The rise of big data analytics, combined with rapidly advancing artificial intelligence (AI) and machine learning capabilities, has created a bevy of new opportunities for financial services providers to offer optimized AI lending services. 

By leveraging these data-driven tools, providers can design AI lending products that are fast and efficient, and highly relevant and accessible to a wide range of new and existing customers, while still ensuring credit decisioning is safe and prudent. 

And with myriad surveys revealing a well of unmet consumer demand for improved lending offerings, data-driven AI lending represents a major opportunity for providers to drive new revenue streams and enhance customer engagement, satisfaction and long-term loyalty. 

Here are three key ways a data-driven approach can help financial services providers offer better–and more profitable–lending solutions. 

1. Smarter, safer credit decisions

Traditional credit scoring methods are based on relatively limited data that don’t always give an accurate assessment of a potential borrower’s creditworthiness. In contrast, AI and machine learning enable a more comprehensive and dynamic approach. 

These tools can capture and analyze much larger datasets, including wider transactional and bill payment history, as well as non-traditional data such as social media activity and online behavior, to provide a more nuanced and accurate picture of a potential borrower’s likelihood to repay. 

Combining this broader data input with the predictive capabilities of AI enables a provider to make a well-informed, forward-looking assessment of a borrower’s financial health and credit risk. Meanwhile, AI’s powerful fraud-detection capabilities make it easier than ever to flag inconsistencies in application data that may indicate attempted fraudulent activity, further ensuring a safe lending process. 

2. More personalized, relevant offers 

Along with improving credit decisioning, big data also offers the ability to leverage insights gleaned from past customer behavior and activity to customize loan offers and terms to fit individual borrower needs. 

Lenders can use this information to tailor what type of loan is offered to a given customer and when, as well as interest rates, repayment terms, and loan amounts–a personalized approach that ensures loan offers are highly contextual and relevant, meeting users’ unique needs and preferences and helping foster long-term satisfaction and loyalty. 

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Furthermore, AI can continually monitor relevant datasets, dynamically suggest loan products or adjustments to existing loans based on changes in a borrower’s financial situation or behavior, continually ensuring that offers and terms are attractive for the customer and financially prudent for the lender.

3. Enhanced servicing and support 

With customer-centricity becoming ever-more critical to success in financial services, loan providers can leverage data and AI to offer significantly improved customer support experiences to borrowers. 

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Today’s highly sophisticated chatbots and conversational AI-driven customer service tools can provide fast, relevant, highly functional assistance on a basis across a multitude of channels and contexts, enabling borrowers to apply for loans, track applications and manage repayments on a 24/7 basis, via the channels and platforms that are most convenient for them. 

By offering these positive, user-friendly support experiences, providers can stand out from the competition, generate high levels of customer satisfaction and deepen engagement over the long term–all critical elements of driving robust, durable revenue streams from loan products. 

Want to learn more about data-driven and AI lending?

Contact us to find out how your platform can reap the rewards of data-driven AI lending.