4 Artificial Intelligence trends noticed in the banking sector
By Joy Dumasia
June 24, 2022
- AI chips
- AI functions
- AI in banking
Artificial intelligence (AI) has been around for a long time. AI was first conceptualized in 1955 as a branch of computer science and focused on the science of building “intelligent machines” that could mimic the cognitive abilities of the human mind, such as learning and problem solving. AI is expected to have a disruptive effect on most industrial sectors, many times over the Internet over the past two decades. Organizations and governments around the world are diverting billions of dollars to fund research and pilot programs of AI applications to solve real-world problems that current technology is unable to solve.
Artificial intelligence enables banks to manage record-breaking high-speed data to receive valuable insights. Moreover, digital payments, AI robots and biometric fraud detection systems further lead to high quality services for a wider customer base. Artificial intelligence includes a comprehensive set of technologies, including but not limited to machine learning, natural language processing, expert systems, vision, speech, planning, robotics, etc.
The adoption of AI in different businesses has increased due to the COVID-19 pandemic. Since the pandemic hit the world, the potential value of AI has increased dramatically. The adoption of AI is limited to improving the efficiency of operations or the efficiency of operations. However, AI is becoming increasingly important as organizations automate their day-to-day operations and understand the datasets affected by COVID-19. It can also be leveraged to improve the stakeholder experience.
Here are 4 AI trends noticed in the banking sector:
- AI in cybersecurity
The use of AI-powered cybersecurity tools is one of the growing AI trends, AI will enhance cybersecurity by helping in threat detection and prevention. For example, by identifying patterns and learning to spot fraud, preventing unauthorized access and cyberattacks by learning to identify unusual or threatening activity. AI-based cybersecurity systems provide the latest insights into industry-specific and global threats. Such decisions depend on what could possibly be used to attack your business. Prescriptive information allows organizations to configure and augment controls and processes to fine-tune their cyber resilience more effectively.
AutoML has traditionally focused on algorithmic selection and finding the best machine learning or deep learning solution for a particular data set. However, growth has been seen in the Low-Code/No-Code movement across the board, from applications to targeted vertical AI solutions for enterprises. While AutoML made it possible to build high-quality AI models without extensive data science knowledge, modern Low-Code/No-Code platforms make it possible to build complete production-grade AI-powered applications. without in-depth programming knowledge.
AI functions require more processing power than non-IA functions. This goes hand in hand with the exponential growth of processing power, and this continued growth and accessibility of AI computing is creating increased demand for more powerful hardware. This hardware will be more efficient and enable increasingly widespread use of AI and automation functions.
Hperautomation is the combination of robotic process automation with artificial intelligence, it is frequently mentioned as a central aspect of the next wave of digital transformation. The power and usefulness of automation has long been known, the COVID-19 pandemic has only made it more apparent, as automation has proven instrumental in mitigating disruption to office workflows. Moreover, an extension of automation makes sense that hyperautomation will gradually come to the fore in the coming years.
IBS Intelligence reported on this that Mambu and Google cloud released a new report indicating that artificial intelligence will deliver personalized experiences and reshape banking as we know it. This change is driven by a combination of disruptive forces in the market. The report shows that the pandemic has increased consumer demand for always-available and personalized digital and mobile financial services.
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