Banking Software Development Guide: Development process, tech, trends

The global economy is fragile due to various factors, including supply chain disruptions, inflation, tightening monetary policies, China vs USA wrestle over Taiwan and Russian invasion of Ukraine. Geopolitical risks, deglobalization, and changes in payment systems are leading to a new economic order.

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Deloitte’s analytics lay it straight: “Global GDP growth in 2024 is likely to be muted at best—barely above 3%, compared to 6% in 2023. 


Good news: both US and European banks withstood rigorous stress-tests at the highest level. For example, US banking system “have sufficient capital to absorb more than $600 billion in losses,” which exceeds loan losses attributed to 2008-2009 financial crisis. 

In short — the economy is in the recession, the future is unstable, but US and European banking systems have accumulated enough “fat” to last through a lean season. 

Resilience. Margin of safety. That’s why digital banking service market is so competitive now. And if you plan to enter it, let alone, disrupt it, you need to do it right — hit the trend, offer what’s necessary and build an efficient software development process to roll out the product faster than the competition. 

For easier navigation through this article on banking applications and software, use this outline:

  1. Banking industry trends
  2. The timeline of fintech explosion
  3. Types of modern banking software
  4. Key technologies in banking software development
  5. Banking software features
  6. The importance of UI/UX in banking app and web development
  7. Finance software development lifecycle
  8. Final thoughts

Let’s start with a reality check on the trends that will drive the industry in the upcoming years. 

Too many software projects fail due to not aligning with current industry trends. In fact, nearly 70% of tech projects face challenges when not updated with the latest market insights. Make sure your software development plan isn’t just technically sound, but also relevant and timely. Here’s what you need to know before assembling a financial software development team.

No matter the changes, challenges and developments, financial industry is first of all depends on what is going on in a banking sector. 

Retail Banking

  • There’s a growing competition among card issuers, with 23% of US consumers likely to switch their primary cards in the next two years.
  • The rise of super apps and non-card payment options, such as “buy now, pay later” (BNPL), are also influencing the market.

Commercial Banking

  • Despite having a loyal client base, commercial banks face competition and need to respond to changing macroeconomic forces and corporate customer needs.
  • For big players, opportunities come from financing the transition to a carbon-neutral future (complex, costly, challenging for smaller operators).

Transaction Banking

  • Demand for cash management services is on an upswing, signaling profits over profits.
  • However, the geopolitical landscape, marked by its unpredictable nature, is reshuffling the deck for cross-border payments.

KMPG offers a comprehensive vision for those interested in making money on banking software projects or software development services in this sector.

Adoption of Cloud and API Technologies in Online Banking

  • Commercial banks are partnering with modern infrastructure providers to transform legacy technology.
  • 68% are already monetizing API development and plan to intensify the use of this tech.
  • An additional 20% are planning to do so in the next 12 months.

AI and Machine Learning

  • AI and ML will help sales and marketing teams identify prospects, predict customer needs, enable dynamic deal pricing, and automate decision-making processes.
  • Respondents KPMG addressed rank AI as the most important technology to differentiate themselves in the commercial banking market.

Distributed Ledger in Commercial Banking

  • The next 10 years are likely to see a shift from centralized to decentralized systems.
  • Blockchain-based trade finance networks help commercial banks eliminate operational friction and reduce fraud.

Continuing analyzing KPMG take on the banking landscape, let’s summarize the general trends that may be relevant for finance software development in 2024 and beyond.

A Successful Connected Enterprise

  • Banks need to adapt to a connected operating model to approach change effectively.
  • High maturity commercial banks that invest in specific capabilities are more likely to develop compelling customer value propositions, harness data and analytics, and operate efficiently.

Small and Medium-Size Enterprises (SME) Segment

  • SMEs play a significant role in global economies, especially in developing markets.
  • They remain an underserved segment, so if you plan to develop a banking project with a swift rollout and limited budget, this may be your target audience. 

Future Business Models

  • Banks are expected to evolve into platforms, providing a mix of business products and services. Investing in the digital banking should always go side by side with readiness to scale. 
  • Three dominant business models are anticipated: the reimagined digital commercial bank, Banking-as-a-Service models, and platform providers.
  • Banks should focus on innovating relationship models, transitioning to new ecosystems, transforming operating models, and delivering services supported by AI.

Trust

  • Sustainability and ethics in business operations can significantly enhance customer trust.
  • Banks are focusing on green finance products and considering ESG and climate risk in their decisions.

Do you know those timelines, where they point “you are here!” and continue with some predictions? Let’s do just that before moving to the ins and outs of a particular software development project. To make sure we understand where this story goes, let’s see how the digital finance market appeared and developed.

The Growth of the Fintech Market and Digital Banking Industry

The fintech sector has seen more twists and turns than a prime-time soap opera, and with the same level of drama. Here are some snippets of numerous banking software development and general fintech industry twists.

A Timeline of the Fintech Explosion

  • 2008. The Global financial crisis. Traditional banks lost the ground and fintech startups got their heads up, looking to capitalize on the overall confusion and bring innovation.
  • 2013. Bitcoin’s price gets to $1,000 for the first time, starting the good, the bad and the ugly of the cryptocurrencies and blockchain technology era. Suddenly, everyone and their grandma wanted in on “magic Internet money.”
  • 2015. China’s Ant Financial, the behemoth behind Alipay, reaches $45 billion value. West gets reminded once again that fintech is not just a buzzword, it’s a lucrative industry. And it’s time to move fast. 
  • 2018. Global fintech investments double to a whopping $55 billion. Everyone wanted a slice of the fintech pie.
  • 2019. Digital-only banks like Revolut, Monzo, and N26 start gaining traction. They operate without any brick-and-mortar branches and challenge the big traditional banks with their user-friendly services and low fees.
  • 2020. The COVID-19 pandemic forces everyone online. Digital payments and neobanking see a massive boost as people avoid physical contact. Fintech solutions go from being a nice-to-have to essential.
  • 2021. Decentralized finance or DeFi takes off. Platforms that let people lend, borrow, or trade without middlemen grow popular. By year-end, DeFi has over $40 billion in assets, showing the world that blockchain’s potential goes beyond just cryptocurrencies.
  • 2022. Fintech booms in places like India, Brazil, and Nigeria. New startups and apps pop up, giving many people their first taste of modern financial services, bridging the gap left by traditional banks.
  • 2023. Governments and institutions worldwide start setting rules for fintech to make sure it’s safe but still innovative. The world starts seeing fintech not just as a trend, but as the new norm in finance.

And here we are, strategizing about banking software you want to develop that hopefully will disrupt the market and make such a list in a few years. What should it get rid of not to bring the cons of traditional banks into the new world? Let’s see.

What Was/Is Wrong with Traditional Banks?

  • Legacy systems. While fintechs were built for the digital age, many banks still relied on technology that was older than the first “Die Hard.” Some of them still are.
  • Risk aversion. Banks, with their stringent regulations and conservative nature, often ignore innovation. In the effort to increase security, they also don’t invest in state-of-the-art sec systems and quality tests, jeopardizing account safety.
  • UX. If banking apps were rated on user-friendliness, some apps rolled out by traditional banks would rank just above “trying to assemble IKEA furniture blindfolded.” In contrast, modern fintech solutions are designed from scratch with the user in mind, prioritizing seamless experiences over bureaucratic hurdles.

Truth to say, big legacy financial institutions catch up rather fast. They cannot act fully like startups and smaller companies, but they successfully incorporate some of the approaches to their benefit:
 

Bruce

“A larger organization that understands its processes and systems can make more significant releases. For example, a big legacy bank wants fintech to engage more with users. They know how the system works; it is just a question of putting a user-friendly Front-End on.

While a startup — new and fresh, something no one has seen before, needs constant checks on where and how to evolve. Big financial players use MVP to show what is going on, and startups use MVP to learn and define where they are going.”

Bruce Mason, Delivery and UK Director in QArea 

In essence, while traditional banks were busy fumbling with outdated tech and red tape, fintechs were sprinting ahead, capitalizing on modern tech and changing consumer expectations. It’s like comparing a horse-drawn carriage to a Tesla. And we all know who wins that race.

Types of Banking: Traditional vs Digital 

AspectTraditional BanksThe ChallengeDigital Transformation SolutionPotential Gain
Customer ServiceBranch visits, paper-based services, call centersInefficient, time-consuming, limited reachDigital platforms, chatbots, 24/7 online serviceGreater customer retention, increased satisfaction
Transaction MethodsPrimarily physical: checks, cash, in-branch transfersSlower processing times, higher costsMobile banking, instant transfers, digital walletsReduced costs, faster operations
Data HandlingManual data entry, limited analyticsInaccurate predictions, slower decision-makingAI-driven analytics, real-time data processingImproved decision-making, tailored offerings
OutreachLimited to branch locations, regional focusLimited market penetration, higher operational costsGlobal reach via online platforms, app-based servicesAccess to global markets, increased customer base
InnovationInfrequent, often reactive rather than proactiveFalling behind in the competitive landscapeAgile methodologies, continuous R&D, quick pivotingStaying ahead of competitors, capturing new markets
Operational CostsHigh due to physical infrastructures, manual processesReduced profit margins, scalability issuesCloud-based solutions, automationSignificant cost savings, scalable operations

And now let’s talk numbers, and how these numbers can reward those investing in quality and innovative banking software solution. 

  • Operational efficiency and savings. As banks benefit from custom software development, operational costs are taking a nosedive. For example, a digital transaction costs a fraction of its physical counterpart. JPMorgan Chase and Oliver Wyman reported that central bank digital currencies (CBDCs) could cut company transaction costs by almost $100 billion annually.
  • Revenue growth and new opportunities. Goldman Sachs’ digital bank, Marcus, is a testament to the revenue possibilities. Within its initial 18 months, Marcus secured over $50 billion in deposits. When traditional banks choose to benefit from a software product, they could unlock untapped revenue streams.
  • Customer base expansion. The global fintech adoption rate, according to EY, leaped from 16% in 2015 to 64% in 2019. For banks, this implies an expanding customer base, only if they can offer the seamless digital experience these users seek.
  • Mitigated risks and improved returns. AI and data analytics aren’t just buzzwords. They offer banks a smarter way to assess risks. A study by Autonomous Research highlighted that banks could leverage AI to save up to $1 trillion by 2030 through improved efficiency and reduced risks.

These are inspiring examples of how financial institutions can benefit from innovative app development — be it a mobile banking application, document management software or any other digital banking service you want to launch. 

It seems a good moment to discuss different types of banking software applications, so let’s have at it. 

Our Featured FinTech Cases

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JavaScript Development

Different Types of Banking Software Applications

No matter which type of software you want to build, you will see that every solution has its problems, and having a right software development partner can help with solutions. 

1/10 Core Banking Software (Systems) (CBS)

Centralized systems that support a bank’s most common transactions and accounts across different branches. A set of services offered by a bank’s central system, which includes managing accounts, loans, and financial transactions. Essentially, it’s the bank’s backbone, ensuring operations run smoothly and efficiently.

  • Often built on enterprise platforms like Java EE or .NET.
  • Require robust databases (like Oracle DB, Microsoft SQL Server) to handle vast transactional data.

Examples

  • Temenos T24 Transact. A popular CBS used worldwide that offers rich functionality and modular design.
  • Oracle FLEXCUBE. Another widely adopted system known for its scalability and resilience.

Key problems

Many banks still operate on legacy systems, which are outdated software platforms or technologies. These systems are not only slow and less efficient, but they also pose security risks. Moreover, as the financial world becomes more digital, these systems struggle to integrate with newer technologies, causing operational hitches.

Potential approach

APIs are becoming fundamental. They allow seamless integration between different software systems, offering flexibility and enhancing UX. By moving towards an API-centric approach, banks can easily incorporate new features, connect with third-party services, and ensure a smoother, more integrated banking experience for their customers.

2/10 Online Banking Platforms

Online Banking Platforms are software platforms designed to empower online and mobile banking activities. They give customers the convenience to access their bank accounts, manage finances, and execute transactions through digital means, anytime and anywhere. Mobile banking solutions — mobile-specific solutions cater to the ever-growing segment of customers who primarily bank via their smartphones — are the subsets of online platforms. 

  • Typically built with a microservices’ architecture to ensure scalability and agility.
  • Incorporate modern web technologies (like React or Angular) for responsive interfaces.

Examples

  • Backbase. A leading omnichannel banking platform that facilitates digital transformation for many banks.
  • Infosys Finacle Digital Banking Suite. Offers a wide range of digital banking capabilities, including e-wallets and QR code payments.

Key problems

There’s a constant challenge to balance user-friendly interfaces with robust security measures. Additionally, with the proliferation of digital banking solutions, creating a distinctive and intuitive user experience becomes crucial.

Potential approach

Embracing modular and flexible design principles can help. By  using API-driven integrations and focusing on continuous UX enhancements, online banking platforms can stay ahead, offering both security and ease of use to their customers.

3/10 Payment Gateways

This software helps process online payments, acting as the middleman between merchants and the payment processors. 

  • Requires strong encryption methods (like SSL certificates) to ensure transactional security.
  • Integration capabilities with APIs to work seamlessly with various e-commerce platforms.

Examples

  • Stripe. Renowned for its developer-friendly APIs and comprehensive toolkit.
  • PayPal’s Braintree. Offers customizable checkout experiences and global payment options.

Key problems

Not all payment gateways easily integrate with various e-commerce platforms or banking systems, leading to potential hitches in transactions. Occasionally, transactions may not go through due to various reasons, causing inconvenience to users. On the client side, some payment gateways charge significant fees, making them less favorable for merchants, especially small ones.

Potential approach

When evaluating or developing a payment gateway, focus on its adaptability. The digital commerce ecosystem is vast, and a gateway’s ability to choose payment gateways that prioritize API-driven integrations, implement mechanisms to handle transaction failures gracefully, offering alternatives or ensuring quick resolution for the end-users. Think about a clear, competitive, transparent fee structure for the gateway. 

4/10 Customer Relationship Management Software for Banks

It is designed to systematically manage, assess, and optimize customer interactions and data. The overarching goal is to elevate business relationships, ensuring customer satisfaction and loyalty, while also refining internal operational processes.

  • Integration with other banking systems for data pooling.
  • Utilizes data analytics and machine learning to provide insights on customer behavior.

Examples

  • Salesforce Financial Services Cloud. Tailored for banking with AI-driven insights to personalize customer experiences.
  • Finastra Fusion CRM. A bank-specific CRM emphasizing customer retention and cross-selling opportunities.

Key problems

The dynamic nature of customer behavior means the CRM system must constantly evolve to address changing preferences and needs. Also, with multiple touchpoints for customers, collating cohesive and comprehensive data can be a challenge, leading to potential missed opportunities.

Potential approach
Using AI and machine learning to anticipate customer needs may help provide timely and personalized offers or solutions. It is also beneficial to integrate various data sources, ensuring a 360-degree view of the customer.

5/10 Banking Analytics Platforms

Platforms that analyze vast amounts of banking data to derive actionable insights and optimize decision-making processes. These platforms enable banks to predict future trends, make informed decisions, and refine their overall strategy.

  • Implementation of big data technologies (like Hadoop and Spark).
  • Advanced AI and machine learning algorithms for predictive analytics.

Examples

  • SAS Banking Analytics. Helps banks in risk management, customer intelligence, and fraud mitigation.
  • TIBCO Spotfire. A data visualization tool popular in the banking environment for its real-time analytics capabilities.

Key problems

With the influx of massive data sets, it becomes challenging to sort, analyze, and derive meaningful insights efficiently. Handling sensitive financial data requires adherence to stringent regulations, which can be daunting. Also, banking analytics platforms might face difficulties in seamlessly integrating with existing systems, leading to data silos or inaccurate insights.

Potential approach
Implement tools and practices that prioritize relevant data, filtering out noise and ensuring efficient processing. Regularly update the platform to align with the latest data protection standards and conduct periodic audits. Finally, opt for platforms that support robust API-driven integrations, ensuring consistent data flow and reducing silos.

6/10 ATM Software

These software systems handle a variety of tasks: cash withdrawals, deposits, account balance inquiries, and more, providing customers 24/7 access to their bank accounts. They are also crucial in delivering banking services to areas where physical bank branches might be scarce or non-existent.

  • Built on robust, secure architectures to ensure transactional safety, particularly since ATMs are standalone entities often located in public places.
  • Incorporate multi-layered security measures, including encryption and anti-skimming technologies, to guard against potential fraud and physical attacks.

Examples

  • NCR APTRA. A suite of ATM solutions designed for enhancing the consumer experience, optimizing device and network performance.
  • Diebold Nixdorf Vynamic. Offers both consumer banking and teller automation, is known for its security and advanced transaction capabilities.

Key problems

The physical nature of ATMs makes them susceptible to skimming, hacking, and other forms of unauthorized access. The development of banking technology is good for clients, but makes it challenging for ATM software products to seamlessly communicate with core banking systems. 

Potential approach

Focus on proactive security measures, including regular software updates and advanced threat detection systems. Prioritize collaboration with core banking system providers for enhanced integration and optimized real-time transactional data flow. Implementing remote monitoring and management capabilities can also help in timely maintenance.

7/10 Loan Origination Systems (LOS)

This software handles the end-to-end journey of a loan application, from the initial customer inquiry and processing of their financial information, to the final loan disbursement. Lending field is increasingly competitive, and LOS play a big role in speeding up decision-making, reducing errors, and optimizing the overall lending experience.

  • Typically built on scalable architectures to handle a varying load of loan applications.
  • Incorporate advanced data analytics for real-time credit scoring, risk assessment, and fraud detection.

Examples

  • Ellie Mae’s Encompass. A leading LOS known for its all-in-one approach, covering CRM, loan origination, and compliance management.
  • Black Knight’s Empower. An integrated system that supports retail, wholesale, and consumer-direct lending channels.

Key problems

With lending regulations frequently evolving, it is difficult to make sure that LOS are updated to remain compliant. For accurate risk assessment, LOS need to integrate with a multitude of external data sources, which comes with integration challenges. Different lenders have varying needs, and a one-size-fits-all LOS can often fall short.

Potential approach

Modular system architecture can help with easy updates and integration with new data sources. Risk assessment and fraud detection can be strengthened by automation and AI-enhanced solutions. Focus on custom software development will help to tailor a particular solution to the needs of a specific lender and their clients. 

Real-Life Case:

Synchronizing data across multiple organizations can be tricky. Thrift Plus 1 faced this when creating loan systems for various organizations. With borrowers potentially being linked to multiple entities, the risks of data duplication loomed large. Collaborating with QArea, this fintech front-runner from Oceania implemented a universal file repository — ensuring seamless profile synchronization across all platforms. Moreover, adapting to the unique data transfer protocols of local banks was a crucial success. Read more about the synchronization solution.

8/10 Digital Wallets & Peer-to-Peer Payment Platforms

Digital wallets store digital versions of credit and debit cards, allowing users to make electronic transactions, while P2P platforms facilitate direct money transfers between individuals without the need for intermediaries. In an increasingly cashless society, these platforms offer convenience and speed.

  • Typically, use cloud-based infrastructure to ensure availability, resilience, and scalability.
  • Emphasize end-to-end encryption, biometric authentication, and real-time fraud detection to ensure the safety of transactions.

Examples

  • Apple Pay. A digital wallet that allows users to make payments in person, in iOS apps, and on the web.
    • Venmo. A P2P payment platform popular among millennials for its social feed and user-friendly interface.

Key problems

The difference in international regulations, currency conversions and fees make cross-border transactions challenging. The growing number of digital wallets and P2P platforms, it is difficult to ensure that they can interact and transfer funds between each other. Also, digital wallets and P2P platforms are constant targets for cyberattacks.

Potential approach

Prioritize partnerships and integrations with international financial networks to ease cross-border transactions. Engage in industry collaborations to promote interoperability standards. Prioritize security in every phase of application development, and stay updated with the latest cybersecurity trends and threats.

9/10 Forex and Trading Platforms

Forex & Trading Platforms serve as the gateway for retail and institutional investors to the global financial markets. These platforms offer tools for trading a wide variety of assets, from currencies and commodities to stocks and bonds. The emphasis is on real-time data, comprehensive analysis tools, and a seamless trading experience, allowing users to make informed decisions swiftly. 

  • Generally built on a multi-tiered infrastructure, balancing the need for high-speed data processing and a robust, user-friendly interface.
  • Prioritize real-time data feeds, advanced charting tools, and algorithmic trading capabilities for seasoned traders.

Examples

  • MetaTrader 4 (MT4). Widely regarded as the industry standard for forex trading, it offers advanced technical analysis, a flexible trading system, and algorithmic trading tools.
  • Baraka. An investment and US stocks trading platform built to empower the next generation of Middle East investors. Qarea team worked on this project ensuring quality assurance and UX tailored to the specific needs of Gulf region clients.

Key problems

When it comes to trading, every millisecond counts. Delays in order execution can lead to significant losses for traders. Also, traders can be misled by inaccuracies in market data or lags in its update. Don’t forget that overly complicated interfaces can deter novice traders (reducing your client base) and even overwhelm the experienced ones. 

Potential approach

Invest in state-of-the-art server infrastructure and reliable data providers to minimize latency and ensure real-time market data accuracy. Rely on user-centric design principles to create intuitive interfaces that cater to both novice and expert traders. Regularly gather feedback from platform users to iterate and improve the UX.

Real-Life Case from QArea:

Even the most proficient in-house teams can benefit from external expertise, especially when the stakes are high. Take, for instance, POS systems — balancing reliability with intuitive design can be a delicate challenge. When a prominent European mobile banking service provider faced this very issue, they turned to us. Despite their formidable internal resources, they recognized the value of our specialized insights. Our QA team meticulously evaluated and refined their mobile POS interface, ensuring millions of users across Europe experienced a seamless transaction process. Here is how we achieved it: QA for POS Hardware & Mobile Banking Application.

10/10 Banking Chatbots & Virtual Assistants

Banking Chatbots & Virtual Assistants are AI-driven tools designed to simulate human conversation and assist bank customers in real-time. These digital entities cover various of banking needs, from checking account balances and transaction histories to guiding users through complex financial products and services. They aim to enhance the UX, provide instant responses, and significantly reduce customer service wait times.

  • Typically, developed using natural language processing (NLP) and machine learning algorithms to comprehend user requests and deliver appropriate responses.

Examples

  • Erica by Bank of America. An AI-driven virtual assistant that helps clients with their banking needs, offering proactive insights and guidance.
  • Eva by HDFC Bank. Virtual banking assistant that can answer millions of customer queries across multiple channels instantly.

Key problems

Even with advanced AI, chatbots can misinterpret user queries. Some chatbots may only handle basic tasks, forcing users to switch to human representatives for more complex queries. Also, it is challenging to make sure that chatbot interactions are secure and don’t expose sensitive customer data.

Potential approach

Regularly train the chatbot with new data sets to improve accuracy in understanding and responding to queries. Incorporate a smooth handoff mechanism to transfer a customer from the bot to a human representative when needed. Prioritize end-to-end encryption and regular security assessments.

Obviously, it is not an exhaustive list. There is Anti-Money-Laundering software, Risk Management software, Wealth Management platforms, Fraud Detection Systems and many others that we will cover in the upcoming articles. 

From the variety of banking solutions, let’s move to the key technologies that make them possible. 

Conquer the financial frontier with our experience and flexibility in banking software development.

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