ABCD’s Driving FinTech – Info News

During the last few years, alternative finance has been slowly transforming the offering of financial services and the providers of such services in two main ways. New business models and new technologies. It’s critical to understand the four key and interrelated technologies that have allowed alternative finance to flourish. These can be known as the ABCDs driving FinTech, namely, artificial intelligence, or AI, blockchain, cloud computing, and data.

Banks for the longest time have relied upon and generated a tremendous amount of information. These include information from and about customers, their identity, their transactions, their net worth and even their relationships and location. Yet, in the old times, a lot of this was gathered by using paper forms filled by customers and bank staff and not easily searchable or manipulated for analysis. The digitization of information from paper into data, from written to digital ones and 0’s means that such information can more easily stored, transmitted, searched, processed, analysed and displayed. This digitization allows for online capital marketplaces to be more easily created and operated where gatherers can more cost effectively process and analyse the data for those who need the capital. Then they can display the relevant information on the new platforms for the potential providers of capital to make their own investment decisions. At the same time, digital form filling and tracking of the online customer activity allows both these online platforms as well as, virtual banks and e-brokerages to scale more quickly with less manual labour and space resources. Customer data includes online behaviour such as the time and location of logging in and transactions as well as, other online activities such as web browsing, e-commerce and social media use. Increasingly, offline behaviour is also being tracked through data from internet of things for IoT devices such as wearable smart watches, smart cars and smart home devices such as Amazon Echo. For example, in the world’s biggest retailer, Walmart, 2.5 petabytes of data is processed every hour. One petabyte or pb is 10 bytes with 15 “0”s afterwards. Customer data has been called the new oil that is being bought and sold by gatherers and users and increasingly fueling the AI engine.

In the past, businesses such as financial institutions had to build their IT systems using different enterprise level software that was developed or licenced at high cost over time and hosted on large servers on premises. However, with the birth of cloud computing, software resides at data centres on servers run by companies that are created to manage such servers which also provide value-added services such as cyber security protection. This means that new businesses such as alternative financial providers no longer need to dedicate high capital for expensive infrastructure and can focus on improving client experience and can dynamically scale their server usage in accordance with their rates of growth.

Cloud computing also allowed new business models to thrive. Software as a service or SaaS businesses bypass the traditional vendor model of software development and sales that require marketing software licences at higher upfront fees and then again each time a new version or upgrade is introduced. Software that resides in the cloud can now be marketed at a lower upfront cost based on a subscription model. And software upgrades can be automatically made on a continuous basis which gives the client one more reason to switch vendors. This means that online capital marketplaces as well as, startup virtual banks like UK Starling Bank require less upfront cost to prototype new business models. This also means that user interfaces can roll out more quickly and cost effectively while scaling to new jurisdictions. In addition, the cloud enables connected IoT devices to gather data and stream more services including financial services to customers through new interfaces like smart watches, voice-activated speakers, smart homes, and smart cars. Cloud computing now can effectively offer institutional level technology support to retail businesses.

Distributed ledger technology or DLT continues to have an evolving impact on alternative finance. The oldest example of double-entry bookkeeping can be traced back to Franciscan Friar Luca Pacioli in1494. Luca Pacioli is an Italian mathematician who is called “the father of accounting and bookkeeping” in Europe. He was the first person to publish work using the double-entry system of book-keeping which allowed for reliable documentation of both creditor and debtor in a standardised manner. The white paper on Bitcoin by the mysterious Satoshi Nakamoto in 2008 was similarly revolutionary in establishing a cryptocurrency that seeks to solve the double spending problem intrinsic in a currency based on software without the need of a trusted authority or central server. Nakamoto created a ledger that is distributed via a peer-to-peer network which records transactions by way of blocks. Each block is validated by different node computers in the network through solving cryptographic mathematical puzzles, at which time a new block with a new cryptographic hash, timestamp, and data would be added to the chain which is transparent to all users. Data on the block is immutable and effectively cannot be altered unless all prior blocks in the chain are altered by consensus or agreement of the network majority. Blockchain is the underlying technology behind cryptocurrencies that have expanded dramatically beyond Bitcoin. In this way, this technology has created a new form of digital asset as well as a new alternative finance method to raise capital for new projects, with the so-called crypto exchanges turning into new forms of online capital marketplaces. In addition, blockchain technology could form the basis of new capital markets infrastructure. NASDAQ is using blockchain technologies to secure record keeping of ownership of private companies and transfers. In December 2017, Australia’s ASX announced that it would replace its stock exchange registry, settlement and clearing system with blockchain technology. An even more ambitious use of blockchain technology could be the creation of decentralized autonomous organization (DAO), fully automated business entity (FAB), or distributed autonomous corporation/company (DAC). DAO, FAB, and DAC are different names for the same concept. DAOs are companies that are self governed organizations that allow for automatic execution upon specific conditions via smart contracts, with innovative governance mechanisms based on open-source software that is on the computers of the stakeholders. Even though this is far fetched, if implemented to its fullest extent, DAOs and its efforts to disintermediate could impact not only the venture capital market but also the very concept of the joint stock company and even some functions of government.

The concept of intelligent human-like machines was mentioned in old Greek myths of Hephaestus, the blacksmith who manufactured mechanical servants, and the bronze man Talos who incorporated the idea of intelligent robots. The term artificial intelligence was coined at the now famous Dartmouth summer research workshop in 1955. For AI, there are two broad types, the narrow or weak AI that relates to algorithm performing specific tasks, and the general or strong AI that reflect broader human intelligence and decision-making. Also, there are different strands within AI, including Natural Language Processing or NLP which relates to language, and Machine Learning where systems learn from experience by being trained with data as opposed to being rules-based. There are many techniques within Machine Learning, including neural networks which comprise from nodes of weighted interconnected ideas inspired by the human brain, and deep learning, which refers to algorithms based on neural networks arranged in deep layers. Computer vision for image recognition is a good example of machine learning. AI blossomed due to a sequence of events that made both Fortune and Forbes name 2017 the year of AI. First, instead of expensive large supercomputers required for the AI algorithmic processing, researchers started using relatively cheap graphical processing units or GPUs originally developed for video games with increased computational power when used in parallel. Second, data storage cost continues to fall while data is being gathered at alarming rates through online activity and connected devices, thereby allowing for more structured and unstructured data to be gathered, stored, and used to train the machines. Third, most major cloud companies, such as Amazon’s AWS, Google Cloud, Microsoft’s Azure, IBM Cloud and Alibaba’s Aliyun incorporate AI into their services, often including machine learning frameworks on some open source basis to allow their clients to experiment and incorporate into their operations. For example, AI is rapidly changing Alternative Finance user interfaces, from facial and voice recognition to biometric identity management to chatbots that can provide personalised recommendations. Algorithmic matching of needs, pricing, and predictive analytics are also being used. AI also allows some alternative finance companies to create new business models that focus on analytics of the customer data rather than building platforms to provide financial fund flow. For example, some Chinese companies which started primarily as P2P lending companies have pivoted to provide credit analysis and scoring that serve the marketplace lending conducted by institutional investors and lenders.

These technologies are why the FinTech industry is one of the most exciting industries to follow for the next few years.