A decade or so ago, financial services firms might have operate a mile at the idea of entrusting the future of their businesses to open-source technology. It was considered far too risky to expose such a highly regulated industry to software whose source code any person in the general public can inspect, modify, enhance and even distribute – all totally free. The advantages of financial bodies being able to manipulate code to meet their specific requirements to aid fast and competitive innovations was clouded by security fears, many of which prevail.
However, financial services leaders are now getting out of bed in a world where competition is fierce and fast. New fintech rivals take advantage of free to offer customers better services and products that meet fast-evolving expectations. Open-source technologies are no longer a risky option; it is the fearless future of financial services.
The “olde worlde” of financial services technology – shattered
Traditionally, the financial services sector relied on developing its very own, proven, proprietary software. Closed source, of course. Why? Because it desired to address compliance and security concerns with confidence, while creating and protecting its competitive Intellectual Property .
Then, a few years ago, because the rest of the world was beginning to embrace open-source technology with open arms, something happened. Established technology vendors started acquiring open-source organisations. In 2022, Microsoft bought GitHub for $7.5 billion. The following year, IBM acquired Red Hat for $34 billion. New challengers were now running ahead with digital transformation and disrupting the market having a stream of innovative digital banking services. Established financial services were needing to jump to it, or risk losing out to ambitious new competitors.
A brief history of open source within the financial sector
Some would argue that the shift to open source within the financial services sector began around 10 years earlier, once the financial sector began to change from closed-source Unix servers to open-source Linux platforms. This would massively accelerate data processing, storage and trading infrastructures.
In January 2022, the Second Payment Services Directive – the ecu regulation for secure electronic payment services – boosted innovation and helped financial services adjust to new technologies, enhancing the need for Application Programming Interfaces . Many finance businesses began to depend on open-source programming languages for example JavaScript to construct and implement APIs, in addition to micro-services and other front-end assets to handle multiple customer activities.
Then in 2022, outdoors Banking initiative – promoted through the European Commission to spread out up financial services and stimulate competition and innovation – further pushed the adoption of free integration standards and APIs to help financial services firms interact better across borders.
These key developments allowed financial services firms to innovate faster and at a lesser cost than ever before. Customers benefited from new services such as automated loan approvals and trading, chat bots and fraud detection. Testimonials for example Capital One began to appear. They committed to open source so they could deploy software faster and also at scale while managing code vulnerabilities and security risks. Within six years, Capital One was among the world's largest digital banks with millions of accounts.
A new generation of data science driving business intelligence and real-time analytics
Open-source programming languages such as R and Python are driving advancements in AI and machine learning, generating live data insights overall – from risk management to customer intelligence – allowing businesses to provide hyper-personalised experiences instantly.
While a cultural shift in many financial organisations is still a piece in progress, global IT and data quality teams can rest assured that most of the latest generation of analytics solutions now deliver secure and compliant use of popular analytic languages like R. Secure end-to-end validation mitigates the chance of adopting and managing open-source software for repeatable and consistent analytic environments, saving time and resources while generating tailored, dependable results.
Governance-related concerns that previously formed a barrier to open-source adoption among financial services could be safely consigned to the history books. Instead, firms can deploy the most recent AI tools and machine learning methods to predictive modelling and statistical analysis, extracting business-critical information from thousands of data sources.
Moreover, organisations can draw on a rich pool of today's graduates, who're experienced in programming languages like R for data science, big data analysis and visualisation.
The future of free within the finance sector