The trends to watch in fintech in 2020 have been examined by our #RefinitivSocial100 group of influencers. How will the rise of AI, machine learning and data analytics impact buy-side traders, wealth managers or developers in the year ahead?
- A LinkedIn discussion involving members of the #RefinitivSocial100 considered five questions regarding the trends to watch in fintech in 2020 and beyond.
- Technology already looms large on trading desks, but our influencers think it’s more likely to augment human knowledge and expertise rather than replace it.
- One of the biggest fintech hurdles facing financial services is the ability to plug new AI and machine learning models into existing core banking and payment systems.
For more data-driven insights in your Inbox, subscribe to the Refinitiv Perspectives weekly newsletter.
To examine the trends to watch in fintech in 2020, who better to ask than some of the thought leaders and social media influencers who make up our exclusive #RefinitivSocial100.
Together they have a combined reach of 4.7 million followers with their views spanning all of Refinitiv’s key finance areas, whether that covers the challenges of evolving trading workflows, the fight against financial crime or the digitalization of wealth management.
Find out what these influencers had to say during our recent LinkedIn discussion — then join the conversation on social media: #FightFinancialCrime, #TrustedData, #DigiWealth, #SustainableLeadership, #CloudReadyData, and #SmarterTrading.
Q1: As fintech in 2020 advances, how will trade automation, trade performance analytics, AI, and machine learning impact trading professionals?
Participants in the #RefinitivSocial100 LinkedIn discussion appeared confident that tech won’t replace human knowledge and expertise but instead augment it.
Bradley Leimer, the co-founder of Unconventional Ventures, pointed to how tech looms large in trading but is still arbitrated by humans: “Technology is already dominating trading — but the movements on which they make trades on are still primarily human-led.”
Dr Nafis Alam, who spends much of his time researching banking regulation, financial stability and corporate finance, highlighted the importance of human common sense:
“Technology can only complement human intellect. With the advent of technology in trading, professionals need to be equipped with solid trading fundamentals, and use common sense rather than depending too much on the tech-focused outcome.”
That said, however, the increasing prevalence of tech frees traders’ time for other things, as Kevin McPartland, Head of Market Structure and Technology Research at Greenwich Associates, told us: “We should think of these advancements not as a replacement for people, but as tools to help people be more informed, make better decisions, and focus on the highest value tasks.”
Q2: Will sustainable wealth be driven by data in 2020 and beyond?
On the ways data could be leveraged to enable sustainable development in the future, our respondents were positive.
Kai Grunwitz, who is a top influencer on cybersecurity, blockchain, and digital transformation, had this to say: “People invest while focusing on sustainability and ethics. This will be data-driven — leveraging aspects of AI here in the same way as in all other areas of the industry.”
Others pointed to how sustainability data is already being used to inform financial decisions, with this set to increase in the future.
According to Refinitiv Head of Sustainable Investing & Fund Ratings, Leon Saunders Calvert: “Sustainability-related data is on a journey to becoming a fundamental dataset in supporting and augmenting existing data sources for capital allocation decisions.”
While data can show us which businesses act ethically, it is also able to identify unethical companies.
Corporate governance expert David Doughty said: “In addition to enabling ESG investors to pick the winners — well run, ethical businesses — it will also enable, investors, suppliers, customers, and regulators to identify the badly run businesses which are causing harm on a global scale.”
Q3: Do you think customization and enhanced data tools reduce the requirements for the wealth advisor’s skillset?
Our experts emphasized the fact that data tools shouldn’t reduce the skillset requirements but transform them.
Alex Jiménez, Chief Strategy Officer for Extractable, said: “Enhanced tools should not reduce the requirements for a wealth advisor’s skillset. It should change the balance of skillsets.
“An advisor that relies on tools for their advice without understanding how the tools arrive at proposed solutions will ultimately give unsound advice.”
It portends a future where advisors will need knowledge of AI and machine learning to remain competitive.
“Rather than decrease a wealth advisor’s skillset, it will increase requirements. All the obvious stuff will be dealt with by AI and machine learning, leaving the more complex matters for a reduced number of higher-skilled wealth advisors,” added Dr Nafis Alam.
Q4: What will make the greatest impact on financial markets in 2020?
There was broad agreement that for all the potential for tech to transform finance, it was, like all things, at the mercy of politics:
“Trump re-elected or impeached, U.S./China trade wars, and Brexit will all impact financial markets in 2020 but also look out for an EU financial crisis and the start of the EU pensions crisis.” – David Doughty.
Bradley Leimer warned against the damaging effects of growing inequality:
“No amount of technology in this space will be as important as the ongoing shift of wealth that has been occurring — in both directions depending on the geography — but very acutely in the United States.”
Q5: What will be the biggest hurdles to the adoption of AI in financial services in 2020 and beyond?
Nick Kerigan, who has almost 20 years of experience in payments and banking, began by warning of the issues with explicability and productionization:
“Explicability of (say) decisions is vital in any B2C situation. However, a hurdle that few are talking about is the ability to productionize. It’s a big challenge to plug new machine learning and AI models into existing core banking and payments systems.”
Refinitiv data scientist Mahesh Kulkarni pointed to data variety and quality, while techUK President Jacqueline de Rojas highlighted the challenges of outdated legacy systems, talent shortages and culture.
She said: “Many banks still have legacy systems for IT and data infrastructures that often aren’t optimized for data-driven technologies. It is both difficult to find the right diverse talent to innovate with AI and also to address cultural resistance born out of a lack of understanding of the technology.”