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Mining After Ethereum 2.0

Posted on September 12, 2022September 12, 2022 by Jean Chalopin

In our last article we introduced the Ethereum Merge and its potentially profound impact upon the world of investing–whether for traditional or digital assets. Bellatrix on September 6th paved the way for the final merge to likely happen around September 15th through the second stage–Paris. With this comes the transition from proof of work (PoW) to proof of stake (PoS). What will mining after Ethereum 2.0 look like?

The proof of work protocol entails two components for its blockchain: “miners” and work. Validators, dubbed miners, work to solve hash puzzles before adding a subsequent block to a blockchain. Each block contains a set of transaction data to be added to the immutable public ledger than is any one blockchain.

Mining after Ethereum 2.0 actually refers to “staking,” or the practice of validators staking (read: depositing) their assets for the benefit of a blockchain’s protocol. Proof of stake uses a modified form of random selection favoring integrous stakers with larger deposits while not disenfranchising those holding smaller deposits.

This article delves into proof of stake, Ethereum 2.0, and the larger impact of staking. Let’s get into it.

Proof of Stake

A younger invention than the proof of work arriving over a decade ago with Satoshi Nakamoto’s Bitcoin, it shifts the onus from energy-intensive work and computation to at-risk deposits and integrity.

Ethereum’s PoS introduces a complex system focusing on the character of its validators (stakers). To participate, each validator must first deposit 32 ETH (ether) into a smart contract and operate using three different pieces of software: an execution client, a consensus client, and validator.

Once their validation account is active, validating users receive new blocks from peers operating on the Ethereum network. The blocks’ transactions are “re-executed,” and the validator checks the block signatures to ensure they’re valid. The validator finally sends a vote–referred to as an attestation–in favor of each new block across the network.

PoS also introduces a unique feature carrying potential benefits for scaling: The timing of adding blocks remains fixed. Simply put, one slot occurs every 12 seconds and an epoch refers to 32 slots.

The protocol randomly selects one validator per slot, to function as a block proposer. The validator therefore remains responsible for sending out new blocks to the network. And with every slot, a committee of validators–randomly chosen–votes on the validity of the new block.

Source: Finematics

Mining After Ethereum 2.0

In short, mining ceases to exist in favor of staking. PoW ensures validator integrity through the work they must complete in solving the next hash puzzle required for adding the next block. PoS ensures integrity through the extraordinary financial cost in engaging in dishonest behavior.

PoS validators lose out on ETH rewards if they fail to validate when selected. In addition, their existing stake is up for removal if they behave dishonestly: namely proposing multiple blocks for a single slot or sending contradictory attestations. The penalties increase gradually the longer a validator fails to provide honest attestations–leading to outright ejection from the Ethereum network after 36 days.

Any attack–even coordinated–would therefore be extremely costly for the criminal party given that the minimum staking amount is 32 ETH.

A 51% attack to propose an entirely separate blockchain of transaction data, feared in the PoW domain, requires billions upon billions in dollar equivalent of staked ETH. However, the Ethereum community would recognize a single bad actor or group of actors trying to propagate this false chain. They could then mount a counterattack by raising alarms, at which point the network would likely destroy all the staked ETH of the false chain.

Integrity is ensured through the heavy economic cost and the collective voice of honest validators.

The Benefits of Staking

Previously, we’ve touched upon the environmental benefits of switching to staking in a world ravaged by climate change. Ethereum’s energy usage would decrease by approximately 99.95%.

However, there are number of additional benefits:

Passive income. Staking enables retail individuals in securing the Ethereum network, even from a laptop. Staking pools collate ETH and allow individuals to stake without having the required 32 ETH.
Increased decentralization. Economies of scale happen with PoW as institutions have the cash balances necessary to purchase dedicated, intensive “rigs.”
Economic security. PoS expressly uses staked (locked) deposits, which are held liable for destructing provided dishonest behavior.

There are some notes to consider, however, before entering into staking:

PoS is younger and lesser-known than PoW.
PoS is complex as it locks the addition time of new blocks and consistently monitors the actions of validators.
A validator needs to use three pieces of software.

Closing Thoughts

PoS opens the door to the crypto universe for all individuals or entities, large or small, while removing the economic incentives of bad actors. PoW works from a security perspective while ironically encouraging some centralization and excluding the vast majority of potential validators as it matures.

Retail investors now enjoy several solid, regulated crypto exchanges for entering into crypto without jeopardizing their security. In tandem, yields from traditional bond investing pales alongside staking’s potential return. This spells opportunity for forward-looking banks embracing tomorrow.

Democracy and opportunity remain the heart of cryptocurrency. Ethereum’s PoS represents an invention furthering that ideal to anyone with an internet connection.

Disclaimer: The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech, and entertainment. Mr. Chalopin is Chairman of Deltec International Group, www.deltecbank.com.

The co-author of this text, Conor Scott, CFA, has been active in the wealth management industry since 2012, continuously researching the latest developments affecting portfolio management and cryptocurrency. Mr. Scott is a Freelance Writer for Deltec International Group, www.deltecbank.com.

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees. This information should not be interpreted as an endorsement of cryptocurrency or any specific provider, service, or offering. It is not a recommendation to trade.

When Is the Ethereum Merge?

Posted on September 9, 2022September 9, 2022 by Jean Chalopin

After some delays and much anguish, the upcoming “Ethereum Merge” is set to happen. Bellatrix, the first stage of this process, happened on September 6th. Yet one question on millions of minds across the world remains: When is the Ethereum merge?

Paris, the second and final stage, is set to be complete by the next week, likely around September 15th. After this French foray, Ethereum – the world’s second-largest currency following Bitcoin – shall fundamentally change from its very core. Meaning, its blockchain “proof of” protocol shall shift from Bitcoin’s original proof of work to the new, more centralized, and extremely energy efficient, proof of stake.

The waves of change coming from the behemoth that is Ethereum shall not only shape the future of cryptocurrencies, but of finance itself in a time of “Web3” as retail investors across the world have joined in through massive crypto exchanges like Binance or Coinbase. First, let’s get into the basics of Ethereum, the jargon, and then some of the changes we can all expect.

How Blockchain Works

When investors and crypto enthusiasts throw around the term “blockchain,” they’re referring to the engine driving a coin itself. It’s an immutable public ledger, decentralized and democratized.

In contrast, a centralized ledger of traditional banks or gambling parlors retained this information, but privately. And therein lies the problem – trust. This method forced consumers to trust an institution’s efficiency, integrity, and infallibility.

Instead, the block of each blockchain contains records of transactions for time immemorial, decentralized for the benefit and trust of the general public. The same public maintains any blockchain’s integrity through what’s known as a consensus mechanism.

The Consensus Mechanism

Unlike a centralized ledger, a consensus mechanism follows the tradition of a democratic parliament. A simple majority (51% or more) changes the accepted blockchain, or the blockchain which everyone agrees is true.

Yet with the “miners” or “stakers” (validators) across the world incentivized to take part in the blockchain’s validation process by way of additional income, a single bad actor would need an absurd amount of energy and processing power.

This formed the backbone of proof of work’s astounding success, although the energy consumption feels crippling in a time of rampant global warming and record heat waves. Proof of stake solves this issue.

Proof of Stake

This new consensus mechanism requests that crypto holders deposit their own digital assets as collateral for the opportunity to have their transaction record (their copy of the blockchain to date) used by the blockchain as parts of its goings on. In return, the holders of those deposits, or staked assets, receive rewards.

Proof of stake relies upon mathematical randomness and the power of groups. Stakers are selected randomly, although higher stake amounts add to any one staker’s chances. Therefore, the mechanism requires multiple stakers to verify any one transaction before it becomes blockchain canon.

When Is the Ethereum Merge?

Bellatrix served to prepare Ethereum for its merge by acting as its “hard fork.” This translates into a radical change requiring all Ethereum actors and users to upgrade to the latest protocol software.

Specifically, it prepared the consensus layer of the cryptocurrency for a merge with its execution layer. That merge is what we call “the Ethereum merge.”

Paris occurs when the Terminal Total Difficulty (TTD) reaches 58,750,000,000,000,000,000,000. This figure represents the cumulative total difficulty of all mined Ethereum blocks under the proof of work consensus mechanism.

After hitting this difficulty, mining, or solving the next hash puzzle for the next block, becomes impossible. And thus proof of stake takes over like a default recourse.

So to answer the question – when is the Ethereum merge? – predictions suggest September 15th on the dot.

Bottom Line

Shifting to proof of stake is necessary due to crypto’s increasing regulation in a world suffering from overheating. Critics argue that the difficult hash puzzle remains the most secure blockchain invention to date. However, a stake-based mechanism succeeds in getting the job done while eliminating over 99.9% of the current energy usage and laying the groundwork for a similarly massive decrease in transaction fees through another process dubbed “sharding.”

In our next article we will describe the benefits of staking and the world changing benefits of the second largest cryptocurrency switching to it. These implications stretch from an increased price valuation to the removal of all mediums of exchange consuming far too much energy, be they crypto or fiat.

Artificial Neural Networks for Finance

Posted on September 5, 2022September 5, 2022 by Jean Chalopin

Back in the early days of data science, before it was even called data science, any financial applications handled by programs were called Expert Systems. These were a domain of AI that was developed using the knowledge of a “Human Expert.” The expert’s knowledge was used to create a set of programming rules to assist the algorithm with making decisions.

At its most basic level, an Expert System would look like this:

If the price of asset “A” when compared to asset “B” exceeds X%, then sell asset A (or buy asset B or do both), or:

If a prospective borrower has a credit score below 591, do not lend them anything.

Such expert systems have been successfully used in fraud detection, medical diagnosis, and even when prospecting for minerals. However, there is a major limitation to them, which is that they require full information to be provided to them as an input and this fact means that they will either perform poorly or not at all with uncertainty.

Financial applications primarily deal with the prediction of future events based on the results of past data. This is the reason that Artificial Neural Networks have become so popular in recent times, especially in the finance industry, because they have a better ability to handle uncertainty when compared to expert systems. When we consider various scenarios that involve predictions, we find a few primary areas enhanced by using artificial neural networks (ANNs):

1. Predicting the movement of the stock market, both indexes, and individual stocks

2. Predicting loan application underwriting and repayment success

3. Finding suitable credit card clients

In this article, we will explain the basics of artificial neural networks and go deeper into the applications where artificial neural networks can be the most successful and beneficial for the financial, banking, and insurance industries. Finally, we will finish with an example outline of an ANN for making credit decisions.

Artificial Neural Networks in Brief

ANNs are designed to mimic the actions of biological neural networks seen in life forms with nervous systems and brains such as humans.

Image courtesy of Quora

The biologic nerve cell will take the chemical input into its dendrites, and if the signal is sufficient, then it will transfer this signal down its axon to its axon terminals, where it produces its own chemical signal to go to the next nerve cell.

The artificial neuron (sometimes called a perceptron) will take input and evaluate it with a bias (or summing) function. The bias function decides what to do with the result, sending it on or not, and to what degree the message will be transferred.

This perceptron was created by Frank Rosenblatt back in the 1950s and was used by the US Navy for image recognition tasks as well as many other applications.

The ANN expands on the perceptron and consists of many interconnected neurons all performing their summing functions with the data inputs. Each of the following circles is a single artificial neuron.

Image courtesy of techvidvan.com

The ANN is made up of input and output layers, and a network will have at least one hidden layer between these, but can have dozens of hidden layers with numerous neurons in each layer depending on the model.

The summing functions for each neuron (colored circles above) will have their own weights and use input data coming in from the left and are connected to the next layer to the right, where they send their decision results. Information is stored in the weights of the connections between the neurons. As an ANN is “trained,” the weights are what changes to improve the results that the model is providing as its output.

This example is a “feed-forward architecture” and the most commonly used in ANN applications. There are other types of neural networks that are used in specific applications where they perform better.

ANNs give the user the ability to utilize the data available fully and to determine the structure and parameters of a model without restrictive modeling assumptions.

Artificial Neural Network Applications

ANNs are especially appealing in finance, banking, and insurance because there is an abundance of high-quality data available for these fields. This data means that there are plenty of inputs, and before ANNs, a lack of testable financial models to deal with all this data.

Predicting Stock Movements

The prediction of stock market indices and specific stock values are handled by ANN using the vast supply of historical data and then predicting based on several parameters. The accuracy of the prediction is enhanced by the choice of the variables and the information that is provided during the training process.

It can be further improved with an ANN structure that has more hidden layers and more training variables. One group attempted to predict the NASDAQ stock exchange movement and found that a network with three hidden layers, consisting of a configuration of 20-40-20 neurons in the hidden layers, the team had an optimized network and a resulting accuracy of 94.08%.

While there are other types of neural networks, these types of feed-forward networks are the most widely used because they offer generalization abilities and can be implemented easily.

Searching for Credit Card Customers

Some credit card companies are using ANNs to decide whether to grant credit card applications. The underwriting process uses the analysis of past failures to make current decisions based on the past experience of other card holders.

All banks that are in the credit card business wish to obtain an ideal customer who will help them remain profitable. If the client does not spend much with their credit card or uses the revolving line of credit, then that customer is not profitable. This non-profitable customer will have a per card revenue much lower than the per card cost, and the result will be a low breakeven percentage.

A group of researchers used an artificial neural network to approach this problem and more accurately predict ideal customers. This study used values called eigenvalues to find the lowest error rates for deciding on the best customers. After several rounds of testing, there were 14 eigenvalues that had the lowest error rates identified and settled on when choosing the most suitable customers.

This process eliminates instances where credit cards are issued to customers who have no credit card needs, and it gives the bank more meaningful questions to ask on a credit application to better identify the ideal customer.

This is now broadening beyond the yes-no approval decision and expanding to the amount of credit that is being provided to customers who are approved.

Evaluating Loan Applications

Financial institutions will provide loans to their clients for different reasons, and these decisions are based on various factors. ANNs can be employed to aid in the underwriting process, deciding whether to approve or decline the loan application.

Any loaning institution will want to minimize its default rate for loan applications and maximize its returns on the loans they issue. A research group was able to test the accuracy of an ANN in predicting the success of loan recovery, and they found an accuracy of 92.6%.

Additionally, their error rates for Type I (making a bad loan) and Type II (rejecting a good loan) errors were 6.5% and 8.2%, respectively. The failure rates that have been seen for loans approved using ANNs are lower than some of the best traditional methods.

Other Applications

Beyond those applications listed above, ANNs can be applied to several valuable use cases:

· Forex price predictions

· Futures movements and pricing

· Bond ratings

· Prediction of business failures

· Assessment of debt risk

· Predicting bank failure

· Bank theft

· Predicting recessions

How an Artificial Neural Network Decisions Works

To give an example of how an ANN decision can be made, let’s consider an example of what could be used to make a creditworthiness decision.

Inputs

· Age

· Gender

· Annual Income

· Length of time at current job

· Marital Status

· Number of Children

· Number of Children in the home

· Education level attainment

· Homeowner or renter

· Cars owned

· Address/area

· Commute distance

· Credit score

Training and Testing

There will be a large set of clean data created that contains all the inputs to be fed into the ANN to train it with known results (this is called the training set), changing the weighted variables for each neural node to increase the model’s prediction accuracy.

Once the ANN is trained, a different set of input data is supplied (none of which is present in the training set), and the ANNs “Loan Approved” results are obtained. This second run through of data is a “test set” and can be done using real-time data coming in.

Based on what was “learned” during the model’s training phase, the accuracy of the predicting ability is refined. The model’s prediction accuracy depends on the various input factors that go into it as well as the addition of hidden layers which are added to the neural network–until the optimum level of accuracy is achieved.

Closing Thoughts

ANNs have continued to improve, and their use has broadened with the decreases in computer costs and the persistent increases in computing power. They will likely be a foundation for financial and economic models but may need to evolve with the likely adoption of quantum computers.

As we move forward, ANNs will become an even more useful tool to automate service- or data-oriented tasks. The financial, banking, and insurance worlds have an abundance of clean data that can feed into ANNs.

Care must be taken to ensure that bias is removed from any data going into the model as this can ensure that bias will not come out of the model. Essentially, if we treat the models with care, they will bring us infinite value.

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group, www.deltecbank.com.

The History of Stablecoins

Posted on September 1, 2022September 1, 2022 by Jean Chalopin

Stablecoins, especially fiat-backed stablecoins, seem poised to dominate online currency exchanges across the world. Tether grew by approximately 82 billion USD in five years and USD coin by approximately 54 billion USD in two years. How did this happen? What is the history of stablecoins?

In a word, brief. In several words: expansive, incredible, awe-inspiring, somewhat confusing.

This article follows the history of stablecoins from its first origination only five years after Satoshi Nakamoto’s Bitcoin, 2014, through to today. In other words, this article describes the creation of hundreds of billions of market capitalization of a new asset class in eight years.

BitUSD

The world’s first stablecoin was released on July 21, 2014. As a crypto-backed stablecoin, BitUSD was issued on the BitShares blockchain, which is now mired in obscurity.

Dan Larimer (EOS) and Charles Hoskinson (Cardano) envisioned these pioneering digital assets before they went on to become cryptocurrency rockstars today.

However, BitUSD lost its 1 to 1 parity with the US dollar in 2018 and has been unable to recover since. BitMEX’s research brilliantly highlighted the stablecoin’s weakness in their detailed analysis of BitUSD. BitUSD was collateralized with an obscure, volatile, itself-unbacked asset, BitShares.

In the event of a fall in the price of BitShares, a single BitUSD can be used to purchase more of Bitshares and thereby encourage mass arbitrage similar to traders of traditional asset classes. However, the opposite was not guaranteed. There was only an implied pile of reserves from BitShares alone. Therefore, BitUSD operated much more like a volatile security than a stablecoin.

Yet it did succeed in putting the concept of pegged stablecoins on the radar and beginning the history of stablecoins.

NuBits

Also launched in 2014, the second stablecoin provided ample lessons to the fledgling, but growing crypto community. NuBits was crypto-collateralized, similar to BitUSD, but this time using Bitcoin.

Ultimately, that failed to help in any way. Since Bitcoin was and is a volatile asset trading according to the tune of speculators across the world, Nubits reserves could not be high enough nor mature enough to withstand a rout. As Bitcoin fell, the coin’s reserves fell.

Like with traditional investing, the primary method to reduce the impact of volatility is to diversify. However, not only were the reserves of NuBits fairly volatile, they were insufficient and undiversified.

A lack of capital and diversification spelled doom for the second stablecoin, now trading around 0.04 USD.

TerraUSD

In May 2022, the TerraUSD (UST) algorithmic stablecoin crashed, hard, losing almost all of its value in days.

Source: How It Happened

TerraUSD relied upon an algorithm and the forces of arbitrage to fix the value of one UST to one US dollar. If it became too cheap, the (centralized) powers behind UST could retract supply or provide further incentives for holders of other cryptocurrencies to convert their holdings into UST coins. If it became too expensive, additional supply could be created.

However, demand would remain naturally occurring, even if incentivized. This translated into a glaring weakness.

Despite the Luna Foundation Guard, the body protecting TerraUSD’s reserves, once holding a warchest of over 70 thousand bitcoins, it failed to prop up the stablecoin in the face of a complete rout. Today, one UST is roughly 0.02 USD.

The Lesson

In the history of stablecoins, all three carry one essential lesson: unstable cannot back stable. In normal market circumstances, partial reserves and arbitrage mechanics probably do the job just fine in the context of fractional reserve banking. As long as all investors do not act all at once, a non-fiat-backed stablecoin should function normally.

This is why the headlines covering each of these three crashes also carry the same tone of: fine, until not fine. In each instance, too many investors piled into the selloffs and effectively broke the reserve assets.

Unless there is a 100%, stable reserve backing a so-called stablecoin, most investors feel weary of the street logic. Meaning, how can an idea of assumed stability or enough volatile reserves become enough to handle a total rout? It can’t. That’s all there’s to it.

Tether

Launched in 2014, Tether (USDT) came to extraordinary success with a current market capitalization exceeding 67 billion USD.

This stablecoin fixes the issues inherent in the previous three. It relies not upon volatile reserves or the idea of persistent arbitrage trading, but on hard reserves of fiat currency. For every Tether coin in existence, there is one US dollar in a vault backing its existence.

In this way, the stablecoin handles a complete theoretical rout with ease. Tether continues to serve the burgeoning digital asset space while garnering the implicit affection of regulators.

Dai

Launched in 2017, MakerDAO’s Dai is a decentralized, crypto-backed stablecoin capturing the hearts of DeFi (decentralized finance) investors.

The match in ethos feels all well and good, but is Dai secure? Is it at risk because of its crypto-backed nature?

Dai has yet to crash or break its 1 to 1 peg to the US dollar. The stablecoin is technically a hybrid of crypto-backed and algorithmic, employing a simple algorithm requiring 1.70 USD worth of Ethereum to be deposited in exchange for any 1.00 Dai.

The premise here remains simple and that is a very good thing in terms of handling potential crashes. MakerDAO is banking on (1) a 70% buffer in value and (2) diversified reserves. In addition to Ethereum, the stablecoin utilizes USD Coin (like Tether; 42% of reserves) and Wrapped Bitcoin amongst others.

And in these holdings we see a third, albeit clever safety mechanism. Approximately half of Dai’s reserves are fiat-backed through fiat-backed stablecoins.

Closing Thoughts

The history of stablecoins remains brief, but exceptional. In that time, entrepreneurs daring to transfer the global landscape of financial services learned key lessons.

BitUSD, NuBits, and TerraUSD failed due to an overreliance upon a volatile asset backing an intentionally stable asset. Volatility without diversification struggled under the weight of investor redemptions–something any bank could potentially encounter. The growing Dai stablecoin continues to succeed due to its steep algorithmic requirements and diversity in reserves.

Tether and USD Coin function remarkably well despite a “crypto winter” and leave regulators in begrudging awe of their efficacy. In eight years, stablecoins stand ready to disrupt traditional financial services on a global scale.

The Top Five Fiat-Backed Stablecoins

Posted on August 29, 2022August 29, 2022 by Jean Chalopin

Stablecoin regulation and the concept of mass stablecoin use grows daily. What began with news of an unfortunate crash highlighting the “risks” of stablecoins continues to snowball into a globally supportive movement for fiat-backed stablecoins.

The key to understanding: algorithmic stablecoins, relying upon an algorithm to maintain a hard peg to an external asset, suffer from a shaky foundation. The goal is creative, novel–even noble, in its hope to remove fiat’s inflationary influence. Yet can an algorithm deal with freefalling markets?

No. Investors and regulators alike learned, very quickly, that introducing volatility or unguaranteed assets anywhere in the chain of a stablecoin’s reserves almost guarantees disaster. Remove that monkeywrench and we have something of a masterpiece.

The European Council introduced a comprehensive framework effectively accepting fiat-backed stablecoins. The United States purported legislation calling for stablecoin regulators and protections for crypto investors, although this is in flux until September.

But why, all of a sudden, the mad dash from governments across the world? The answer lies in market capitalization. For example, Tether reached over 83 billion USD in 2022, from under 1 billion USD in 2017.

This article delves into the top five fiat-backed stablecoins and what you need to know before regulation is likely passed everywhere.

Tether

Launched in 2014, Tether is a fiat-backed stablecoin, pegged 1 to 1 to the US dollar. One USDT equates to one USD.

Name: Tether
Ticker: USDT
Price: 1 USD
Market cap: 67.6 billion USD
Crypto rank: 3

As a recap, a fiat-backed stablecoin generally keeps 100% of the value of coins in regulations backed in actual US dollars. It may publish regular, audited reserve reports proving this backing.

Tether, for example, is famous for publishing reports detailing the makeup of its reserves. Currently, almost 80% goes to cash and cash equivalents, including short-term paper (debt).

USD Coin

Launched in 2018, USD Coin is also a fiat-backed stablecoin, pegged 1 to 1 to the US dollar. One USDC equates to one USD.

Name: USD Coin
Ticker: USDC
Price: 1 USD
Market cap: 52.4 billion USD
Crypto rank: 4

Like Tether, USD Coin publishes its reserve reports frequently. It expressly markets itself as a “digital dollar.”

Binance USD

Launched in 2019, Binance USD is a fiat-backed stablecoin offered by the world’s largest crypto exchange, Binance.

Name: Binance USD
Ticker: BUSD
Price: 1 USD
Market cap: 18.8 billion USD
Crypto rank: 6

Binance USD operates identically to Tether or USD Coin, but its focus remains for users of the Binance exchange.

Dai

Launched in 2017, Dai is a crypto-backed stablecoin focused on upholding its ethos of decentralization. Instead of US dollars or euros, only other cryptocurrencies comprise the reserve assets of Dai. Decentralization refers to a mandate of not having a central entity controlling the supply of Dai coins.

Name: Dai
Ticker: DAI
Price: 1 USD
Market cap: 7.1 billion USD
Crypto rank: 13

Dai remains popular in DeFi (decentralized finance) circles, with each “DeFi” referring to a protocol or other entrepreneurial effort to improve or replace traditional white collar services.

TrueUSD

Launched in 2018, TrueUSD builds upon the fiat-backed stablecoin ethos with daily holdings reports, monthly audits, and protections against theft.

Name: TrueUSD
Ticker: TUSD
Price: 1 USD
Market cap: 1.2 billion USD
Crypto rank: 44

Despite offering a pure fiat-backed solution for US dollars, it still falls by the wayside and well under the rank of crypto-backed Dai. This may be due to the dominance of Tether and USD Coin.

Summing Up

Three of the top 10 cryptocurrencies in the world by market cap are stablecoins. Specifically, they are fiat-backed stablecoins whose mandates are to provide stability, utility, ease, and minimal transfer costs.

That is to say, their mandates do not include “changing the system” or “bucking the trend.” They make no ideological arguments and, unlike DeFi, seek not to challenge the overarching dominance of central banks.

Will this change? Will inflation and global inequality reach a point to where many more might risk stability for a currency not prone to double-digit inflation? Time will tell–and fiat-backed stablecoins may yet be the first step.

Crypto Lending, Staking, and Protocol Dividends

Posted on August 26, 2022August 26, 2022 by Jean Chalopin

Dividend stock and coupon bond investors earn passive income via dividends or their coupon payments. For the longest time, no regular paying passive investments were available in the crypto world, having to rely solely on capital gains, but that has quickly changed. Now there are options for earning passive income through crypto lending, crypto staking, and protocol dividends.

Lending, staking, and dividends are now ways for crypto holders to make money with their crypto holdings without selling their holdings. This set of options leads an investor to ask what is the difference between them, and is there one preferable to the other two?

We will start with a brief crypto introduction, explain the different passive income choices for crypto investing, and then explain the positives and negatives of choosing one over the others for a passive investment choice.

A Crypto Brief

Until the advent of Bitcoin in 2009 by the mysterious Satoshi Nakamoto, virtual digital currency was a thing of science fiction. The only type of currency the present generations knew was fiat. That which was only backed by the good name of the government and central banks that issue it. Some older readers might have known a time when a currency was tied to assets like gold and, in some cases, silver.

Notice what is written directly below the picture of George Washington, “IN SILVER PAYABLE TO THE BEARER ON DEMAND.”

Since the Great Depression, the U.S. dollar has been defined by the county’s economic outlook and a promise that the U.S. government will always consider the dollar redeemable for lawful currency at the U.S. Treasury. This is the meaning behind, “Backed by the full faith of the U.S. government.”

Cryptocurrency has an aim to avoid any governmental or institutional middleman through the decentralization of money, giving power back to the holders. Such decentralization is meant the make the transfer of value between the users of the currency easier, reducing the costs of these transfers and preventing any tampering or corruption possible by a middleman.

Cryptos are able to do this with the advent of blockchain technology. In its most simple form, a blockchain is a database that proves the crypto’s value by maintaining a transaction record in a decentralized manner, which is accessible by all. However, it is “immutable” or alterable by none.

Bitcoin is the most well-known crypto, and it was the first. However, Bitcoin is only one form of virtual currency and is often misused to mean cryptocurrency in general. With the advent of so many different cryptocurrencies, their concept can be confusing because Bitcoin is considered a tradable asset.

Cryptocurrencies are now not just for tracking the transfer of a single coin’s value, but blockchain projects such as Ethereum, Cardano, and Polkadot have been created to facilitate a vast array of new activities. These projects have more native functionality and are cheaper to operate.

Rewards

This article focuses on token rewards, like the dividends paid by a share of stock owned. However, in two cases, this is not a profit share. It is a form of compensation received from lending your tokens back to the blockchain project for use in the facilitation of transactions and administration of processes on the blockchain.

· Crypto lending is the leasing out of owned crypto to human borrowers, and in return the lender receives interest.

· Crypto staking is the leasing out of owned crypto to that particular coin’s blockchain to receive token rewards.

· Protocol dividends represent the newest passive income streams and are closest to the dividends of stocks. These tokens give their holders a payment as a portion of the issuer’s profits, but the difference is that the token owner does not have any other rights to the company.

Let’s review the adoption of these different passive earnings approaches. In April, the largest institutional crypto lender, Genesis, released its Q1 2022 Market Observations Report. The report stated that as of March 31, 2022, cumulative loan originations reached $195 billion, with $44.3 billion in Q1 2022 alone. This Q1 result is more than double all of the crypto loans that originated in 2020 combined.

Though the value of crypto has decreased significantly DeFi Pulse shows that there is nearly $39 billion locked in lending, up from just over $9 billion two years prior (June 21, 2020).

Data courtesy of DiFipulse

In the past 12 months, staking has also increased in volume. In the Staked “State of Staking” Q1 2022 report, it was stated that staking yields increased to 15.4%, and the staking rate grew to 49.3%. This resulted in staking rewards that were just under $15 billion for Q1, up 57% over Q1 2021. To get such a return, investors would need to purchase about $860 billion in 10-year U.S. Treasury bills to realize a similar return. This report also stated that Proof of Stake protocols account for 30% of cryptocurrency’s total market cap.

Dividend-paying tokens are the newest form of coins that provide owners a passive income. The payouts may be regular, weekly, monthly, they may be dependent on a defined level of token ownership. The larger holders are first in line, and they may also require the network to reach a particular milestone of performance. Being new, there is very little info about these types of tokens’ overall performance. However, there are several tokens that have chosen this route to provide a source of income for holders.

Differences Between the Passive Methods

All crypto investments can be risky due to their volatility, and even stablecoins have shown that they are not immune to the risk. Depending on the type of stablecoin, the backing behind it can make its peg to a fiat currency stronger, lowering the risk to investors.

Crypto Lending

Crypto lenders will lease their crypto to borrowers on specific platforms. These platforms charge borrowers’ interest on the loans and pay a portion of that interest to the lender. The loans are secured with a deposit of the borrowers’ crypto.

Bitcoin lending can generate 3-8%, and other altcoins can generate returns in the double digits. Stablecoins can be lent out for good returns without the typical crypto volatility. Some platforms offer up to 12% returns, but returns are generally a bit higher than the typical 0.5% of a bank savings account.

An essential crypto lending positive is that your money is tied up for a term of between 1 and 90 days, not years.

Crypto Staking

Stakers commit their tokens to the native blockchain. The stake is used to ensure the network’s security infrastructure, and the staker is compensated with a reward of more coins. Staking is usually for a 30-day cycle of commitment, and staking will usually provide better rates than a bank CD. There are staking pools where you don’t have to stake the entire required minimum amount needed (Ethereum requires 32ETH, approximately $38,300USD at the time of writing).

A new method called “liquid” or “soft” staking is also available, giving you access to your funds even while staking them, giving the returns for staking and the liquidity for trading when needed.

Protocol Dividends

Being similar to stock dividends, protocol dividends vary greatly in how and how much gets paid to holders. For example, Hong Kong-based Kucoin will share 50% of the transaction fees with the holders of 6 or more KCS tokens. The better the exchange does, the higher the dividend.

Decred supplies decentralized credit. This multi-platform crypto has a hybrid proof of work (PoW) and proof of stake (PoS) consensus mechanism that is run by the DCR token. DCR stakers can receive dividends of up to 30% per year.

Ontology offers peer-to-peer trust infrastructure, and users can benefit from dividends and staking rewards. A $10,000 investment currently has the potential to make a 43% annual return.

Safety and Regulation

There are some issues with crypto passive income. Lending always has the risk of default, and coin volatility can happen when the investment is ongoing. The recent crypto market falls have shown that even Bitcoin and stablecoins are susceptible to volatility. This natural uncertainty means that a coin can drop in value while staked or lent out, leaving you unable to get out and limit losses.

Governments have been pressuring lending platforms over certain methods that are considered “unlicensed securities.” This gives reason to use platforms that are centralized and licensed to conduct business in your nation.

Staking does not have the same regulatory concerns as lending, but volatility remains. For traders looking at capital gains as their source of income, only liquid staking may be the optimal choice.

Closing Thoughts

Crypto lending, staking, and platform dividends are new ways to earn passive income on crypto holdings. If any of these are in your portfolio, be diligent with the tax and regulatory requirements of your locality to ensure that you are compliant. As the crypto world expands further, there will likely be more types of passive crypto investments.

These revenue streams have incredible potential for economic gain, but they also have corresponding risks. They should be considered part of an overall portfolio, not stand alone. Review the different options for lending platforms–they differ significantly and have different risk profiles.

Most staking and lending activities are not warranted if liquidity is needed, but liquid staking and dividends could make sense. If you are a long-term holder, then any of the methods may produce significant results assuming that the coin’s volatility matches your risk profile.

Bear Market Crypto Strategies

Posted on August 23, 2022August 23, 2022 by Jean Chalopin

In June 2022, the S&P 500 entered its first major bear market, excepting the very brief bear market of 2020, in 13 years. Bitcoin’s original ethos of “digital gold” implied a lack of correlation to traditional markets. Yet crypto, the S&P 500, and Nasdaq appear interlinked regardless. So, what are the possible bear market crypto strategies available to investors today?

First, we must understand the relative youth of cryptocurrencies as an asset class: 13 years. Analysts focusing upon traditional asset classes benefit from over a century of modern data concerning stocks, bonds, funds, and so forth. However, every year brings something new for crypto.

Second, a traditional bear market should not in theory translate to a “crypto bear market.” Yes, so far, it does. What causes such a bear market, then?

Third, what bear market crypto strategies are available to us? Usable data and advice feels limited. There remains a handful of globally minded, professional advisors specializing in digital assets. Fortunes continue to be made with crypto, and there are relevant tips for all of us.

This article delves into crypto bear markets, their possible causes, and the strategies for coming out on top. Let’s get to it.

Traditional vs. Crypto

Investopedia describes a bear market as “a condition in which securities prices fall 20% or more from recent highs amid widespread pessimism and negative investor sentiment.”

Typically, the focus is upon an overall market or index, such as the S&P 500 and Nasdaq. They may precede or associate with a larger economic recession, either domestic or global.

Source: Practical Wisdom – Interesting Ideas

For understanding digital asset markets and bear market crypto strategies we can use the definition found on Coinbase’s website: “Bear markets are defined as a period of time where supply is greater than demand, confidence is low, and prices are falling.”

One clause trumps the three, “confidence is low.” Despite the original premise of digital gold, the truth lies closer to the idea of risk-on investing. Confidence, another way of saying “investor sentiment,” dictates the general trend in prices that we arguably have a market dominated by the style of growth investing.

This runs similar to investopedia’s definition, excepting two key details: (1) 20%, and (2) the implicit reference to an overall market index. An overall market index, such as the S&P 500, contains growth and value securities, making it a broad index.

Deteriorations in economic conditions translate to central bank decisions, and both translate to bear markets. The correlations between economics and traditional assets remains clear. For example, a sharp drop in the savings rate implies a further decline in luxury or inelastic spending. The correlations between economic indicators and digital asset markets feel remarkably less clear.

What Causes a Crypto Bear Market?

If we assume that digital assets markets, given their relative newness to the world, reflect the growth investing style, then we can reasonably speculate towards their origins.

Excessive Leverage

Defined as open interest divided by the value of relevant reserves, the estimated leverage ratio provides a glimpse into traders’ appetites. For Bitcoin, this reached a new high in January 2022 and offered a long-range warning signal.

Interest Rate Hikes

Like gold, major cryptos are inversely correlated to real interest rates. As the Fed funds rate stuck to 0.25% in 2021, Bitcoin soared 60% and Ethereum 399%. Yes, you read that correctly.

Yet excessive growth begs excessive increases in prices. Inflation is a sharp, possibly deadly, double-edged sword. The post-industrial economy relies upon inflation to encourage demand and innovation in tandem, yet too much eats away at savings, wages, and sentiment.

Traditional Asset Losses

By examining similar growth and alternative sectors, analysts can forecast what’s likely to happen to cryptos.

Bitcoin’s price peaked at nearly $70,000 in November 2021, when the Russell 2000 (a small-cap index) also peaked at nearly $2,500. The patterns have since then moved oddly in step.

Technical Troubles

Bitcoin, Ethereum, and altcoins remain famous for their volatility–perhaps much more so than for their mystery.

In volatile markets, technical indicators guide traders on how to act and react in the short-term. For example, a “death cross,” or when a 50-day moving average falls below a 200-day moving average, suggests selling immediately.

Bear Market Crypto Strategies

Before we delve into general tactics for managing a crypto bear markets, there are some fundamentally oriented pieces of advice to consider:

Take the time to understand your favorite coins’ protocols; these reflect their competitive edges
Research and form an opinion on the major “proof-of” systems, such as work, stake, or hybrid
Determine your investing time horizon and maximum allowed drawdown (loss)

And with that said, here are three strategies to maximize returns and minimize losses in a crypto bear market.

Dollar-cost averaging. Gauging the specific bottom of a bear market remains a virtually impossible feat even for veteran analysts. However, data from a 60- or 90-day period may provide the grounds for an educated guess. Dollar-cost averaging here means to purchase equal dollar allotments of cryptocurrency at regular time intervals, often weekly.

Staking. Not the same as lending for interest, staking refers to supporting the protocols of blockchains using the proof-of-stake system. By depositing or staking your coins, you become a validator (i.e. verifier) for that blockchain and effectively work for that blockchain. Staking represents your yield and paycheck.

Diversifying. With digital assets, it pays to understand the different possible protocols and uses for blockchain technology. Bitcoin is the standard proof-of-work cryptocurrency and maximizes security through required energy power (to solve the next hash puzzle). After the upcoming Merge, Ethereum is to use proof-of-stake, or the energy-conscious system of randomly chosen validators who stake their holdings.

While it’s always recommended to sit down with a professional advisor well-versed with digital asset markets, a blended approach is a good place to start. Identify your time horizon and risk tolerance, and then determine what you want to buy through dollar-cost averaging, what you would like to stake, and which blockchain protocols may lead the next bull market.

Using Stablecoins as a Savings Account

Posted on August 12, 2022August 12, 2022 by Jean Chalopin

Our article focusing upon the inevitability and importance of stablecoin regulation given the success of fiat-backed stablecoins indirectly introduced another subject: savings in the time of inflation. How are investors already using stablecoins as a savings account?

Regulators across the world seem to approve of fiat-backed stablecoins, whether begrudgingly or not, because they hold to their pegs through the simplest of safeguards. That is, one US dollar or euro (for example) for every coin “minted” or released.

It works, virtually flawlessly, as it seeks not to eradicate the fiat structure but destroy the incumbent idea that transfering cash should cost anything more than 1 or 2 USD. Frankly, it should cost nothing.

In addition, using stablecoins as a savings account opens up the door to a much more sophisticated “crypto” portfolio arguably able to beat traditional returns, particularly during global bear markets. Fiat-backed stablecoins serve as gateways to much greater yields and capital gains.

This article delves into the wisdom of embracing stablecoins as a savings account in this year of rampant inflation.

The Cost of Cash Savings

What do we mean by the cost of cash? Simply put: it costs money to hold money. The opportunity cost we hear of in economics class actually takes cash out of your pocket. The technical term for this is inflation.

For July 2022, the headline consumer price index rose by a less-than-expected 8.5% in the USA.

In other words, the value of your US dollar decreased by 8.5% in the past year. If you did nothing with one dollar, you lost 8.5 cents.

In this way, inflation forces you to invest, to put your capital to work. This remains the nature of modern economics, which introduced the common term of “healthy inflation” at 2 percent. As economies grow, businesses in general want to increase their profits, leading to noticeable price rises over the long term.

However, what’s distinctly wrong with 2022 is the reward for saving, or traditionally known as “interest.” For the USA, the national average savings account rate is currently 0.13 percent. Is that worth opening an account? The paperwork?

Using Stablecoins as a Savings Account

Stablecoins open up new doors and new financial opportunities in tandem.

Towards the latter part of the last decade, getting involved with crypto felt like trusting your life’s savings with a dodgy “digital wallet” that worked in a manner beyond full comprehension. And this digital wallet could be hacked. Therefore, you had to make your wallet “cold” by taking your wallet “offline” and writing your “private key” down on separate sheets of paper.

Because you could simply lose your life savings too, in the way you might lose your TV remote.

However, coronavirus taught us the sheer potential of shifting all of our workflow to an encrypted cloud safe from hacking and manipulation. Now, work-life balance exists. Remote working feels the norm. An office needs a reason to call you in.

Cryptocurrency exchanges now automate the wallet process for you, facilitating trading as an online broker would, while often providing insurance in the event of hacking or theft. Opening a new account for stablecoins generally takes less than 10 minutes from the moment you open your laptop.

In addition to eliminating transfer fees, stablecoins open the door to “staking,” or the common practice of depositing or staking your stablecoins for use by a specific blockchain or protocol.

Any one protocol is the product of an entrepreneur or institution trying to disrupt the incumbent issues with traditional finance or the traditional brick-and-mortar world. These are the folks working to make your life easy while hoping to make a digital buck along the way.

For example, the world’s largest stablecoin by market capitalization, Tether, currently pays an annualized staking rate of 6.02%.

Crypto-to-Crypto

Deltec takes the common practice of providing access to traditional assets and digital assets simultaneously, but gives holistic, actionable advice along the way. Using stablecoins as a savings account, particularly in the context of a mixed portfolio, yields a tertiary benefit beyond free transfers and high deposit rates.

Crypto-to-fiat transfers can turn costly, especially when working with alternative cryptocurrencies not among the massive Bitcoin or Ethereum blockchains. Crypto-to-crypto remains a solid alternative as it offers substantial liquidity.

For example, Tether currently has a 24-hour volume of 69 billion USD equivalent. This is a simple measure of how much Tether was traded on a rolling, daily basis.

Cryptocurrency liquidity pools tend to utilize major, liquid coins as a central segway between multiple other cryptos. This process is known as “routing.”

Source: Whiteboard Crypto

Using stablecoins as a savings account offers 5 key benefits:

Eliminates transfer and similar banking fees
Widens the range of eligible transferees to anywhere on the globe
Offers above-average staking rates
Offers the chance to take part in very high-yielding liquidity pools
Opens the door to many other cryptocurrencies

While many crypto enthusiasts seek to reduce the reliance upon fiat and its possibility of extraordinary inflation, we count our victories where we can. These essential benefits to stablecoins both democratize the world’s access to capital and offer the financial means to a better life for all.

Deep Learning, AI, and Finance

Posted on August 11, 2022August 11, 2022 by Jean Chalopin

Deep learning has been applied to computer vision (self-driving cars), natural language processing (speech-to-text), and audio-visual recognition. The successes seen with deep learning as a data processing pathway have attracted interest in several areas, including research and finance.

According to the IDC, banking will be one of the industries that spends the most on AI solutions in the coming years. With the proliferation of Fintech in the recent past, the use of deep learning and AI in finance has already become prevalent.

We want to introduce this field of Deep Learning that is growing in prominence quickly, provide a few examples of how the banking and finance worlds are solving problems with state-of-the-art deep learning models, and give a vision for the future of finance.

Deep Learning Simplified

Deep learning comprises a subset of Artificial Intelligence and Machine Learning that provides the output for a set of highly complex inputs. Within deep learning itself are neural networks and deep neural networks, which we will explain in brief shortly.

Artificial intelligence is our broad idea of learned concepts by machines that are intended to supplement or replace the actions of humans. More simply, AI is a machine that mimics the human mind, with learning, rationalizing, and problem-solving skills.

Machine learning is the application of algorithms and statistical models where a machine will perform a specific task, but does not need any explicit instructions to do so. This ability is because machine learning algorithms are using learned patterns and inferences they gain from past data.

As we move deeper, reaching deep learning, we are now utilizing huge data sets, and the information available is very complex. With this information, a deep learning model can identify errors and correct them without the intervention of humans. Machine learning will not use this sort of in-depth information, and it cannot correct errors without human intervention.

Deep learning takes advantage of neural networks, which are algorithmic systems that can process information the way humans would and then solve various tasks. This is the point where the concept of artificial neural networks comes into play, where the designs mimic a biological neural network (the nerve cells within life forms).

Image courtesy of techvidvan.com

Deep neural networks are created when there is a combined group of artificial neural networks, and this group works together to provide outputs to a set of very complex inputs.

Image courtesy of kdnuggets.com

The more complex the inputs, the better deep neural networks will perform compared to less sophisticated machine learning models.

Deep Learning and Finance

When we turn to finance, artificial intelligence is widely applied to the industry. The banking sector is making investments in fraud analysis and investigation, programmed robo-advisors, and recommendation systems.

Research from Accenture indicates that $1 billion in value will be added to the financial services industry by 2035. AI is being used to identify unusual debit and credit card use or a large number of deposits into an account.

These applications are ways that artificial intelligence can save clients and banks from ongoing fraudulent activity. AI is also being used to make trading easier and more efficient with organized, quick decision-making, taking advantage of the various factors in the markets that neither a single person nor even a team of humans could process at the same rate.

Deep learning provides capabilities to automate complex operations and make decisions at higher degrees of accuracy than other statistical and machine learning methods.

There is an important factor required to run deep learning models, which is the need for a significant volume of high-quality datasets in order to produce these beneficial and more accurate insights. Fortunately, this kind of data is exactly what the financial industry has and can utilize. The plethora of bill payments, transactions, suppliers, customers, prices, and their movements can fuel deep learning models and result in successes.

Supervised Models and Unsupervised Models

Deep learning models are characterized by two broad types:

Supervised and Unsupervised

We won’t go deep into the specific algorithmic models, such as, Convolutional and Recurrent Neural Networks, Self-Organizing Maps (SOMs), and Autoencoders. However, we will say that these supervised and unsupervised models are trained differently and hold different features.

Supervised models are trained with examples of a particular dataset. There is a list of “features” that the data set will include (weather, price, credit score, age, location, employment, salary, etc.), and it also has an output result that can be two or more choices (paid loan off or defaulted, a number or percentage), but the output has been characterized by human intervention.

Unsupervised models are only given input data. They don’t have any set outputs. These models will infer underlying hidden patterns using historical data. With such an approach, a deep learning model will try to find similarities, differences, patterns, and or structure in the data by itself.

For example, the computer knows what a cat picture looks like but does not know that it is specifically a cat nor that there are other cats in the world. It “sees” any image that has two ears, four legs, a tail, fur, and whiskers and predicts that it is a “cat” to the model. This process is considered unsupervised.

If it is told that the first training picture is a cat and a second picture is a cat, but a third is a dog, then it is supervised.

Deep Learning Use Cases

While there are several use cases for deep learning in finance, we will introduce the places where it is already active and provides the most benefit to the financial industry.

Lending

Deep learning systems use learned patterns from historical records and the results of document processing to assess the credit worthiness of loan requests. The input data include income, age, occupation, current financial assets, overdraft history, current credit scores, outstanding balances, foreclosure history, loan payments sizes, and other data points.

Combining all this information, a deep learning model can decide about a client’s qualification for a loan and the likeliness that they will repay the loan as expected. It will further improve based on the results it sees with its own decisions.

Customer Service

Financial service companies are using finance-specific telephone, and web-based chatbots with deep learning models behind them intended to improve the user’s experience. These deep learning-based solutions bring personalized service to customers allowing them to complete several financial activities, including the:

Automation of frequently completed actions (checking balance, account numbers, recent transactions).
Suggestion of products that are not currently used by customers but might be a good fit (credit cards and other loan products, overdraft protection).
Answering of key questions (what balance is needed to waive by account fees?).

Deep learning models can also identify potential churn and prevent customer loss by analyzing interactions and preemptively making special personalized offers to retain the customer. This capability allows insurance companies and banks to provide new plans and discounts that will protect their customer base from other institutions.

Fraud and Compliance

Deep learning is effective at identifying suspicious transactions in real-time with high precision, preventing them before they are complete.

It can also incorporate unstructured data such as satellite and street view images to confirm the existence of a business to facilitate other compliance controls. With these features, deep learning algorithms can reduce a bank’s operational costs while also improving its regulatory compliance.

Improving Credit Utilization

Financial institutions want cardholders to utilize their cards effectively, and deep learning systems can identify optimal consumers. This allows for more meaningful questions to be put on card applications and optimizes the respective credit limits.

Market Predictions and Trading Analyses

Using historical data and additional parameters of the current market, the neural networks of deep learning systems can predict stock values. The systems will utilize detailed data to predict the market and individual asset values.

With more data using its system of hidden layers, a deep learning network’s prediction ability improves. Because a deep learning model can analyze numerous data sources at the same time, including sentiment analysis, it can provide results faster than humans. Lacking emotion, the predictions and trade decisions are neutral and more data-driven.

Robo-Advisory Services

A robo-advisory platform is nothing but algorithms that advise clients or advisors with regard to portfolio allocation and constituents. These tools recommend specific products like insurance, portfolio management, and distribution across various investment opportunities.

Insurance Underwriting

Using historical data, insurance companies train deep learning models to evaluate potential policies. Data can include health records, wearables, potential health issues, income, age, profession, credit history, and more. These models can predict and reduce risks, set more accurate premiums, and improve the speed of the underwriting process.

The Future of Deep Learning in Finance

With the wide offering of services that deep learning provides to finance, the future is bright. According to Varified Market Research, OpenPR.com’s evaluation report on deep learning in finance states that deep learning will continue expanding until at least 2027 and beyond.

The presence of machines making more decisions in the financial realm, which started high-frequency trading, already makes billions of trades possible in a microsecond. By 2018, up to 73% of trading was being done by algorithms, and it is likely higher now.

The global rating agency Crisil told cio.com that they were investing heavily in deep learning and had every intention to continue doing so because of the positive results, stating that they have been adopting automated data extraction tools for unstructured paragraphs, tables, and more. This is a key boon, as Crisil told the magazine that nearly 90% of its key processes are data-driven.

Because automated systems can make operations faster and more accurate, they can maximize returns for financial institutions that apply them. The markets are becoming more sophisticated with added AI trading systems making up more of their trading volume.

Deep learning will imbed its importance in finance and shape the industry to come.

Closing Thoughts

We have provided a brief overview of deep learning and its use in the financial, insurance, and banking worlds. The applications of models are both diverse and new.

What needs to be considered is that the data going into a deep learning model is critical. It needs to be clean and accurate to get the best results. If there is a bias in the data going in, then that same bias will continue, and this has happened in the past.

For example, will we be creating a group that will have access to financial services and completely ignore another set? Will our algorithms for offering credit be extracting too much from our clients, putting them into situations that could be beneficial to us but detrimental to them?

These are all ethical questions that need to be considered when building deep learning models. If created ethically, deep learning models shall become a key pillar of our future.

Why Stablecoins?

Posted on August 9, 2022August 11, 2022 by Jean Chalopin

The fundamental question behind stablecoins and their destiny for disruption remains: why? Why do we need stablecoins at all? The world was getting on fine without them. It was more or less, stable.

Was it?

The bear market of 2022 following a virtually unbelievable v-shaped recovery following the first global pandemic of several generations brings into question the sustainability of said recovery. Pumping helicopter (free) money into a global consumer base alongside additionally free money from central banks everywhere challenges the concept of purchasing power.

Meaning, that purchasing power, the worth of your dollar or euro, should over a short-term remain stable while you accept small deteriorations over time.

However, the USA is currently experiencing, or suffering, a 9.1% inflation rate. All else held equal, this implies a 9.1% deterioration in your dollar over the last year. Another problem: we’re not yet sure if inflation has yet peaked, whether in the USA or abroad.

So how can stablecoins help? What’s the point?

The Purpose Behind Stablecoins

The primary ethos of a stablecoin remains, forevermore, stability. The crypto community understands the outer world sees the volatility of cryptocurrencies as a whole, uninviting.

Like any traditional portfolio requires cash within a mix of equities or mutual funds, for example, a crypto portfolio necessitates the equivalent. Stablecoins represent that equivalent. No matter the issue, 1 USD equals 1 USD. Likewise, 1 USD Coin always equals 1 USD.

Stablecoins such as USD Coin or Tether earn the respect of regulators worldwide through their mandates of maintaining a 1:1 peg with the US dollar. Despite continuous money printing and the bear markets of 2022, their pegs are holding steady.

Yet you’d be correct if you thought: How does this solve the inflation problem?

This is the second goal underpinning stablecoins: to remove the reliance upon fiat currencies and establish, permanently, a way to eradicate high inflation. It’s easy to forget inflation, but what we all must not forget, is that it hurts most those in the lowest income brackets.

After all, it may be better to limit market intervention when v-shaped recoveries only lead to further downturns down the road.

Centralization, Central Banks, and Transfer Fees

The fiat world is not without issues. Central banks and regulators can raise concerns concerning crypto’s role in illicit activity. However, that narrative is outright false.

The true narrative suggests that the US dollar is used for illicit purposes far more than Bitcoin. Cryptocurrencies like Bitcoin operate through a blockchain, or a public register of all transactions. While seemingly countless transactions happen daily, any user’s name could ultimately be retrieved.

On the other hand, cash transactions effectively eliminate “tracing.” This remains common knowledge.

Centralization and Central Banks

During times of market stress, analysts and executives alike seemingly stay glued to their screens, fixated upon the words of the current central bank leader. In the USA, we have the Federal Reserve (“the Fed”). In the EU, we have the European Central Bank (“ECB”).

As the Fed is the bellwether leading the G7, let’s focus upon its asset purchases. In this context, asset purchases translate to “printing” new money by lending money (generally for free) which did not yet before exist. These purchases grew from less than 1 trillion USD in 2008 to 9 trillion USD in 2022.

While this was to encourage a recovery following the global financial crisis of 2008 and altruistically help people get back on their feet, there is a catch-22. In fact, there is always a catch-22 when the financial markets are pushed one way or another away from their natural ebb and flow.

This translates into a bear-defying 26% return for the S&P 500 in 2021, or when the coronavirus pandemic struck. In other words, if you did nothing for your portfolio that year, you likely would have earned good money, better than many “normal” years.

However, we’re feeling the sharp downside today through inflation and the opposite knee jerk reaction of global bear markets. As that comes, we see how the words (read: “commentary”) of less than a handful of central bank chairs dictate the savings and wellbeing of millions.

Transfer Fees

Historically and somehow today, the cost of sending an international wire transfers ranges anywhere from 30 USD to over 100. While the exact cost depends upon your bank, you get the point.

Why should it cost so much for you to send your money?

And here lies only one part of stablecoins’ disruptive potential. Tether, intended only for large-scale business transfers of pegged USD coins, charges 0.1%. USD Coin showcases withdrawal fees as little as 2.0 USDC, or USD.

Further, select blockchains are working on zero transfer fees.

How Stablecoins Are Shaking It Up

The incessant rise of stablecoins has forced regulators to seemingly accept their worldwide adoption.

In short, they’re:

Eliminating transfer fees for international or domestic transactions.
Removing the need for banks or similar intermediaries.
Holding their pegged currency values regardless of market downturns.
Vastly improving crypto-crypto liquidity, in addition to crypto-fiat.
Establishing favorable crypto interest from regulators worldwide.

Through staking, often returning yields greater than 5%, users deposit or “lock” their stablecoins for use by protocols. Each protocol is different, although they may be separated into categories according to their utility. One example is establishing liquidity for crypto-crypto or crypto-fiat trading pairs.

Courtesy of Whiteboard Crypto

Not only does this yield far surpass a typical “savings” rate of 0.10% or less, it removes the centralization inherent with broker-dealers. These are a limited group of major institutions providing liquidity to popular trades across currencies and asset classes.

For example, there are now several leading brokers catering to everyday retail cryptocurrency or stablecoin investors regardless of geography.

Mass inclusion, democratization, and advancement through technology remain the central pillars of blockchain technology. They’re the pillars of stablecoins as well.