The emerging technologies that shape the financial industry
By Dr Joerg Ruetschi, Chief Operating Officer at Cosaic
Technology management has become a critical success factor in financial services. The topic had up to the Global Financial Crisis (GFC) a shadow existence in many institutions. Most financial institutions relied on core systems that were often developed more than 30 years ago, leading to a patchwork of different system applications. These legacy systems provide stability but are inflexible to adapt to new requirements. After the GFC when revenues in many previously profitable areas tumbled and the cost–income ratios increased dramatically, the real operational costs of many of these outdated systems became transparent. Established commercial and operating models with their profitability thresholds were further challenged by the incoming regulatory agenda through higher capital requirements and scrutiny. Investments of several billions of US dollars have been required to modernise the platforms.
Emerging technologies, often subsumed under the term “Fin-Tech”, created unseen momentum in innovation over the last 10 years. FinTech is the shortened version of the phrase financial technology and became a synonym for the initiatives of a dedicated start-up community that developed new services and solutions outside of incumbent financial institutions. However, a broader definition of FinTech applies the abbreviation to the entire financial technology universe in an industry-specific application. The following article aims to clarify which are those emerging FinTechs and how they shape the future of the financial industry.
The incoming technology agenda has the potential to re-innovate the industry and put it back on a growth path. Emerging technologies have fundamentally transformed operating platforms, infrastructure and decision-making frameworks. Open Finance with its collaborative architecture models allow incumbent financial institutions to specialise in their core competence and to integrate best-in-class services with the objective to provide customers a comprehensive experience through core platform offerings. Decentralised finance (DeFi) has become a broadly used term for experimental forms of finance that utilise smart contracts on distributed ledgers to perform financial services functions. The DeFi ecosystem revolves around decentralized blockchain applications that provide similar traditional financial services but do not rely on a traditional intermediary model. Transactions can directly be executed between participants which will be at the core of a new financial infrastructure. The commercial interactions and the customer experience with financial institutions will fundamentally change. Most of today’s administrative functions will be replaced by efficient technology solutions. Those technology solutions are built on a number of key technologies that define the three pillars’ of the financial industry’s transformation agenda.
Advanced software and operational efficiency (the first pillar)
Advanced software solutions such as application programme interfaces (API), cloud computing (CC) and interoperability (smart desktops) shape today’s open architecture models. Open architecture has substantially improved operational efficiency through automation and collaboration as the first pillar of transformation agenda. API is a software and web development concept that represents a set of clearly defined methods of communication among various components. They make it easier to develop computer programs by integrating the underlying building blocks, and drive connectivity and standardisation between third-party applications. Within a typical banking technology architecture, software systems are typically isolated and the functionality of one system cannot be accessed from the other system. API provide the opportunity to connect these separate software entities. By connecting software, API connect businesses with other businesses, businesses with their products, services with products, or products directly with other products. They further facilitate the share of data between systems.
CC is the on-demand network access and system resources availability to many different users over the internet. It is applied especially to data storage and computing power, and has added completely new features to technology infrastructure and software applications. The technology enables financial institutions to dynamically scale their data storage, computational power and bandwidth. It leads to a huge advantage compared to previous solutions around data centre and servers. CC relies on the pooling and sharing of configurable computing resources to achieve economies of scale and coherence. When multiple users access the same virtual resources in the cloud such as software, storage or virtual machines, those resources know multiple tenants. Virtual applications can be installed with their own operating systems and different set of applications. Different service models emerged such as software as a service (SaaS), platform as a service (PaaS) or banking as a service (BaaS).
Interoperability brings different software solutions and applications together through one unified customer experience, the Smart Desktop. Smart Desktops create intelligent workflows with customized workspaces. Its original focus was on the integration of web applications with other web applications. Open-system containers were developed with the objective to create a virtual desktop environment in which these applications could be registered and then communicate with each other. Interoperability has now evolved into full-service platform solution which includes container support, basic exchange between web and web but also native support for other application types and advanced window management. The unified customer interface with different applications make the management of complex workflows much easier. Financial institutions have targeted full automation of front-to-back processes and services, addressing the high manual work of complex product integration. Interoperability allows cross-application data sharing in an instant and eliminates manual re-entry and error rates. This optimisation of workflows leads to substantial gains in effectiveness and efficiency in an open architecture framework.
Artificial intelligence and augmented decision making (the second pillar)
The second building block is artificial intelligence (AI) with focus on big data and advanced analytics that augments decision making, the second pillar of the transformation agenda. AI seeks to build autonomous machines that can carry out complete tasks without human intervention. There are many and varied definitions of AI and the term is often interchangeably used with machine learning (ML).
ML is a key field of study of AI that uses algorithms for the analysis, manipulation, pattern recognition and prediction of data. Algorithms are the mathematical procedures that ML applies to interpret data in specific ways and create predictable output based on identified patterns. Big data is a collective name that refers to the use of immense datasets for ML applications. It covers relevance, complexity, and depth of a financial institution’s data that come from internal and external sources. ML allows to process large data with mathematical accuracy and objectivity which leads to unbiased results, substantial efficiency gains and new insights. Most financial data such as accounting statements or transaction records are structured. Unstructured data, on the other hand, have no predefined organisation form. They can be found in emails, reports, news, social media, or any other form of written and oral communication. Unstructured data can be captured and processed by natural language processing (NLP).
NLP is a branch of ML that facilitates the interactions between computers and human natural languages. It applies the principles of linguistic structure and breaks down sentences into their elemental pieces to identify semantic relationships among them. The algorithms detect the polarity of sentences within a range of positive, neutral, and negative on a respective target entity. Sentiment data are an output of this process. It uses large amount of language and evaluate its positive or negative connotation through a predefined event methodology. The event classification is shaped by key words that imply a specific attitude associated with statements made in the respective language. News and social-media blogs can be analysed accordingly and establish a view on the sentiment of the statements in the text. Alternative data sets are established through which specific insights are gained during the decision-making process.
Through a probabilistic ML methods, such as Bayesian inference, these processed forms of unstructured data (or alternative data) are brought in the structured context of traditional quantitative analysis. Bayesian probability theory allows the modelling of uncertainty in a sensible way. It measures unfamiliarity and enables appropriate subsequent decisions to be made under the respective circumstances assessed by the model through an underlying hypothesis. The probability for this hypothesis can be updated as more data become available during the process. This enables the simultaneous assessment of risk and uncertainty. The implementation of an overarching ML algorithms then optimises the decision analytics. This allows more comprehensive, objective and accurate decision making through predicting specific political, macroeconomic and/or corporate events. The methods can be applied to identify risks early (such as a pandemic and an unexpected war) and extrapolate certain trends. The most obvious use case is in investment and risk management but it can be more broadly applied to businesses and social contexts, such as the analysis of environmental, social and corporate governance (ESG) issues.
Blockchain and digital financial innovation (the third pillar)
The third emerging technology is blockchain, the main industry application of distributed ledger technology (DLT). DLT is the parent technology behind blockchain that has found a broad application in financial institutions. It facilitates identity management, value storage, and back‐office operations such as settlement. However, it is mainly known for financial innovation and speculation through cryptocurrencies such as Bitcoin and Ether. Both cryptocurrencies follow the same blockchain principles but have different characteristics in their implementations. Bitcoin is written out as Bitcoin code, run by Bitcoin software which creates transactions containing data about Bitcoin coins that are recorded on the Bitcoin blockchain. Accordingly, Ether is a multitude of tokens that are recorded on Ethereum blockchain.
Blockchain is to be understood as a bunch of protocols (rules) that define and characterise its functioning. These protocols can best be articulated in a computer code which in turn can be compiled into a software that enacts those rules and makes them operate. This is how ownership is represented and recorded, what constitutes a valid transaction, and how participants can operate on the respective blockchain network. Transactions on a blockchain network apply a mathematical mechanism that is known as cryptography. Its most well‐known use is the encrypted data exchange (encryption) that defines the process of encoding an information in a format that only authorised parties can access it. Although nothing on the Bitcoin network, for instance, is encrypted by default, the technology applies asymmetric cryptography with its public and private key schemes. Together with hashing and digital signatures, private and public keys are crucial technical components of blockchain transactions. Mining is the process of validating by adding transactions to the existing blockchain ledger distributed among all members of the blockchain. It involves creating a hash of a block of transactions that cannot be easily forged, protecting the integrity of the entire blockchain.
Smart contracts are computer protocols intended to digitally facilitate, verify, or enforce the negotiation or performance of a contract without third‐party involvement. Their implementations become today trackable and irreversible through blockchain networks. Several blockchains have implemented types of smart contracts with Ethereum as the most prominent representative. In a smart contract, many kinds of contractual clauses are partially or fully self‐executing, self‐enforcing, or both, which makes it very attractive in the use of financial instruments with specific cash flow and settlement specifications. They aim to provide security that is superior to traditional contract law and to reduce other transaction costs associated with contracting.
Tokens represent a unit recorded on a blockchain, and is often used in reference to all digital assets. However, as the terminology is evolving, a narrower definition for token is emerging. There are coins such as that are tracked on the cryptocurrencies’ respective blockchains. Then there are tokens that are tracked within smart contracts on any blockchain such as Ethereum (as the most widely used). The native tokens (i.e. crypto currencies such as Bitcoin and Ether) have an intrinsic value by themselves and are not backed by an issuer or asset. Asset‐backed tokens represent ownership of a financial or physical asset. These are often referred to as non-fungible token (NFT).
Blockchain is in the process of reshaping the financial industry in a series of a broader infrastructure application that started a new chapter for (digital) financial innovation. Different smart-contract use cases facilitate the synthetic trading of assets, historically represented by derivatives contracts either traded at regulated exchanges or over the counter. They replace traditional derivatives structures with their legal and collateral requirements. Stablecoins are crypto‐based assets that are linked to and redeemable in fiat money (a currency such as the USD), commodities (precious metals such as gold), and any other underlying assets. The coins are usually issued by an independent third party. An initial coin offering (ICO) is the cryptocurrency equivalent to an initial public offering (IPO). Investors receive a blockchain equivalent to a share which is a cryptocurrency token. Blockchain has further been implemented for settlement of securities transaction. The objective is to remove settlement and counterparty risk to increase speed and reduce financial, operational, and frictional costs.
Replatforming and specialisation
The financial industry’s ongoing transformation agenda led to the dedicated discipline of technology replatforming. It replaces old with new systems while integrating the emerging technologies in the design of operating platforms. In this new world, technology-enabled service components allow financial institutions to differentiate and gain a competitive market positioning. An open architecture model decomposes the value chain and separates the core platform from the service offering. It enable the access to large data pools, internal and external resources as well as regulatory compliant infrastructure, and allow the integration of best-in-class services from third-party providers. This form of open finance allow financial institutions to focus on their core capabilities. There is inherent value in specialised finance capabilities such as dedicated lending, trading, and related risk transfer across specific client segments and product portfolios. Today already specialty finance businesses operate at a much lower cost-income ratio and higher return-on-equity targets than large-scale, aggregated financial businesses. However, this requires substantial investments and the break-up of the industry’s existing organisational structures in a highly collaborative approach.
Dr Joerg Ruetschi is transformative technology, value-creation and turnaround specialist, and author of new book Transforming Financial Institutions (Wiley)
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