Artificial Intelligence/Machine Learning (AI/ML) is an Area of Great Interest and Opportunity for Fintech Developers.
Rapyd’s State of the Global Fintech Developer Report investigated the experiences and opinions of fintech developers in a survey of 500+ developers worldwide. Not only is Artificial Intelligence/Machine Learning (AI/ML) an area that many fintech developers work in, but it’s also an area where they see great opportunities for fintech and their professional development.
In examining the projects and initiatives that fintech developers are working on and excited about, our study showed that developers were overwhelmingly excited and interested in the AI/ML field.
Nearly Half of Developers Already Involved in Data/AI Initiatives
More than four in ten respondents reported being currently involved with Data/AI initiatives, and 76% of respondents identified AI/ML as the greatest area of opportunity in their work.
Source: The State of the Global Fintech Developer. 451 Research and Rapyd Custom Survey.
Using AI/ML for Greater Automation, Security
Rapyd’s survey revealed that AI/ML remains a growing opportunity for developers to solve problems from increasing workloads and a lack of automation to improving security and fraud prevention.
It’s no secret that roadblocks and delays are a part of software development. In fact, one study found that more than half of all development projects are late and over budget, with another 20 percent canceled outright. (Speed and Function).
While fintech APIs are helping to ease workload issues, deploying more AI/ML solutions can also greatly speed up development. AI/ML solutions are an opportunity to address these productivity challenges. A recent Deloitte article noted that AI-enhanced software development could enable a typical developer to be 10X more productive than they would be on their own. (Deloitte)
AI/ML for Automation and Productivity
Developers are applying AI to address security and fraud challenges to enable greater preventative measures deployment with less labor-intensive intervention. This application of AI/ML also has far-reaching implications for addressing the increasing workloads of developers and the currently limited scope of automation across many areas in fintech development.
AI/ML for Security and Fraud Prevention
Developers are increasingly turning to innovations in AI and ML to quickly and automatically detect suspicious activity. As more sophisticated AI/ML-enhanced software is deployed, developers are able to let algorithms do more of the heavy lifting and refocus their time on other priorities.
Discover What’s Driving Today’s Fintech Devs
Understanding how advancements in AI/ML are impacting developers is just the tip of the iceberg. Whether it’s learning more about the opportunities for advancement for fintech developers, what the most in-demand coding languages and skills are, or
what developers are really focused on at work and in life, download and get your copy of the State of the Global Fintech Developer study.
Deloitte. AI is helping to make better software.
Koombea. “8 Uses of AI/ML (Machine Learning) in Fintech”
Speed & Function. “A look at 25 years of software projects. What can we learn?,”