The lending industry is developing at lightning speed to meet the growing customer demand. With the advancement of AI technology, it seems that soon enough we will have AI bots answering customer service inquiries with AI-concierges informing the clients about their best lending options. But how much of it is actually true at this point? It turns out, that only 13% of banks started implementing AI technologies, despite everyone talking about AI threatening to change banking as we know it, along with the whole loan application process.
AI is coming, we just have to wait
AI tools may not be used extensively right now, but the lending scene is changing as we speak. Numerous banks and loan companies like LendUp, Upgrade, UpStart, and LendingTree are looking to improve their customer services using cutting-edge technologies. According to this survey, 80% of businesses believe that AI tools can considerably boost the lending process. Half of the surveyed respondents are planning to invest $100,000 or more into implementing AI algorithms into their banking systems, with 12% of banks about to spend $500,000 or more to do the same.
AI-powered software is expected to increase the efficiency of all lending operations, allowing banks to review 3.5 times more loan applications compared to companies that don’t use AI tools. As far as effectiveness is concerned, machine algorithms can quickly identify customers who are more likely to repay loans, making predictions based on their financial behavior and transaction history.
AI tools come with challenges
Naturally, implementing AI technology comes with its set of pitfalls and underlying issues. Lenders will have to revolutionize their approach to match the standards of AI tools that require data availability and a high level of security. Some of the issues lenders will need to solve include:
- AI bots and machine learning models rely heavily on high-quality data that should be available in large quantities. Banks often face challenges trying to provide the necessary amount of data for their training and authentication.
- Many AI tools present challenges in terms of transparency in data collection and usage. This is an important issue many lenders face when trying to implement AI-driven algorithms.
- The algorithms need to be thoroughly validated in order to avoid biased behavior. They should provide high-quality service without discriminating against certain customer groups or demographics based on their financial profiles.
- To maintain trust, lenders should be able to explain why AI bots and other machine-powered algorithms arrive at a certain conclusion. Thus, making explainability yet another crucial factor when it comes to using Artificial Intelligence to streamline financial operations.
The benefits of using AI in lending
Banks are in dire need of instruments that could streamline loan-related financial operations. In this regard, AI tools can be of great help to human teams, automizing financial operations and increasing the number of processed applications at any given time. Some of the other benefits include:
- AI tools can help lenders to better assess credit risks when giving out loans to certain groups of customers or individual clients. They can analyze large volumes of data, providing them with metrics and statistics to help them make more informed decisions.
- AI algorithms can use extensive customer data to predict potential delinquency or default. Customer service teams can use AI tools to better understand borrower behavior and analyze their payment patterns.
Ai-powered loan management software is changing the way lending businesses operate on a daily basis. For borrowers, this means getting a more personalized service and quick loan application review. By using these tools, lenders increase cost-efficiency and considerably reduce the amount of time spent on repetitive manual tasks.
Why automation is the future of loan management
In 2025, lenders are expected to improve their services in accordance with the growing customer demand. Automation allows companies to considerably enhance the user experience while making the process of applying for loans effortless and stress-free. Automation will also result in a 15-20% increase in annual revenue, making lending companies more profitable than ever.
By implementing cutting-edge automated credit scoring models, lending businesses can revolutionize the whole loan approval process. While still assessing all possible risks, they can speed up the decision-making process by a whopping 70% compared to the companies that don’t use AI and automation software.
The processing capacity of businesses that use automated loan management systems is expected to grow by 30%. This also promotes better communication with customers, who are motivated to make more informed decisions based on the customer service provided by AI bots and other automation tools. By improving the borrowers’ experience, companies can build long-lasting relationships with their clients based on trust and high-quality services. This type of software also helps in monitoring and analyzing loan portfolios.
Conclusion
As AI continues to advance, its impact on the lending industry is inevitable. By automating processes and analyzing vast amounts of data, AI-driven lending platforms can streamline the application process, improve decision-making, and enhance the overall customer experience. Businesses that choose to use automation software and AI-powered algorithms have a chance of increasing their annual revenue by more than 30%. While AI offers numerous benefits, it’s essential to find a balance between automation and services provided by a human team. By combining the efficiency of AI with the empathy of human interaction, lenders can create a seamless and personalized experience for their customers.
