The transformative impact of AI has been obvious since its impact and the financial sector is no exception.
In fact, artificial intelligence could potentially deliver up to $1 trillion of additional value to the financial sector each year, states McKinsey report. The banking and financial industry is moving towards AI to improve efficiency, service delivery, productivity and cut down costs. Here are some of the major examples of AI implementations in banking software development.
Software Development Automation
Artificial intelligence turned out to be an increasingly essential tool for building ever-green software changing the way applications are developed and examined. AI-powered technologies assist humans in every stage of banking software development lifecycle – from smart resource allocation and prototyping to predicting bottlenecks and making recommendations for upgrades and enhancements. One of the most obvious examples of AI implementation in banking software development is its ability to generate pieces of code assisting human developers. This method is known as automated programming, and it is becoming more popular.
Added Security
Statistics are scary – the number of successful cyberattacks in the financial sector is increasing year-by-year. According to an IBM report, the financial sector is second-ranked in the global cyber incident damage statistics. Thus, the banking sector is facing a growing need to enhance its fraud detection capabilities. Artificial intelligence plays a crucial role in this area. AI and ML (machine learning) enable banks to detect fraudulent activities, identify system vulnerabilities, reduce risks, and bolster the overall security of online financial transactions.
Enhanced Customer Experience and Personalization Opportunities
AI is seen as a tool to retain customers providing them with ultimate convenience and personalization while interacting with your banking software. Firstly, AI-powered chatbots come into play to react and solve basic user queries 24/7. Second, AI-powered algorithms can analyze vast amounts of data, including user patterns and preferences and help you offer tailored services and offers based on the insights received. Third, voice-responsive systems are another prevalent AI integration aimed at enhancing user experience. These systems enable users to voice their queries and deliver relevant responses, thus boosting overall performance.
Assistance in AML and KYC Procedures
Banking is one of the most heavily regulated industries globally. Governments wield their regulatory power to ensure customers are not using banking services to perpetrate financial crimes and “legalize” the “dirty” money. To manage these regulatory demands, banks typically employ internal compliance teams. However, since these compliance efforts are manual, they are time-consuming and costly. Regulatory standards also change frequently, requiring banks to continually update their processes and workflows to comply.
In this context, AI and ML are transforming banking by utilizing deep learning and natural language processing (NLP) to interpret new compliance regulations for financial institutions and enhance decision-making processes. While AI cannot replace compliance analysts entirely, it significantly speeds up and optimizes their work, making it more efficient.
In conclusion, artificial intelligence is rapidly transforming banking software development by enhancing security, automating development processes, providing personalized customer experiences, and optimizing compliance procedures. As AI continues to advance, we can expect to see even more groundbreaking innovations in the financial sector.
S-Pro development team is at the forefront of opportunities that AI opens to the financial sector. Whether you need to develop banking software from scratch or implement AI solutions to the existing digital banking solution – their vetted team is here to help. Don’t hesitate to let your banking software take advantage of the full potential of artificial intelligence with S-Pro.
