What is FinTech? Here’s how to understand all the terms

April 30, 2020

Blockchain. Mining. Cryptocurrency. Do you sometimes nod as if you understand what’s going on when people mention these and other “financey” terms, or do you ask to change the subject because you don’t “get” these concepts? Do you get some of it, but not a lot of it? My hand is up too – you’re not alone!

Since this is a potential time of
learning (and in my case, baking and eating), I’m sharing some FinTech terms
and information via GetSmarter, to help us become overnight “experts” .

Blockchain Technology and Cryptocurrency

Blockchain Technology, sometimes referred to as Distributed Ledger
Technology (DLT), makes the history of any digital asset unalterable and
clearly seen by anyone through decentralisation and cryptographic hashing. An
apt example of the blockchain model is cloud-based, shared-document editing.
The document itself can be edited by multiple parties simultaneously and
previous versions are saved to the cloud and become unalterable.

Users can revert to a previous version but cannot alter the version
history as the new version will count as a new iteration since the chronology
of changes is locked. Also, changes are made by all users in tandem, allowing
everybody to see them, making the alterations transparent. Blockchain
technology is more complex than this but as an analogy, shared editing
illustrates the basics of the concept.

Blocks, Nodes and Miners

To simplify the blockchain technology even further: a blockchain contains
three important aspects – blocks, nodes and miners.

Blocks

Blocks are the rudimentary matter within the chain, which contains multiple blocks. Each block contains

Data

A 32-bit whole number called a nonce which is randomly generation when the block is created and generates a block header hash.The hash is a 256-bit number linked to the nonce. It starts with an incredibly large number of zeroes, making it quite small in terms of numbers.

Miners

Miners create new blocks on the chain through a process called mining. In
a blockchain, even though every block has its unique hash and nonce, the hash
of the previous block in the chain is referenced in the new hash, making mining
a new block difficult, especially in large chains.

Miners use specialised software to solve the mathematical problem of
finding a nonce which generates an accepted hash. There are approximately 4
billion nonce-hash combinations which have to be mined before the correct
combination is found. When this happens, the new block can be added to the
chain.

A security feature which makes this entire process so appealing is that
making a change to any block earlier in the chain requires re-mining not only
the block with the change, but all of the blocks that come after it. The amount
of computation needed for that, including the time, is undesirable for most
people. This makes blockchain technology difficult to manipulate.

Nodes

Finally, the nodes. Nodes are the decentralised aspect of blockchains. No
one device can own an entire blockchain, it is distributed as a ledger via the
nodes connected to the chain. Any electronic device which keeps the blockchain
network functioning can be considered a node.

Each node has a copy of the blockchain and any new blocks which must be
added to the chain must be approved by the entire network before the blockchain
can be updated and verified. Each person in the blockchain has a unique
alphanumeric identification number that shows their transactions and everybody
with access to a copy of the blockchain, via the network, can see the entire
blockchain transaction history.

Cryptocurrency

Cryptocurrency is, therefore, a financial means of using blockchain
technology to make payments and other transactions. All the main aspects which
make blockchains viable including decentralisation, transparency and
inalterability are what make cryptocurrency a powerful concept. It is not
controlled by a central authority and can be sent directly between two parties
with minimal processing fees. In this way, people avoid the high fees charged
by some traditional financial institutions.

An interesting fact: cryptocurrencies are named that because their existence within the blockchain structure is secured by strong cryptography. They are secured by complex mathematics.

Another added benefit is that the unique alphanumeric identifier each
user in the network gets cannot be connected to any real-world entity. It may
be possible to analyse the transaction flow, but this does not equate with
finding the real-world identity of the network’s users. Finally,
cryptocurrencies do not have any gatekeepers or permission structures. It is
simply software that you download for free and once installed; you can trade
any cryptocurrency supported by the software.

Big Data and AI

Machine learning (essentially the most lucrative form of AI for business
currently) and big data go together. Machine learning is already being used in
the financial sphere to detect strange activity on bank accounts such as
foreign transactions or large sums of money being either withdrawn or
deposited.

This is done by a few highly specialised algorithms that monitor
behaviour patterns in your account and then aggregate them to detect anomalies.
This is, of course, user specific. A millionaire’s daily spend will obviously
differ from that of a waitress or office worker.

How big data enters this is through similar pattern recognition. Unlike
allowing machines to carelessly make trade options and sink the stock market,
sending the world into recession as happened circa 2008; machine learning is
now more sophisticated and has extensive parameters which prevent something
like that ever happening again.

What machines now do is analyse data from a varied data set (all a database’s relevant entries) and create models and predictions based on that. These predictions still have a long way to go and still require a significant amount of human interaction to decipher, but they help to condense a lot of information into understandable chunks or metrics.

From there, seasoned professionals can then make their analyses and recommendations as they see fit. So, for a large financial company such as a retail bank or investment firm, this is invaluable information which would have taken many manhours to efficiently collect.

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