I had the opportunity this week to participate in roundtable discussion with finance leaders on “Innovations in Finance” at the Fintech Rising Summit. While 2017 was a big year for the fintech space, there were four major takeaways from our roundtable discussion on Wednesday:
Machine learning and algorithms are driving efficiencies and validating investment opportunities.
Machine learning or an algorithmic approach to finance is actually not a revolutionary method to finance; banks and funds have been using algorithmic underwriting processes for decades. The exciting innovation is the application of data to these algorithms. With more robust data sets and refined algorithms, machine learning can now provide us with more accurate analysis to challenge assumptions and assess risk. We’re seeing this trend in all aspects of finance.
It’s going cost $90 Trillion over the next 15 years to meet our clean energy goals but very few institutions have invested in this sector. To meet our global clean energy goals, we need to empower institutional investors with information that helps them understand clean energy investments and the underlying risk. Machine learning can play a big part in achieving this.
Fintech is converging with traditional banks and financial institutions.
Fintech has fully arrived on Wall Street with banking giants like Goldman Sachs and Royal Bank of Canada (RBC) entering the space. Just last month Goldman Sachs announced plans for generating as much revenue from online consumer loans as from buying and selling securities. RBC announced today the automation of personal finance and budgeting capabilities within their mobile app powered by AI.
While startups might have initiated the disruption, incumbent institutions are now embracing fintech to drive efficiencies and gain an edge.
Fintech is about technology and data, and less about crowdfunding and marketplace lending.
While fintech may have started as a space for individuals and companies to raise money online, it has rapidly evolved into a category that is changing all aspects of finance. With advancements in machine learning, payments, and personal banking, tech and data make the entire finance universe more streamlined, transparent and accurate.
This is important to CleanCapital, we deliver capital to capital-inefficient segments of the clean energy market. We leverage data and technology to attract more investors to clean energy, and accelerate clean energy adoption.
Innovations like blockchain and cryptocurrency are still in their infancy but have large potential for disruption in finance (and energy too).
Blockchain and cryptocurrency will continue to grow. Blockchain’s applicability appears more near term as it is being used for smart contracts, and you can see the use of smart contracts being applied to financial transactions. My co-panelist, Oren Bass and the team at Pave are using blockchain to better analyze credit. Just like machine learning is reducing inefficiencies in the underwriting process, blockchain can help connect parties in financial transactions more efficiently and transparently.
Beyond finance, blockchain is playing a role in securing our energy grid from cyber attacks. Last month, the Department of Energy announced its intention to leverage blockchain technology to sure up grid resiliency by providing highly auditable and structured data trails which would allow for easy and early detection of fraudulent activity and potentially thwart cyber attacks by making the grid essentially unhackable.
There are no limits to the potential for technology to eliminate friction in financial transactions, and for data to improve deal evaluation and underwriting. As CleanCapital accelerates clean energy by applying some of these innovations, it was amazing to see the numerous data and technology solutions that are on the horizon.