Everyone knows the importance of economic stability for a country. The Banking System is primarily responsible for making a country financially stable. Banking is the bloodline that runs through the nerves of a country. They deal with extremely sensitive financial information which cannot be compromised at any cost. This, at times, restrains banks from adopting AI – to its fullest potential. But they have adopted a few features of AI. Let us try to understand the miracles that AI can bring to the banking sector.
Banks deal with many loan applications day in and day out. Not all get approved. Since early times, the approval or rejection depended on the loan-sanctioning authority.
After manually examining the history of each client the loan is approved. Unfortunately, manual observations are prone to errors. Machine Learning models can better predict the possibilities of a loan going bad. Identifying the odds of a willful default reduces stress in the banking system. Traditionally loan eligibility depended primarily on demographic data. AI enables us to assess a borrower based on their Psychometric data. This combination is unique and vastly beneficial to the Banking Industry.
With the world going cashless, identifying credit card fraud is extremely essential. Millions of transactions happen every hour, thus it is vital to keep a check on all.
A person or a group of people cannot be burdened with so much work. Machine Learning models can replace them. Transactional data of each customer can be used to train the models. Their expenditure patterns are considered. Any deviation from this pattern is considered an Anomaly. As soon as an anomaly is spotted, the AI-based system immediately reports it. Any fraudulent action is immediately taken care of, thereby preventing dire consequences.
Every customer has his digital footprint which generates petabytes of data. AI tools can be used to scrape data and derive valuable insights about any user.
His lifestyle, preferences & habits can be identified. Based on these traits, personalized recommendations can be made for each customer. Due to their busyness, people need quick solutions that match their needs. Personalized user experience aids the conversion of the transaction.
Banking officials take many tactical decisions. For taking better decisions, Machine Learning can be used. It helps in the qualitative and quantitative analysis of any situation.
The data collated helps in understanding data touchpoints that may be crucial. The effect that a particular decision can have, may be predicted well in advance. Machines can be used to assist in the decision-making process. It improves the efficacy of the decisions significantly.
Who wouldn’t like to? But when you are not alone in the market you must consider the moves of your competitors too. Anticipation, Alertness, and Action are the three A’s to get ahead of them.
Customers expect their banks to offer them seamless support. They are usually loyal if they feel their service provider understands their needs. The days of customer support executives are passe.
AI is the ray that will keep enlightening every domain regardless of time. With cybersecurity standards in place, it can completely revolutionize the Banking sector.