AI is a science that branches from Computer Science and focuses on making intelligent computers and machines that can mimic a human mind's cognitive ability. AI, therefore, can learn and solve problems.
So how does AI apply to online lending? Banks deal with massive amounts of data that needs to be processed accurately, in real-time, and accurately.
AI ensures that this data is managed at record-breaking speeds while at the same time understanding the information provided and providing insights to improve the lending system.
Below are some of the impacts of big data and artificial intelligence on online lending.
The way customers borrow money has dramatically changed in recent times. The growth in technology has made it possible for people to be online throughout the day. This has left a lot of behavioral data and footprints on the digital property of lenders.
The lenders then use Artificial Intelligence to process the data, helping them understand their customers' behavior. They can predict the outcomes of specific business strategies based on behavior.
For example, AI can predict whether customers have any intentions of purchasing lending products.
AI models the customer's purchase intent using clickstream and search history data. The AI can categorize customers into the most likely to buy the product, those that would require some effort, and those that are uninterested in the lending product.
The lender can also program the AI to produce more categories to understand their customers better. This information is beneficial and can help lender approach their customers at a fertile stage.
AI can help the lender approach a target client by personalizing their products. This nudges the customer to make the purchase. Gday Loans is among the banking service providers that incorporate AI to streamline the online loan finding experiences of their customers.
Determining a customer's credit score helps a lender determine how eligible they are for certain loans. It is a critical factor that all lenders consider because of its role in making profits for the lenders and driving their loan books.
Currently, this process is either rules-driven or manual and is different in all bank branches. Therefore, scoring a customer's credit helps drive the lender's business and operations. AI can cause considerable disruption in credit scoring and help the lender's loan books grow.
AI uses multiple data points that analyze customer behaviors, income-tax histories, financial histories, and any other transactions they have made. After analysis, they can then determine risk scores for each customer, helping the lenders get a clearer picture of who is more likely to repay a loan.
The data points that AI uses to make this analysis include the behavior of the customers on digital platforms of lenders and affiliates, their social profiles, their friends and family, their connections on LinkedIn, Facebook, and other social media platforms, and how long they are online, the type of phone or computer they use, the details of their calls, their qualifications academically, their wallet data, and hor frequently they make payments.
Artificial Intelligence can process such data and model it to output credit scores for each customer. The credit scores are real-time and take into account every transaction of the customers.
The credit scores allow lenders to approach an existing customer or a potential client and sell them approved loan products. The lender's messages to their customers and prospects can also be personalized, helping their loan books grow faster.
AI can therefore reduce the risk that lenders have to take every time they lend money to their customers. It also standardizes the credit scoring process in all bank branches.
Artificial Intelligence has drastically remodeled the banking and online lending industries and will continue to do so with further application.
It has streamlined the customer experiences, made the lending process a lot safer and more accessible for lenders, and given the banks and lenders that use AI programs a competitive edge.
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