FUTURE OF FINTECH - PART 2

FUTURE OF FINTECH - PART 2

In 2018 alone, over 22,000 businesses around the world borrowed more than $380 billion from crowdlending services. 

Disruptive business models are often powered by alternative financing.

In Part 1 of the Future of Fintech, I discussed how mobile is redefining money and banking and shared some of the dramatic transformations in the global remittance infrastructure.

In this blog, we’ll discuss:

  1. Peer-to-peer lending
  2. AI financial advisors and robo traders
  3. Seamless transactions

Let’s dive right back in…

Decentralized Lending = Democratized Access to Finances 

 Peer-to-peer (P2P) lending is an age-old practice, traditionally with high risk and extreme locality. Now, the P2P funding model is being digitized and delocalized, bringing lending online and across borders. 

Zopa, the first official crowdlending platform, arrived in the United Kingdom in 2004. Since then, the consumer crowdlending platform has facilitated lending of over 3 billion euros ($3.5 billion USD) of loans .

Person-to-business crowdlending took off, again in the U.K., in 2005 with Funding Circle, now with over 5 billion euros (~5.8 billion USD) of capital loaned to small businesses around the world. Now, in 2018 alone, over 22,000 businesses around the world borrowed over $380 billionfrom crowdlending services.

Crowdlending next took off in the United States in 2006, with platforms like Prosper and Lending Club. The U.S. crowdlending industry has boomed to $21 billion in loans, across 515 thousand loans.

Let’s take a step back… to a time before banks, when lending took place between trusted neighbors in small villages across the globe. Lending started as peer-to-peer transactions. 

As villages turned into towns, towns turned into cities, and cities turned into sprawling metropolises, neighborly trust and the ability to communicate across urban landscapes broke down. That’s where banks and other financial institutions came into play — to add trust back into the lending equation. 

With crowdlending, we are evidently returning to this pre-centralized-banking model of loans, and moving away from cumbersome intermediaries (e.g. high fees, regulations, and extra complexity). 

Fueled by the permeation of the internet, P2P lending took on a new form as ‘crowdlending’ in the early 2000’s. Now, as blockchain and artificial intelligence arrive on the digital scene, P2P lending platforms are being overhauled with transparency, accountability, reliability and immutability.

Artificial Intelligence Micro Lending & Credit Scores

We are beginning to augment our quantitative decision-making with neural networks processing borrowers’ financial data to determine their financial ‘fate’ (or, as some call it, your credit score). Companies like Smart Finance Group (backed by Kai Fu Lee and Sinovation Ventures) are using Artificial Intelligence to minimize default rates for tens of millions of microloans.

Smart Finance is fueled by users’ personal data, particularly smartphone data and usage behavior. Users are required to give Smart Finance access to their smartphone data, so that Smart Finance’s artificial intelligence engine can generate a credit score from the personal information. 

The benefits of this AI-powered lending platform do not stop at increased loan payback rates -- there’s a massive speed increase as well. Smart Finance loans are frequently approved in under 8 seconds. As we’ve seen with other artificial intelligence disruptions, data is the new gold. 

Digitizing access to P2P loans paves the way for billions of people currently without access to banking to leapfrog the centralized banking system -- just as Africa bypassed landline phones and went straight to mobile. Leapfrogging centralized banking and the credit system is exactly what Smart Finance has done for hundreds of millions of people in China.

Blockchain Backed Crowdlending

As artificial intelligence accesses even the most mundane mobile browsing data to assign credit scores, blockchain technologies -- particularly immutable ledgers and smart contracts -- are massive disruptors to the archaic banking system, building additional trust and transparency on top of current P2P lending models. 

Immutable ledgers provide the necessary transparency for accurate credit and loan defaulting history. Smart contracts executed on these immutable ledgers bring the critical ability to digitally replace cumbersome, expensive third parties (like banks), allowing individual borrowers or businesses to directly connect with willing lenders.

Two of the leading blockchain platforms for P2P lending are ETHLend and SALT Lending. 

ETHLend is an Ethereum-based decentralized application aiming to bring transparency and trust to P2P lending through Ethereum network smart contracts. 

Secure Automated Lending Technology (SALT) allows cryptocurrency asset holders to use their digital assets as collateral for cash loans, without the need to liquidate their holdings, giving rise to a digital-asset-backed lending market.

While blockchain poses a threat to many of the large, centralized banking institutions, some are taking advantage of the new technology to optimize their internal lending, credit scoring, and collateral operations.

In March 2018, ING and Credit Suisse successfully exchanged 25 million euros using HQLA-X, a blockchain-based collateral lending platform. 

HQLA-X runs on the R3 Corda blockchain -- a platform designed specifically to help heritage financial and commerce institutions migrate away from their inefficient legacy financial infrastructure.

Blockchain and tokenization are going through their own fintech and regulation shakeup right now. In a future blog, I’ll discuss the various efforts to more readily assure smart contracts, and the disruptive business model of security tokens and the U.S. Securities and Exchange Commission.

Parallels to the Global Abundance of Capital

The abundance of capital being created by the advent of P2P loans closely relates to the unprecedented global abundance of capital.

Initial Coin Offerings (ICOs) and crowdfunding are taking a strong stand in disrupting the $164 billion venture capital market. The total amount invested in ICOs has risen from $6.6 billion in 2017 to $7.15 billion USD in the first half of 2018. Crowdfunding helped projects raise more than $34 billion in 2017, with experts projecting that global crowdfunding investments will reach $300 billion by 2025.

In the last year alone, using ICOs, over a dozen projects have raised hundreds of millions of dollars in mere hours. Take Filecoin, for example, which raised $257 million in only 30 days; its first $135 million was raised in the first hour. Similarly, the Dragon Coin project (which itself is revolutionizing remittance in high-stakes casinos around the world) raised $320 million in its 30-day public ICO. 

Some Important Takeaways…

  • Technology-backed fundraising and financial services are disrupting the world’s largest financial institutions -- anyone, anywhere, at anytimewill be able to access the capital they need to pursue their idea.
  • The speed at which we can go from "I've got an idea" to "I run a billion-dollar company" is moving faster than ever.
  • Following Ray Kurzweil’s Law of Accelerating Returns, the rapid decrease in time to access capital is intimately linked (and greatly dependent on) a financial infrastructure (technology, institutions, platforms, and policies) that can adapt and evolve just as rapidly.

This new abundance of capital, requires financial decision-making with ever-higher market prediction precision. That’s exactly where artificial intelligence is already playing a massive role.

Artificial Intelligence, Robo Traders and Financial Advisors

 On May 6, 2010, the Dow Jones Industrial Average suddenly collapsed by 998.5 points (equal to 8 percent, or $1 trillion). The crash lasted over 35 minutes and is now known as the ‘Flash Crash’. While no one knows the specific reason for this 2010 stock market anomaly, experts widely agree that the Flash Crash had to do with algorithmic trading

With the ability to have instant, trillion-dollar market impacts, algorithmic trading and artificial intelligence are undoubtedly ingrained in how financial markets operate.

In 2017, CNBC.com estimated that 90 percent of daily trading volume in stock trading is done by machine algorithms, and only 10 percent is carried out directly by humans.

Artificial intelligence and financial management algorithms are not only available to top Wall Street players.

Robo-advisor financial management apps, like Wealthfront and Betterment, are rapidly permeating the global market. Wealthfront currently has $9.5 billion in assets under management, and Betterment has $10 billion.

Artificial intelligent financial agents are already helping financial institutions protect your money and fight fraud. A prime application for machine learning is in detecting anomalies in your spending and transaction habits, and flagging potentially fraudulent transactions.

As artificial intelligence continues to exponentially increase in power and capabilities, increasingly powerful trading and financial management bots will come online, finding massive new and previously lost streams of wealth. 

How else are artificial intelligence and automation transforming finance? 

Disruptive Remittance and Seamless Transactions

When was the last time that you paid in cash at a toll booth? How about for a taxi ride? 

EZ-Pass, the electronic tolling company implemented extensively on the East Coast, has done wonders to reduce traffic congestion and increase traffic flow. 

Driving down I-95 on the East Coast of the United States, drivers rarely notice their financial transaction with the state’s tolling agencies. The transactions are seamless.

The Uber app enables me to travel without my wallet. I can forget about payment on my trip, free up my mental bandwidth and time for higher-priority tasks. The entire process is digitized and, by extension, automated and integrated into Uber’s platform. (Note: This incredible convenience manytimes causes me to accidentally walk out of taxi cabs without paying!).

In January 2018, we saw the success of the first cutting-edge, AI-powered Amazon Go store open in Seattle, Washington. The store marked a new era in remittance and transactions -- gone are the days of carrying credit cards and cash, and gone are the cash registers. And now, on the heals of these early ‘beta-tests’, Amazon is considering opening as many as 3,000 of these cashierless stores by 2023.

Amazon Go stores use AI algorithms that watch various video feeds (from advanced cameras) throughout the store to identify who picks up groceries, exactly what products they select, and how much to charge that person when they walk out of the store. It’s a grab and go experience. 

Let’s extrapolate the notion of seamless, integrated payment systems from Amazon Go and Uber’s removal of post-ride payment to the rest of our day-to-day experience.

Imagine this near future:

  • As you near the front door of your home, your AI assistant summons a self-driving Uber that takes you to the Hyperloop station (after all, you work in L.A. but live in San Francisco).
  • At the station, you board your pod, without noticing that your ticket purchase was settled via a wireless payment checkpoint.
  • After work, you stop at the Amazon Go, pick up dinner -- your virtual AI assistant passes your Amazon account information to the store’s payment checkpoint, as the store’s cameras and sensors track you, your cart and charge you auto-magically.
  • At home, unbeknownst to you, your AI has already restocked your fridge and pantry with whatever items you failed to pick up at the Amazon Go.

Once we remove the actively transacting aspect of finance, what else becomes possible?

Top Conclusions 

Extraordinary transformations are happening in the finance world.

We’ve only scratched the surface of the fintech revolution.

All of these transformative financial technologies require high-fidelity assurance, robust insurance, and a mechanism for storing value. 

I’ll dive into each of these other facets of financial services in future blogs.

For now, thanks to coming global communication networks being deployed on 5G, Alphabet’s LUNE, SpaceX’s Starlink and OneWeb, by 2024, nearly all 8 billion people on Earth will be online.

Once connected, these new minds, entrepreneurs, and customers need access to money and financial services to meaningfully participate in the world economy.

By connecting lenders and borrowers around the globe, decentralized lending drives down global interest rates, increases global financial market participation, and enables economic opportunity to the billions of people who are about to come online.

We’re living in the most abundant time in human history -- and fintech is just getting started.

Join Me

(1) A360 Executive Mastermind: This is the sort of conversation I explore at my Executive Mastermind group called Abundance 360. The program is highly selective, for 360 abundance and exponentially minded CEOs (running $10M to $10B companies). If you’d like to be considered, apply here.

(2) Abundance Digital Online Community: I have also created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance Digital. This is my ‘onramp’ for exponential entrepreneurs – those who want to get involved and play at a higher level. Click here to learn more.

 

Luis R. Balderas

CEO @Vinobreria Be strong, confident, assertive, respectful, responsible, loyal, protector, provider, learner, mentor and leader.

5 年

Benjamín Balderas Quiroz

Manish Dhawan

Co-founder of AspiRise, SporteeGo & YuVik. Passionate about AI, sports, wellness, aviation and finance. Building ventures that inspire and transform.

6 年

Will be interesting to see how artificial intelligence will enable better underwriting decisions, also the possibility of unintended bias. Regulators are going to grapple with these issues and will need to work on improving their own understanding of the relevant technologies, the implications for financial services, and the ways in which those technologies fit–or don’t–within existing regulatory frameworks.

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Chuck Williams MBA, PMP, CISSP, GSLC, CSSLP, MCSE, CRISC, CDPSE

Veteran & intrapreneur w/ over quarter-century of leading large-scale 1st-in-enterprise efforts for Fortune 100, NFPs, Military

6 年

If 90% of trading is automated, there are opportunities because humans are typically more unpredictable than an AI using a predictive model.

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Anna Carolina Campos, CFP?

Author, Lecturer & Entrepreneur

6 年

Carlos Campos 2 parte do texto que falamos semana passada. Vale a leitura!

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