4 ways in which Lendsqr wants to use AI for lenders

The history of AI is a long and rich one, dating back to the mid 20th century. Companies like Apple with Siri and Amazon with Alexa have been using AI for decades

But the emergence of ChatGPT and other LLMs in late 2022 changed AI from something only the best tech companies have to an everyday utility for the average Joe.

According to a recent Forbes Advisor survey, a significant portion of businesses are already using or plan to use AI in various aspects of their operations. 73% of businesses use or plan to use AI-powered chatbots for instant messaging. 53% apply AI to improve production processes, while 51% adopt AI for process automation.

These statistics highlight the growing adoption of AI across various industries, and lending is prime for disruption too.

Traditionally, lending has involved a significant degree of uncertainty. Unlike a typical business transaction where you exchange goods or services for immediate payment, a loan is a bet on a borrower’s future ability to repay. Will Mr. Adu Jones repay the loan you granted him today?

This inherent uncertainty can make it challenging for lenders to assess creditworthiness and determine who qualifies for a loan.

But, AI is emerging as a powerful tool that can help lenders navigate this uncertainty. Lendsqr is taking advantage of it to empower lenders with smarter decision-making capabilities and reshape how lending works today.

Let’s dive in.

AI is transforming global businesses like Klarna significantly

Klarna has aggressively embraced AI across its customer service, marketing, employee productivity, and product innovation.

On February 27 2024, Klarna launched an AI-powered customer service assistant that handled 2.3 million conversations in its first month, accounting for two-thirds of Klarna’s customer service chats.

The AI assistant is capable of handling a wide range of customer inquiries across 35 languages, 24/7. It has matched human agents in customer satisfaction scores and led to a 25% drop in repeat inquiries. Customers now resolve issues in less than 2 minutes, down from 11 minutes previously.

Klarna estimates the AI assistant will drive $40 million in profit improvements for the company in 2024. 90% of Klarna’s employees are using generative AI tools powered by OpenAI on a daily basis. The AI tools have enabled significant cost savings, with a 25% reduction in marketing agency spend.

Klarna has developed several AI-powered tools to help customers find and discover products as well:

• A ChatGPT plugin called “Klarna Shopping” that provides a personalized shopping assistant experience,
• A new AI-powered personalized shopping feed that provides consumers with a stream of relevant product recommendations
• An AI image recognition tool that allows users to point their phone at a product like clothing or electronics and get recommendations, and
• AI to help consumers discover trend-defying products.

AI is responsible for 37% of Klarna’s marketing cost savings, about $10 million annually. The company has streamlined processes like image generation, copywriting, and website/app updates using AI.

Klarna reported a 29% year-over-year increase in revenue in Q1 2024, driven by expansion in the US market. The company reduced operating expenses by 11% in Q1, with AI-driven efficiencies being a key contributor.

Klarna is preparing for a potential $20 billion IPO later this year, buoyed by its AI-powered transformation.

Unfortunately, businesses like Chegg got the shorter end of the stick

ChatGPT and other AI-powered platforms have emerged as popular alternatives to Chegg’s traditional tutoring and homework help services. More students are turning to these AI tools for assistance, leading to a decline in Chegg’s user base and revenue.

Chegg’s stock price has fallen 64.3% since the beginning of 2023, signaling a loss of investor confidence. The company’s CEO admitted that ChatGPT has “rendered its business obsolete”.

Chegg has been unable to keep up with the rapid pace of AI innovation. The company’s human-based tutoring model is costly and difficult to scale compared to the instant, scalable solutions provided by AI platforms.

Chegg has also been criticized for lacking innovation and failing to explore new areas like AI-powered education technologies. This has left the company vulnerable to disruption from more agile competitors leveraging AI.

While Chegg’s CEO, Dan Rosensweig, remains optimistic about integrating AI with human-based support, the company expects lower-than-expected revenue in Q2 2023 due to the impact of AI on its business.

For Lendsqr, AI is a hail mary

It can help us help lenders succeed. We’ve seen AI already mainstream in the lending industry.

1. It can enhance the management of loans by helping with quick assessment of loan risks and streamlining the loan process.
2. AI is being used to determine creditworthiness, especially for borrowers without credit histories, by analyzing alternative data sources.
3. It can improve efficiency and accuracy in loan processing, enhance risk management, expedite approvals, and offer personalized loan products.
4. AI has the potential to reduce biases in manual credit assessments and promote financial inclusion by providing fair and unbiased evaluations.
5. Banks are exploring the use of AI to address past discrimination in lending and support a more inclusive economy, but need to be careful that AI systems do not mirror human biases.

We are developing AI for behavior analytics

Traditionally, lenders mainly rely on credit scores and past financial information to decide if someone is creditworthy. But this approach misses a lot of useful information that’s hiding in all the data that’s collected these days.

Imagine you’re faced with a giant jigsaw puzzle with hundreds of pieces. It can be overwhelming to put it all together by hand. That’s similar to the challenge lenders face when they try to analyze all the data on loan applications, how borrowers interact with them, and how they repay their loans.

But what if we could use AI to help lenders quickly sift through the information and make decisions easier and quicker?

AI-powered assessment for those without credit reports

Traditional lending often relies on two main things to decide if someone is creditworthy: their ability to repay the loan (like their income and job) and their financial background (like their credit history and bank statements).

These are important factors, but they can leave out a large number of people, who would be good borrowers, out in the cold.

Becky, a house manager, goes to apply for a loan today without financial statements, and doesn’t use internet banking either. Even though she’s good for the money, she will never get the loan because she doesn’t have any credit history.

Featured read: The punishments and disadvantages of having a bad credit score

We are proposing tackling this challenge with alternative credit scoring powered by AI,  in collaboration with the federal government using the AI grant.

Instead of relying solely on documents, we’re experimenting using AI to get a more complete picture of the borrower themself. This means we can look beyond pay stubs and bank statements to understand the person’s potential for repaying a loan.

This might sound futuristic, but it builds on a very human concept: intuition. When we meet someone new, we naturally form an impression of them based on how they talk, behave and present themselves.

Lendsqr aims to leverage AI to replicate this process in a digital and scalable way. We are creating a type of scoring methodology where we forget about everything that people bring, because those things are a means to figure out who the person is.

Here’s how it would work:

The video interview: Borrowers will engage in a short video interview with a user-friendly AI system. They’ll explain their financial situation and the purpose of the loan.

AI analysis: Behind the scenes, sophisticated AI algorithms will analyze various aspects of the video and conversation. This includes factors like speech patterns, word choice, and even facial expressions.

Alternative credit score: Then, the AI generates an alternative credit score that reflects the borrower’s true potential, independent of traditional documentation.

We believe this approach holds immense potential for millions of individuals who are currently excluded from the traditional financial system. It opens doors for lenders to reach new customers, offer loans to reliable borrowers who might have been missed before, as well as pave the way for a fairer and accessible lending landscape.

AI-powered chatbots for a personalized customer experience

Many chatbots today are like simple answering machines. They can only respond to certain questions in a pre-programmed way. This can be frustrating for customers who need more nuanced help.

At Lendsqr, we’re experimenting with a smarter kind of chatbot powered by AI.

This chatbot will be able to have real conversations with customers, understanding their questions and responding in a helpful and informative way. It will also be able to access a customer’s information and loan details, so it can provide personalized support.

For example, if you contact the chatbot with a question about your loan payment, it will be able to greet you by name, confirm the specific loan you’re referring to, and then offer specific solutions or instructions tailored to your situation.

This personalized approach will make a big difference in the customer experience, making it feel more like you’re actually talking to a person. It will also improve your customer support and team efficiency.

We’re already seeing amazing results from our internal testing with ChatGPT, and we’re excited to launch this revolutionary chatbot service soon.

Featured read: 6 features in your loan app that chases borrowers away

AI-powered loan recommendations

Lendsqr isn’t just using AI to understand borrowers better; we’re also leveraging it to provide smarter loan recommendations.

Here’s how it would work:

When a customer comes in, our AI system will analyze their data, considering factors like their browsing history, financial information, and even the source of their visit (e.g., did they come from a webpage about a specific loan type?).

Based on this analysis, the AI might automatically suggest a loan product that seems like a good fit for the customer’s needs. For example, if a customer is asking for information about personal loans, the AI would auto suggest a personalized loan amount based on what they need and what they can afford.

We believe that responsible lending practices go hand-in-hand with offering the right products to the right people. This way,  customers won’t need to wade through a sea of generic loan options to find the one that meets their needs. Ultimately, this leads to a more satisfying customer experience.

Featured read: How to use Lendsqr API to power your loan app

We’re still running experiments on AI for lenders

While some of these ideas are still under development, Lendsqr is committed to a rigorous testing process. We have the advantage of our unique internal lender platform called Irorun, which boasts nearly a million customers.

Our philosophy is simple: we don’t gamble with our customers’ businesses. That’s why we prioritize experimenting and refining our AI models in a safe and controlled environment before rolling them out to the broader market.

Our commitment to responsible innovation ensures that our customers can always expect the best possible lending experience.