Chapter 8

Acclimating to the App Mentality

IN THIS CHAPTER

Categorizing FinTech apps

Looking at the FinTech app landscape

Navigating the nonretail side of FinTech apps

Creating a GUI framework and a workflow engine

There’s an app for that.

In 2008, when Apple released the iPhone 3G, a technological evolution occurred as people started seeing smartphones as more than just phone call and text message tools. The idea that you could extend a smartphone’s functionality by installing apps from an App Store was a game changer. Apps gave consumers more choices. For simple computing tasks, they no longer needed traditional PCs, because they could use their phones instead.

As smartphones began to represent larger and larger shares of the personal computing device market, programmers started developing with a mobile first mentality, also known as an app mentality. In other words, when they planned new software, they began to first consider how it would work on mobile devices, because that was the kind of device that the largest segment of their target audience would be using.

This app mentality has been a significant driver behind the disruptive nature of FinTech. Companies that hope to reach consumers must develop software that goes where they are — and where they are is online, on their smartphones, and connected to the cloud. This chapter looks at the various types of FinTech apps that consumers want today and provides some tips for planning and building such apps.

Introducing Types of FinTech Apps

App is a shortened form of application. An app is software designed for end users that enables them to do a certain specific task or a group of netted tasks easily. Though apps were initially supposed to be platform and media agnostic, the term has come to refer specifically to applications built for mobile devices. However, the concept of small, task-focused applications targeted to specific types of end users is becoming more pervasive throughout all of modern software design.

Here are some specific types of apps that you may encounter in the world of FinTech:

• Web apps: Web apps are stored on and run from web servers. Users don’t have to download anything to run them. A web app delivers a consistent user experience through its interface, regardless of the platform being used to access the server. A web app differs from a regular web page in that it’s interactive and can be user defined.
• Native apps: A native app has been developed to run on only one kind of device or platform, such as only iOS or only Android. A native app typically requires you to download and install it on the device. It’s called a native app because it’s written not only for a specific platform but also generally in a language that’s specific for that platform.
• Mobile apps: As the name implies, these run on mobile devices such as smartphones or tablets. They’re usually native apps designed for a specific mobile operating system (OS).
• Hybrid apps: A hybrid app acts like a native app, in that it must be downloaded, but it’s written in standard development language like HTML or Java. This makes it easier to develop, maintain, and use.
• Killer apps: Killer apps are native apps that are so compelling and unique that they drive users to become loyal to the specific platform on which they run. For example, if the app is available only for Android, some people may switch from iOS to Android just to be able to use it.
• Legacy apps: In technology, legacy is just another word for “old and out of date.” Legacy apps are past their prime; they may no longer be supported or may be built in obsolete languages or for obsolete platforms. They continue to exist because they serve a specific function that either is not easily replaced or would be too expensive to re-create in a modern version.

Surveying the FinTech App Landscape

To understand how the app mentality is driving development in all areas of the capital markets, it’s important to look at some of the first mover sectors that defined the rise of FinTech in the past ten years.

Digital banking

Digital banking is one of the largest areas in FinTech, with challenger banks having raised more than $3 billion in 2019 according to research firm CB Insights. FinTech is attacking every core banking operation, offering focused services for savings, student loans, small business services, and credit cards.

Traditional retail banking is under attack due to the rise of Internet banks that can handle all transactions through apps and anonymously advise customers. Users can open savings, checking, and credit card accounts via an app and can interconnect all accounts without any human intercession required. These banking apps track each transaction and auto-generate transaction and payment statuses daily. Through machine learning and artificial intelligence (AI; see Chapter 12), the apps can also develop a sense of the user’s fiscal patterns and spending requirements and offer banking assistance tailored to those patterns.

Some key disrupters in digital banking include Chime (www.chime.com), Aspiration (www.aspiration.com), Varo (www.varomoney.com), and Simple (www.simple.com).

Wealth management

One of the more visible areas in FinTech has been in wealth management app development. These apps and their associated banks have opened the market to a new group of investors and have challenged traditional wealth management institutions. They offer benefits such as robo-advisors (algorithmic trading) for individual investors, low minimum balance requirements, and the ability to open accounts with very little investment.

If you use Merrill Lynch, TD Ameritrade, E*Trade, Schwab, or Stash Wealth, you’re already receiving advice that has been generated by AI apps. Some apps now will automatically invest your “free” money using algorithms you’ve enabled.

Some key disrupters in wealth management include Betterment (www.betterment.com), Robinhood (https://robinhood.com/us/en), Nutmeg (www.nutmeg.com), Raisin (www.raisin.com), and MoneyLion (www.moneylion.com).

Payments and peer-to-peer money transfer

The payments sector is hot because it has such a large potential user base. Nearly everyone wants to be able to pay for small purchases more conveniently. Being able to simply tap your phone to pay for a cup of coffee or transfer money to a friend has had a profound impact on banking. The loss of transaction fees has driven many financial institutions to partner with FinTechs or even develop competing offerings.

E-payment systems now enable completely electronic transactions. Cash is rapidly becoming an anachronism. Many of the Scandinavian countries have moved off cash and into plastic and electronic payments. This trend is very appealing to governments because it makes it more difficult for people to bury money or to create underground economies.

Peer-to-peer (P2P) payment apps can provide near to real-time transactions. It’s now all about immediacy and seamless user-friendly experiences. Using blockchain validation ensures security and immutability (see Chapter 7 for more about blockchain).

Some key disrupters in payments include Stripe (https://stripe.com), Venmo (https://venmo.com), TransferWise (https://transferwise.com), and Square (https://squareup.com/us/en).

Lending

While the alternative lending market isn’t new, FinTech apps have extended credit availability to a much larger pool of individuals and small businesses. The innovation in this sector is less the apps themselves and more about the disruptive business model these companies are utilizing. AI and Internet data mining make it possible for first-time borrowers to meet the criteria to secure loans without any significant credit history. Specially developed algorithms are able to consider social media and other history stored on the Internet to advance new credit recipients.

Service to the small-to-medium enterprise (SME) market has been greatly enhanced through the introduction of AI into organizations like OakNorth (a U.K. online lending firm) that utilize AI to build smart apps for the SME lending business.

Some key disrupters in lending include SoFi (www.sofi.com), Credible (www.credible.com), Zopa (https://zopa.com), Funding Circle (www.fundingcircle.com), Banking Circle (www.bankingcircle.com), Credit Karma (www.creditkarma.com), and Upgrade (www.upgrade.com).

Looking at the Nonretail Side of FinTech Apps

As we indicate in previous chapters, FinTech has driven disruptive changes in the banking industry. Those changes have been motivated by disgruntled customers and by innovation attempts that have taken too long to get to the marketplace. FinTech apps offer speed to market, ease of use and simplicity of design, customer empowerment, and workflow and functionality modification to meet end-user desires. The following sections discuss some ways outside of the mainstream financial services that FinTech apps empower their internal users.

RegTech

The primary role of regulation in financial services is to protect the consumer, but regulations also protect the entirety of the financial system and the economy of a country. In response to the financial crash of 2008, many new regulatory regimes were created, affecting the entire financial services industry.

Regulatory requirements have become more complex and numerous over the last decade, especially for international enterprises, and companies are understandably nervous about them. Nobody wants to pay more taxes or be exposed to fines and penalties because they failed to comply with a regulation they weren’t even aware existed. Regulation frequently introduces new costs, and businesses look for ways to minimize those costs. As a result, a new industry sector has arisen, RegTech (regulatory technology), to assist institutions with regulatory compliance. Institutions are looking externally for FinTech companies to provide solutions to help comply with regulations, shore up workflows and compliance gaps, and do those things more cheaply than they could with in-house builds. RegTech helps manage a business’s regulatory compliance via technologies such as big data analytics, AI, machine learning, and blockchain.

This developing industry is not yet driven by the need to deploy mobile apps. They are building their base by catering to the more traditional client application approach, though some have been adding mobile capabilities to their infrastructures.

Some key disrupters in RegTech include Trulioo (www.trulioo.com), Convercent (www.convercent.com), and Palantir Technologies (www.palantir.com).

Capital markets trading

Capital markets functions such as trading have long been a profitable part of many financial institutions’ offerings. However, increased regulatory burdens have decreased the return on equity for trading operations, and financial institutions are lately looking for ways to cut costs and increase automation.

Driven by the app mentality, end users demand the information they need to make trading decisions when they want it. Many of these decisions require sophisticated analytics and significant compute resources. Legacy systems have been deficient in meeting end-user requirements due to a reliance on batch processing.

Cloud services (see Chapter 6), real-time processing, and artificial intelligence (AI) and machine learning (see Chapter 12) have all opened the door for FinTech in this segment of financial services. New, modern architectures explicitly designed to take advantage of the cloud’s scalability have empowered new players to enter the market. And many financial institutions are glad to have their help instead of trying to build their own technology solutions in-house.

Although AI is still very much a nascent industry, it’s quickly gaining traction in the capital markets space. According to October 2019 data from Greenwich Associates, 44 percent of capital markets professionals globally say their firms are already using AI in their trading processes. (See www.greenwich.com/press-release/artificial-intelligence-permeating-global-capital-markets for more information.)

AI promises to provide numerous benefits to any financial services firm that embraces it. The potential advantages include improved operational and cost efficiencies, enhanced client services, improved data and analytics, as well as increased profit and revenue generation. For portfolio managers, adding AI’s high level of computational and algorithmic complexity to portfolio management, including for trade decision-making and execution, means they may ultimately use AI to find alpha, build custom portfolios, improve portfolio allocation, rebalance portfolios, and mitigate risk.

The most important application of AI in the financial services sector may be risk management. AI could be a game changer for risk management. The capital markets have been hammered with a regulatory tsunami since the financial crisis of 2008, and as a result, a more stringent and prescriptive regulatory environment is having a significant impact on front-office risk-management technology. Today, some institutions are putting AI to work to augment their current front-office risk-management processes.

This is where machine learning, a type of AI, comes into play. Machine learning models have the ability to crunch enormous calculations and analyze huge amounts of data with more granularity and deeper analysis. Doing so can potentially greatly improve analytical capabilities in risk management and compliance. It can help traders make more informed decisions not only at a securities level but also across their entire derivatives book of business. By incorporating a broader set of financial and nonfinancial data, AI applications in risk management could include specific functions, such as identifying the right counterparty with whom to trade, discovering potential counterparty risks, unveiling additional costs within a portfolio, or identifying new trading patterns that could be used to adjust trading strategies — all in more efficient and automated ways.

Some key disrupters in capital markets trading include Numerix (www.numerix.com), Halo (www.haloinvesting.com), and CloudMargin (https://cloudmargin.com).

Building a GUI Framework

The most successful FinTech apps are intuitive to use. Successful apps tend to be graphical in nature and present a dashboard view of the most critical information the user needs when first opening the app. That’s important because most apps don’t include detailed documentation — and if they did, users probably wouldn’t read it anyway. Even complex apps should be able to effectively communicate their use within five or six tutorial screens.

The importance of a good user interface (UI) drives the way developers create apps. In many cases, app development starts in Adobe Photoshop or even in Microsoft PowerPoint before a single line of code is written. In other words, developers first think about how the screen will look and only later think about how it will behave.

Another important element of a successful app is that it usually addresses a single use case. The app’s purpose is clearly defined, and users tend not to expect more from the app outside of that narrow scope.

In the following sections, we explain how a graphical user interface (GUI) provides a good user experience (UX) and how to create a successful GUI framework.

Introducing the GUI

Companies pay a lot to protect their brand. They do so by creating a good user experience (UX). The UX is the overall design of the software, with the main goal of solving the user’s problems via an intuitive experience.

Every interaction a consumer has on the Internet is logged somewhere. Business intelligence tools (see Chapter 9) can mine that data to tell a company how successful it is at giving the customer a good experience. In the olden days, companies used efficiency experts to determine the best set of commands needed to make a customer happy. Today, they use metadata, user logs, AI, and machine learning to hone the look and feel of their software. With website development, the rule of thumb is that a user should never be more than four clicks away from a resolution.

A graphical user interface (GUI) is a user interface based on pictures rather than text. Most modern end-user operating systems are GUI-based, such as Windows, macOS, iOS, and Android. Before there were GUIs, developers and users navigated operating systems and applications via command lines. Some of the text commands are still there, but with a GUI, they are behind-the-scenes. Thank goodness we don’t have to type HTTP or Python commands at a prompt to surf the web!

A GUI is based on the integration of the user experience with the following tools and basic components:

• Icons: Small clickable pictures that serve as shortcuts to files or addresses.
• Desktop: The background behind the active application, or the background behind the icons on the main screen (for example, on a mobile device).
• Windows: Rectangular areas that define a particular application or dialog box within a larger area such as a desktop. On mobile apps, you don’t usually have windows because apps run full-screen.
• Menus and toolbars: A list of commands or options you can select. A menu is usually text-based; a toolbar is usually icon-based.
• Widgets: Can be any element of interaction like a scroll bar or a drop-down menu.
• Pointer: The arrow or other marker that represents the mouse or trackball’s control. On a mobile device, you typically use your finger or a stylus as a pointer so there’s no onscreen pointer.

Everything that you can do using a GUI has associated code. For example, when you click or tap an icon to run an app, the command for starting that app executes. The code behind every GUI is created in standard formats and can resolve to text or graphic. The uniformity of these standards permits data sharing.

Getting the GUI right

Underpinning the GUI is the GUI framework. The GUI framework is a set of software tools utilized to provide developers a faster and more consistent way to deliver GUI-based applications. A GUI framework has many components and many choices of solutions that can be utilized and customized to an institution’s requirements. Using standardized GUI frameworks can save developers months of work and allow the development of new user experiences in a matter of weeks.

GUIs are built in many languages and out of the box. Open source libraries exist to make the creation of a GUI framework easy. Python alone has four basic technologies that it uses as “bindings” across its interfaces: Gtk, Qt, Tk, and wxWidgets. (Flip to Chapter 10 for more information on open source.)

A GUI framework standardizes the objects taken from other more standard programs found in operating systems (like fonts and jpgs) and wraps them in an agnostic form (like classes or handles) making them universal. Figure 8-1 provides a basic look at how a GUI framework may operate.

© John Wiley & Sons, Inc.

FIGURE 8-1: The relationship between the user, the user interface, and the APIs that call the functions and data.

Each browser has its own set of metadata that affects the way the user sees and accesses information. Application programming interfaces (APIs) are used to translate between the way a specific GUI has been coded and a nonnative environment you want to run it under. The API defines the way the components interact in a nonnative environment. The API provides a consistent GUI experience across the different browsers or media. As we note in Chapter 4, the API provides the building blocks that create a consistent user experience in different environments.

Establishing the Requirements Needed in the Development of an App

As we say earlier, there has lately been a shift in the way applications and systems are developed. In the past, the focus was on the programming, and the business drivers were often lost in the process. Business drivers came at the end instead of at the beginning of the requirements gathering. Nowadays, though, business requirements drive the development process, and the workflow can make or break any app’s value.

Keep in mind that apps are developed to solve small programmatic needs with small-footprint, singular experience/function applications. Essentially, an app is all about the workflow. Because workflow is such a critical component of app creation, myriad tools enable developers to create workflows without writing one line of unique code.

The concept may start from a simple sentence on the back of an envelope, but before one line of code is written, you need to understand that specific steps are required for it to be successful. With the development of more complex apps, a requirements document with a unified modeling language (UML) diagram is a good first step. A UML is a visual representation of all the elements that will go into the app. All actions, roles, and classes must be defined there. Having a complete diagram can speed up prototyping and the workflow development. The requirements document must outline the minimum viable product (MVP), which will be reviewed and enhanced with each iteration. The goal of an app’s development process is to define the smallest set of operations that complete the functional requirements. The UML and the requirements document will define the workflow.

Because of the heightened importance of business needs, a workflow engine has become essential to developing a successful app. A workflow engine is software that is designed to manage business processes. These applications have three main functions: determining the validity of executing a task, checking the permissioning of the user who is doing a task, then executing that task.

For example: When you invest money via your favorite wealth management app, it initiates a workflow engine involving security selection, order selection and execution, confirmations, and portfolio rebalancing. It’s the workflow engine that’s moving one stage to another.