digital transformation

In the modern world of digital technologies, several technological and managerial aspects share a strong intersection. Among others, three important aspects are big data, cybersecurity, and enterprise resource planning systems. In the IT era, organizations have been relying on applications for their growth and day-to-day activities. While it is essential to manage and operate ERPs to improve and attain new business heights, there are also big questions about continuous cyberattacks, security, and hacking issues. The ignorance and negligence of the management and staff in any of these have led them to a significant level of loss. Some instances have practically shown companies' reputations and prospects went down drastically due to such uncontrollable white-collar crimes. The growth of the digital era forces us to devise adept mechanisms and take stringent measures. Consequently, there is a need to transcend these major challenges in unison. In this exploratory study, we have proposed the potential and the possibility for deep learning in the area of big data and cybersecurity when closely knit with enterprise resource planning systems. Contemporary ERPs are like the central nervous system of a living organism: providing vital data and ensuring efficient operations. The key elements of today's organizations are reporting systems and transaction processing systems. The database systems that store business data are often architected with a mixture of different data management technologies. These conglomerate systems are often hybrids with a complex array of proprietary, open-source, and emerging cloud-based convergences. Considering the fast and rapidly changing IT environments, ERPs have to be adaptable to these data challenges. The security of an organization's data is a core issue and must be protected from IT-based security threats. Organizations must have reserved data hacked or be demoralized by hacking attempts. The harmonic convergence of data management, cybersecurity analytics, and deep learning provides profound new approaches for hardening the systems that manage and protect the data!

Artificial Intelligence (AI) has become one of the most dominant enablers of digital transformation across a significant number of industries in recent years. With the application of AI technology including natural language processing (NLP), creating human-like chat bots has become easier. Today, a greater portion of India banks have switched over to Chat Bot technology for their customer on-boarding, queries, complaints, fund transfers, etc., due their proficiency in handling numerous queries with high response time and round the clock service. This case study is based on the virtual assistant of State Bank of India (SBI) – State Bank Intelligent Assistant (SIA), which is engaged in providing personalized service to users based on their historical preferences, search frequency etc., via analyzing the data with the assistance of AI techniques. The recent developments and emergence of Virtual Banking in India and the current trends in the modern banking systems are explained along with the features of SBI-SIA virtual assistant. As banking is reshaped by technology, financial stability is a key priority for the Bank of England. The Bank is engaging with FinTech companies to gather information and understanding on the financial stability risks that might emerge from FinTech developments. Such risks are expected from the explosion of technology-enabled financial services. It has now become common for many banks to integrate FinTech, machine learning and AI into their services because customers want more choices, flexibility and control over their banking. AI is a branch of FinTech but not every FinTech is AI. AI is machine intelligence. Machine learning and AI are often treated as synonyms. AI in retail banking is at its nascent stage in the UK, though the potential is extraordinary. In the UK, some banks have launched banking applications using voice recognition. The Royal Bank of Scotland (RBS) has decided to roll out its “Luvo” AI customer service assistant, powered by its partner firm, RBS Group, wider in its branches. Bank of America, Capital One, Société Générale and Swedbank are some of the banks that have experimented with chatbots.