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The banking industry has witnessed an increase in the adoption of digital technologies to improve its business processes, and this love affair of technology and the banking industry continues with the introduction of Cognitive Computing technology in banking.
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CC refers to the technology platform which leverages Artificial Intelligence and signal processing to imitate human behavior. Usually, they are self-learning systems that use a variety of data, predictive analytics, and natural language processing.
In simple words, CC is a branch of computer science that attempts to give machines the ability to think and behave like humans. It analyzes data and makes decision autonomously, but acts in accordance with human behavior.
Financial institutions, including banks, have been swift in adopting technologies that automate their process with a view to serve their increasing customers more efficiently.
These activities involve basic banking services such as money withdrawals, payments and transfer of funds, the printing of bank statements, and solving account related queries. People have started to realize that they are more likely to deal with machines than with humans when interacting with banks. People are not averse to this robotization of banks; they expect these systems to be effective than the human version. It is in the banks’ best interests to make these machines more human with regards to its ability to not only interact with customers but also understand and solve their queries.
Therefore banks are frequently deploying technologies and initiatives to make their interactions with customers more human and convenient. To that respect, they are leveraging big data analytics to personalize customer interactions. The use of cognitive technology in banking will build on these technologies and make banking more efficient than ever while delivering excellent customer experience.
The potential application for CC in the banking sector includes the following:
CC has the potential to manage a large number of banking transactions in a highly sophisticated manner, thereby allowing banks to compete on analytics. It can use context and evidence-based information to provide tailored products and services to customers. It will cause an improvement in the self-service for bank customers through increased automation of banking and investment products.
CC can assist banks to get closer to their customers. Its ability to analyze text and other word-based inputs and to learn from experience adds another dimension for banks. Its ability to improve personalization with every transaction or interaction with a customer leads to a considerable improvement in customer satisfaction as banks address their needs directly.
With CC, more data and from more sources can be examined, including the text-based and other non-numerical data. It enables banks to get a better picture of risks and predict them more accurately. Earlier used fraud detection system were post-hoc, analyzing what happened, and deciding whether it looked incorrect. Real-time systems brought this up to date, thereby allowing faster detection. CC can be used to predict fraud before it has taken place that means before a fraudulent activity occurs.
The use of CC in the banking industry can deliver a great customer experience in the following ways:
With the use of CC with advanced natural language processing capabilities can enable banks to gather insights and make decisions based on highly detailed information. Such decisions would have low risk with them, leading them to more effective actions and better results.
Chatbots for customer service has become essential as it minimizes the need for human executives. The use of CC in financial organizations’ websites and mobile applications can improve their functionality, enabling them to solve complex queries. A chatbot powered by CC can explain to a customer why a particular transaction is taking too much time than usual, and it can also answer follow up questions.
CC can enable the security systems used by banks to be more robust, which can minimize the risk of illicit transactions, identity theft while maximizing the ease of performing transactions that are legal. CC can analyze factors related to customer behavior like their usual modes of transaction, their monthly spending, etc. With this information, the security systems can determine the likelihood of a transaction being legal.
Therefore CC can not just improve convenience for customers, but it also can increase operational efficiency through automation. Moreover, the use of cognitive technology can help in improving the security of money and assets.
Despite having the potential to change lives, this innovation has been resisted by humans due to the fear of change. People have come up with numerous disadvantages with CC. Few of those include the question of security.
When digital devices manage sensitive information, the question of security is always discussed. With connected devices coming into the frame, CC will have to contemplate issues related to security breaches by preparing a foolproof security plan.
One of the biggest obstructions to the path of achieving greatness for any technology is voluntary adoption. For this technology to be successful, a long term vision has to be developed. The adoption must be streamlined, and steps must be taken to boost its adoption.
Read our article:Data Analytics in Banking: Application, Challenges & Opportunities
Ashish M. Shaji has done his graduation in law (BA. LLB) from CCS University. He has keen interests in doing extensive research and writing on legal subjects especially on corporate law. He is a creative thinker and has a great interest in exploring legal subjects.
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