AI Transforms Banking: Chatbots, Personalized Experiences, and Streamlined Processes
The banking industry has witnessed significant changes since the introduction of AI, including fraud detection and prevention, personalized customer experiences, and streamlined processes. Moreover, AI has facilitated the development of personalized investment and savings plans, which were previously unavailable to the average consumer.
Despite the significant advancements in AI adoption by banks, there are still challenges that need to be addressed. Concerns around data privacy, transparency, and the ethical use of AI remain major obstacles in the banking industry. Nevertheless, the benefits of AI to the banking industry cannot be ignored, and it is expected that AI will continue to revolutionize banking in the coming years.
AI and The Banking Industry
The influence of AI on the banking industry is all-encompassing, affecting various areas such as customer service, fraud detection, and data analysis. Although many customers may not be aware of the complex machine learning systems used by their banks to prevent money laundering or identify fraudulent transactions, they have likely interacted with AI-powered customer service chatbots. While some argue that the rise of digital banking and AI is causing the demise of physical banks, it’s worth noting that consumer-facing digital banking has been around since the 1960s, starting with the introduction of ATMs.
What has changed, however, is customers’ expectations for how they access banking services. AI has revolutionized this aspect, with AI-powered chatbots, voice assistants, and biometric authorization becoming the norm at major financial institutions. And for those who still prefer to visit physical banks, AI-enabled robotic assistants are also being introduced.
Kasisto Bank Perfectly Adopted AI
The emergence of digital-first banks, also known as “challenger banks” or “neo-banks,” has been a hot topic and a major draw for investors in some parts of the world, particularly in the UK, for the past few years. Although they have not gained as much popularity in the US as they have in other regions, Kasisto, a US-based company, has been instrumental in facilitating their growth.
Kasisto has developed a conversational AI platform called KAI, which allows banks to create their own chatbots and virtual assistants. Its advanced natural language understanding and generation capabilities enable it to handle complex financial queries that other digital assistants for bank customers, such as Bank of America’s Erica, cannot.
Kasisto has already provided AI assistants for several prominent banks, including Liv., a chatbot powered by KAI technology has been implemented by various banks, including a digital bank in the UAE, as well as DBS Bank, Standard Chartered Bank, and TD. This chatbot is designed to help customers with a range of tasks, such as blocking credit card charges, making international transfers, and connecting them to a human representative when necessary.
AI and Middle Office Functions
Although artificial intelligence has not had as significant an impact on customer-facing roles in banking as it has in other service industries, it has truly transformed the so-called middle office functions.
The middle office is where banks handle risk management and protect themselves against fraudulent activity. This includes initiatives like fraud detection, anti-money laundering efforts, and identity verification through KYC (know-your-customer) checks, which are required by federal law under the Patriot Act of 2001. Socure Bank provides a good example of incorporating AI into legacy anti-fraud platforms.
The ID+ Platform offered by Socure utilizes artificial intelligence and machine learning techniques to scrutinize an applicant’s social, online, and offline data, aiding organizations to satisfy stringent know-your-customer (KYC) regulations. Predictive data science is employed to examine data points like email addresses, phone numbers, IP addresses, and proxies to verify the legitimacy of the information provided by the applicant.
How the Impact of AI on the Banking Sector Will Continue?
It is clear that the impact of AI will be higher on the banking sector than it is today. Here are some ways that AI is expected to affect banks in the years to come.
First, chatbots and virtual assistants are already being used by many banks to handle routine customer queries, and as AI technologies become more sophisticated, these chatbots will become more capable of handling more complex queries, providing personalized advice and recommendations, and even identifying potential fraud.
Second, AI is expected to play a larger role in risk management. As the volume of data that banks collect continues to grow, AI algorithms can be used to analyze this data and identify patterns that may indicate fraudulent activity, money laundering, or other types of risk.
One potential application of AI is enhancing the efficiency of back-end operations. By automating loan application processing through AI algorithms, it’s possible to decrease the time and expenses associated with this task.
Finally, AI algorithms can be used to analyze customer data which is the best to develop new products in as short time period and with less needed resources.
One example of how AI is already being used in the banking industry is JPMorgan Chase’s Contract Intelligence (COiN) platform, which uses machine learning algorithms to review and extract key data from legal documents. Another example is the AI-powered virtual assistant developed by Kasisto, which is being used by several prominent banking institutions to provide personalized financial advice and support to customers.
In summary, AI is likely to have a profound impact on the banking industry in the years to come, improving customer service, enhancing risk management, increasing efficiency, and driving innovation.
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