demanding, and advances in technology make this easier. It will put companies in a position where they cannot hide any unethical practices.

The next decade will likely be dominated by AI and machine learning, however, the pandemic might have slowed some progress in developments. Blockchain technology might be bolstered by the need to track and trace people for vaccinations and virus outbreaks, however, resistance to such invasive tracking by governments might see the benefits of this immutable record held back until a time when people begin to trust authority again.

While predicting changes is always a challenge that requires much economic and social information, the unpredictability of the influence of the pandemic has made 2020 and beyond less certain.

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