AI And Financial Industry
A worldwide technology has emerged and evolved over the years. From Siri Google Assistant, from Netflix to Pandora and from Amazon to Tesla, we are gradually adapting Artificial Intelligence. It has been highly popular from giant enterprise like Amazon and Tesla or intermediary like Zoox or Twilio.
Similarly, Banking sectors have been seen increasingly investing its time and $$$ in Artificial Intelligence(AI). Their strategies are to drive cost and efficiency tremendously.
If I simplify, AI involves algorithms that can make decisions like human and sometimes smarter than human. Using AI technologies, banks can find data, filings, earnings and millions of research documents in one second. It can improve keywords to find suitable searches to help clients better than before.
Compared to other sectors like e-commerce or healthcare, adoption of AI in the banking sector is really limited due to its highly confidential nature of user data. However due to rapid growth of using AI technology in business via mobile or other devices, banks also started to focus on what they can achieve through AI under the limited secured user data governance.
AI Use Cases And Application in Banking Sector
We are really thankful to advance technology concepts because every organization can use and make their application or business model more intelligent through Artificial Intelligence. Banks are also trying to be on stage by using AI in certain applications.
1. Chatbots/Personal Assistants
Chatbots and personal assistants are changing the interest of customers by providing a personalized experience to the user. Chatbots have indeed proven a powerful tool to customers and an unmatched tool that is saving lots of money for banks. Banks are racing to integrate chatbots to attract the customer attention and expand the brand and its service.
2. Complemented Customer Experience
Banking sector can enhance its customer experience through AI in their app. They can track customer choice, personalized suggestions, transaction trail, money variation to suggest to customers to either invest or spend, search patterns, and much more. Demand for this kind of AI enabled app in the banking sector has grown intensely. Overall banks can improve their customer service based on customer experience on apps with AI integration.
3. Data Collection and Analytics
Collected data from customers can be used by AI machines to understand the customer. Customer data can be used for segmentation that categorizes the customer based on their behavior which helps banks to target their customer in a better way. Banks are starting to shift their model where their products are now services and services need data to understand the customer to provide and serve them better.
4. Risk Management
Risk management analysis is one of the key areas where banks can save themselves from any kind of fraud. Understand the borrower when they apply for a loan, banks have to keep their personal data and at the same time banks have to review the financial status of the borrower before disbursing the loan. With the integration of AI, banks can easily track the recent financial transactions of the borrower and based on that banks can collect enough data that will empower them to decide either grant loan or deny it.
5. Loan Processing
Lending is the massive business of all the banks which directly and indirectly touches the economy of the world. To find out borrower creditworthiness is one of the crucial tasks for the banks before they process a loan to the borrower. For example the better banks can find out the creditworthiness of a client, the more easily they can streamline the process of loan in organization. In other ways the quicker and less hassle is really appealing to the customer.
With the use of Artificial Intelligence and Machine Learning, in a few seconds banks can find out, if customer lacks credit history, year or credit, FICO scores and top this traditional data, banks can also find out educational background like SAT scores, GPA, field of study, job history to determine creditworthiness of a borrower.
6. Detects Fraud
After every few weeks/months you hear the news about fraud of customer credit/debit card. AI with ML is on top when it comes to detect fraud and security. It can find out the past spending behavior of a customer to find our odd behavior of the transaction. AI never feels uneasy, if it finds the correct behavior as faulty and and it gets corrected by human intervention that itself corrects the ML and next time AI can skip that finding.
7. Compliance
Banking sectors are very strict in terms of their compliance and its rules. They consistently need to review and update their compliance and keep their system updated. In most of the banks they have their internal team to manage this compliance. Compliance team, update the documents, clean the webpages and other internal services. With AI integration, it can actively find the rules that apply to the bank and mark them compliant. It also improves the thinking and work process of the compliance officer and its internal team.
Whats Next?
Still AI is new and is being adopted by banks in slow or medium pace. But, AI futures in banking sectors are going to be multiplied. This whole technology is going to be really a game changer for banking and financial sectors as it is for other organizations.
