How Does AI and Regulation Play Into Fintech?
Chalmers Brown — September 8, 2017 — September 8, 2017
geralt / Pixabay
Fintech, or Financial Technologies, has proven that it’s more than just an industry buzzword. Fintech represents many technologies that have already disrupted traditional financial services. One of Fintech’s advances is enhancing everything from mobile payments, money transfers, loans, fundraising, and asset management. According to a report by Accenture, investment in Fintech has jumped from $ 930 million in 2008 to more than $ 12 billion by early 2015.
There’s no question that Fintech is here to stay. But are two important components that are playing a role in where exactly Fintech is headed; AI and regulation.
AI and Regulation are Paving The Way For Fintech
Artificial Intelligence is all the rage right now in Silicon Valley. In fact, funding to AI startups reached record highs in 2016. While AI is currently being used by a variety of businesses, it’s being specifically used by businesses in these nine categories:
1. Credit Scoring / Direct Lending
Companies in this category use AI for credit scoring and lending applications.
2. Assistants / Personal Finance
Companies in this category rely on AI chatbots and mobile app assistant applications in order to monitor personal finances.
3. Quantitative & Asset Management
Companies in this category employ AI algorithmic trading and investment strategies or tools.
4. Insurance
Companies in this category use AI to quote and insure.
5. Market Research / Sentiment Analysis
Companies within this category use AI for research and to measure sentiment.
6. Debt Collection
Companies in this category use AI to improve creditor collection of outstanding debt through personalized and automated communication.
7. Business Finance & Expense Reporting
Companies in this category use AI to improve basic business accounting.
8. General Purpose / Predictive Analytics
Companies in this category use AI for general purpose semantic and natural language applications as well as for broadly applied predictive analytics.
9. Regulatory, Compliance, & Fraud Detection
Companies in this category use AI to detect fraudulent and abnormal financial behavior, and/or to improve general regulatory compliance matters and workflows.
While this technology may sound revolutionary, it’s actually been around for years in industries like trading.
“There are two types of algorithms used in trading today,” says Juergen Schmidhuber, an AI researcher of more than 20 years. The New York Times called Mr. Schmidhuber the father of AI in November 2016.
“There are simple programs pre-wired to do certain things that the traders have identified, for instance. Little tricks that enable it to propose a price for a certain share. Then, of course there are little [systems] that are just going through a bunch of rules. Depending on the risk profile of the client, they make certain decisions according to not very intelligent self-learning mechanisms.”
“On the other hand, you have systems that have been used since the 1990s that learn from experience to become better prediction machines,” adds Schmidhuber.
“These use neural networks to predict behavior, financial indicators and so on. The hope is you have a system that works better than those of your competitors and detects patterns that the others don’t see.”
Where is AI Headed
However, as technology has advanced, AI has not become more effective. It’s also being embraced by more businesses, countries, and investors. For instance, Fintech investment in China more than tripled to $ 10 billion from 55 deals in 2016. This representing 90% of fintech ventures in the Asia-Pacific region.
“Many of China’s financial service companies are making investments in fintech companies and exploring cutting-edge solutions such as blockchain technology,” said Albert Chan. Mr Chan is Accenture’s managing director of financial services in China.
After China, the U.S. is second in Fintech funding with $ 6.2 billion. Funding is also rising in Japan and Europe.
The reason? “Smarter computers, algorithms and dedicated AI systems are a fintech dream. Faster decision-making and deeper learning (recognising, for example, predictors of financial turbulence) are obvious and huge boons to financial organisations,” writes Rich Wordsworth for Wired UK.
“The drive to eliminate human fallibility has also made artificial intelligence (AI) driven to the forefront of research and development. Its applications range from sorting what gets shown on your social media newsfeed to self-driving cars,” adds Nikolai Kuznetsov for The Next Web.
“It’s also expected to have a major impact in Fintech due to potential of game changing insights that can be derived from the sheer volume of data that humanity is generating.
Enterprise AI Regulations
Enterprising ventures are banking on it to expose the gap in the market that has become increasingly small due to competition.”
“I think the biggest change is that people are going to receive financial help before they even know it,” says WIRED Money 2017 speaker and CEO of online investment management company Nutmeg Nick Hungerford.
“It’s a combination of big data and artificial intelligence. We’re going to be able to be more intelligent about people’s spending habits, their health, their lifestyles. [We’re] going to get more effective at predicting what they’re going to need for different scenarios of spending and saving.
AI predicts when people are likely to get married, when you are likely to have a baby, etc. So in five years, we should be really good at giving people financial advice before they even realise they need it,” says Hungerford.
AI is also being experimented with traditional financial institutions.
“AI driven workflows will be the only way for traditional banks to leapfrog the competition from new, nimble breed of banks built around innovative technology such as Blockchain and business models such as peer-to-peer payments,” says Ramesh Mahalingam, CEO and Founder at Vizru.
“The emerging new shareconomy demands banks to reassess their role where products and services need to be increasingly personalized. Using real-time data can only be delivered by AI-driven digital ecosystems. AI systems dynamically and continuously learn, reason and solve problems in real-time.
“AI driven workflows will play an instrumental role for banks in the future to deliver immersive customer experience.”
Simply put, innovations in Fintech are being driven by the advancements made in AI.
Regulation Is Holding Fintech Back
When it comes to financial services, there will be regulations – especially after the passage of Dodd-Frank following the financial crisis. While AI is being used to assist regulations and ensure that businesses are compliant, there is a fear that regulations are actually holding back Fintech.
According to a report from BI Intelligence, “The US regulatory environment is holding back fintechs and hindering their chances of success.” This is mainly because regulatory system in the US involves several players at the federal level, as well as a regulator for each state.
“This complexity not only makes the US regulatory environment harder for fintechs to navigate in the first place, but it’s a major barrier to the development of a coherent fintech policy.”
As a result, US fintechs are not able to scale and are falling behind overseas competitors in Europe. To make matters worse, a coherent fintech regulatory policy is still in the distant future.
The Office of the Comptroller of the Currency (OCC) is proposing that fintechs apply for charters as “special purpose national banks.”
This controversial charter, as explained by Nik Milanovic in TechCrunch, means that fintechs “would be subject to minimum requirements around governance structure, capital, liquidity, compliance, financial inclusion and continuity strategy.”
Interestingly, the most vocal opponents to this charter are state regulators. They view this “as a broad overreach of federal authority.”
This proposal may not impact for commercial banks. It could however prevent innovation from Fintech startups because:
1. Fintechs are too diverse to be included in a one-size-fits-all charter generally drafted to legitimize deposit-holding institutions. In other words, payday lenders could be lumped together with insurance tech.
2. “The charter could narrow the gap between fintechs and banks, allowing fintechs to compete nationally instead of applying for state-by-state licenses, it could also lead to a ‘thinning of the herd’ by being too cumbersome or expensive for young companies.”
3. There’s also the possibility that fintechs could be “written into a narrower and narrower regulatory box, increasing the chances they’re shut down for benign compliance missteps.”
4. The OCC may not protect fintechs from other regulators who may have different sets of rules.
Since we currently live in an age of de-regulation, these fears may not last much longer. However, other countries, such as China and the UK, are focusing on Fintech regulations.
Unlike their American Counterparts, these regulations may only hinder growth temporarily. This is because they’re looking to use technology to innovate the Fintech industry through Regtech.
RegTech: Where AI and Regulation Collide
RegTech has emerged as the technology that could address these possible regulation and compliance hurdles. Technology like AI can automate compliance awareness, monitor risk and compliance in real-time, and to automatically report to regulators.
The Financial Conduct Authority, an independent U.K. financial regulatory body, has been exploring the possibility of using artificial intelligence (AI) and machine-learning tools to enforce regulatory compliance.
“We are looking at the extent to which we can make parts of our handbook initially machine-readable. Then we want them fully machine-executable.
Effectively converting, probably initially our regulatory reporting rules, into truly unambiguous rules. The machines can interpret and implement directly,” said Nick Cook, the FCA’s head of data and information operations.
“The idea being that we can put out rules which are written manually in ways that can be fully and unambiguously interpreted by machines,” he added.
Where is AI and Regulation Headed?
According to a report published by the University of Hong Kong, RegTech has been identified as a field that is capable of addressing risk in “real time” and increasing the efficiency of compliance.
“Regtech to date has been focused on the digitization of manual reporting and compliance processes. For example it can be used in the context of “know-your-customer requirements,” said the U of Hong Kong.
“This offers tremendous cost savings to the financial services industry and regulators. However, the potential of regtech is far greater.
Regtech has the potential to enable a close to real time and proportionate regulatory regime that identifies and addresses risk. It can also facilitate far more efficient regulatory compliance.”
For example, Transferwise and World Remit have lowered the cost of remittance down to around 1% from rates of around 16% for African countries.
The possibilities in RegTech can also extend beyond finances. Human resources, for example, could use the technology for onboarding and employee benefits.
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