TurnKey Lender

7 Artificial Intelligence Applications in Digital Lending

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Digitalization leaves no industry untouched. In the last decades, lenders, traditional and alternative, have been on the lookout for new technologies to take them ahead of the competition. Software that would make credit decisioning and loan management safer, faster, and cheaper. Naturally, AI has been a focus for most.  

Many of the AI applications are still in the R&D phase, but many are already here and helping real businesses save money and streamline processes. 

But before we start looking at the specifics, let’s straighten up our vocabulary. Artificial Intelligence (AI) is quite a vague term. Feels like lately it’s used for marketing reasons far more commonly than for solving actual problems. Some of the more specific niches of AI that can apply to lending include machine learning, deep learning, natural language processing (NLP), and image recognition.

AI in credit decisioning and underwriting

Credit scoring and underwriting are still some of the biggest challenges and risk sources for most lending operations. That is why TurnKey Lender focused its efforts on these two domains first. 

The end-to-end lending system comes with all the functionality one needs to run a crediting business of pretty much any kind. And the benefits of deploying TurnKey Lender’s AI-driven solutions manifest both for the lender and the borrower. There’s no guesswork involved in the credit decisioning anymore, even when there’s virtually no data about the borrower. 

Thanks to the sophisticated self-learning algorithms, lending businesses make faster and more accurate decisions based on the proprietary scoring technologies. Now the application can be analyzed and the loan issued to the right people within minutes where it used to take days. Besides, lenders can tap into previously underserved or unserved demographics — the people who may have been overlooked in the past. 

Lending operations tend to process large amounts of consumer data which remained unused up until recently. This left space for human error, lengthy loan approval process, and weak fraud protection. TurnKey Lender solved this problem with advanced self-learning algorithms. They analyze large sets of consumer data, learn the behavior patterns, and make risk evaluations and credit scoring based on this data.

As mentioned above, TurnKey Lender mainly uses machine learning for credit decisioning and risk evaluation. TurnKey Lender’s CEO, Dmitry Voronenko (Ph.D. in Artificial Intelligence), guided the development of the system. He has put together a team of scientists that did machine learning and scoring projects for Boeing, LG, Bank of America, and Stanford University in the past. 

They utilized deep neural networks with self-learning scoring models based on both traditional and alternative evaluation approaches and data sources. The system learns to use prediction, classification, clustering, and association to process loan applications through user data. 

For safety purposes, the system doesn’t just use the data client is providing but also pulls the available information from various sources (like the credit bureaus and social networks). TurnKey Lender’s algorithms process the data and then present it in the form of a risk evaluation. 

Credit decisions backed by psychology and AI

Even though the credit decisioing that comes built-in with the TurnKey Lender’s platform presents an excellent usage of AI on its own, the team didn’t stop there. The algorithms and models are polished and upgraded to account for more factors and learn faster with each new release. The experience the team got working with clients from all over the world led it to create a unique, standalone, product called TurnKey Lender Psychometrics. 

It’s an app that uses the original AI-powered decisioning engine as a starting point and enhances it with a psychological evaluation. The test, combined with the deep neural networks which analyze its results, allows to accurately evaluate loan risks and potential borrowers even in cases when there’s no access to their credit history or even bank accounts.

Here are fresh comparisons of TurnKey Lender’s solutions and its closest competitors, nCino and Cloudlending.

Regulatory compliance and AI in lending

Problems with compliance cost some businesses billions. So even though implementing end-of-the-line AI into your compliance workflow is costly, it’s still way cheaper than having expenses required for a bigger staff of compliance officers. Not to mention the cost of running a higher risk of getting fined.

Of course, AI for compliance relies heavily on specific jurisdictions and the law differences. But keep in mind that some things are universal. For example, no matter where you work, you got to fight identity fraud and any unlawful activities. In addition to regulations, weeding out wrongdoers is in the best interests of any lender. 

As of now, you still need to have proper compliance blueprint and human involvement in the compliance process. But you can implement AI software to address the following:

  • Regulatory updates – tracking and monitoring 
  • Borrower identification
  • Stress testing of the system
  • Identity fraud

[related-solutions]

AI use cases for lending security 

Cybersecurity is an endless race between fraudsters and white-hat developers who struggle to create protected systems. And the good guys sometimes lose. Big time. 

 

Biggest data breaches of the 21st century

Source: CSO

The thing about data security is that the software requires regular updates and maintenance to combat evolving threats. That is why self-teaching AI already plays a massive role in preventing and fighting cybercrime. 

An important innovation here is, of course, image recognition technology. For example, JPMorgan Chase’s tech already surpasses humans abilities. Not to mention, saves the company a whopping 360,000 hours of work. The technology is at a stage when accurate image recognition isn’t something special. It’s a rather mundane thing you can (and probably should) have in place in a serious lending business. 

The specific parts of the security process that can benefit from AI implementation are:

  • Spam filter applications
  • Network intrusion detection and prevention
  • Fraud detection
  • Credit scoring and next-best offers
  • Botnet detection
  • User authentication

Intelligent self-learning software can see patterns and help lending business eliminate security threats. And not just that. 

Due to strict regulations and high sensitivity of data, financial businesses tend to be very cautious, not willing to take any undue risks. So other than protecting from the dangers, smart technology can also help reduce the number of false positives, thus increasing profits. 

A 2015 study by Javelin Strategy shows that false positives (wrongly rejected legitimate transactions) account for $118 billions of dollars in annual losses. And that’s not counting the potential lost business that won’t come back after being rejected once. Machine learning can help address that by learning about your customers and approving more of the safe accounts.

Accounting and AI in lending

As per the article Jean Baptiste Su wrote for Forbes, “…by 2020, accounting tasks including tax, payroll, audits, and banking will be fully automated using AI-based technologies, which will disrupt the accounting industry.” 

And even though we’re no fans of disruption, there’s no stopping technology. And the best business can do is embrace change and enjoy the benefits of automated processes.

AI-driven accounting software for lenders can analyze receipts and invoices extracting information like VAT identification numbers from it in the form of data points. Then it may pass the data to the reporting module of a platform like TurnKey Lender. It, in turn, will help with regulatory compliance. 

Keep in mind, that generally, this software learns continuously. And over time, it will handle each client with more insight and accuracy and extract more information about borrowers faster. 

Streamlining user experience through AI

The automation is here to stay, but this doesn’t mean that your users don’t expect to receive a personal experience. Live chat solutions and various bots powered by AI can help you provide instant quality support 24/7 and only escalate complex issues to a real person. So you cut costs while improving service. 

If you collect the right data and feed it to the right algorithms, you can automatically offer tailored loans and plans based for each client. Another approach would be to do the little things like greet them by name in their language, adjust the offering on the website based on their location, etc. Your users will be thankful for personalization of experience, products, and services.

Funding insights in P2P with AI

We’ve already covered how big a phenomenon peer-to-peer lending is right now. And no wonder, since with the right wealth management, it can be extremely beneficial both for the investor and the borrower. But making money of investing is hard unless you know what you’re doing. That’s where investors can benefit from choosing a P2P platform that runs on TurnKey Lender. 

We use the same AI-driven credit decisioning techniques to evaluate borrowers who opt-in for funds within our P2P platform. This way, AI helps investors make safer and more beneficial decisions. In this scenario, the investor only deals with one metric – borrower evaluation. And for the lender everything from filling out the form for the first time to collection and payment reports is automatic.

Next steps

Real and practical AI applications aren’t matters of science fiction anymore. This software already brings real value to the business owners. And in the lending space, TurnKey Lender’s intelligent software leads the race by example. 

Biggest benefits AI brings into lending space are:

  • Faster and more accurate decision-making
  • Increased sales through repeated business
  • Reduced operational costs
  • Identification of potential defaulters
  • Increased speed of work processes
  • Boosted operational efficiency
  • Reduction of operational costs
  • Simplified regulatory compliance process
  • Streamlined and personal customer experience
  • Easier analysis of large volumes of data 

TurnKey Lender easily integrates with other solutions. If a business needs to implement AI automation of some processes, our team can take care of that. 

But TurnKey Lender isn’t just about AI. On a higher level, we offer an all-in-one intelligent platform that automates the entire lending process. The solution includes functionality that covers loan origination, underwriting, collateral management, borrower evaluation, risk management, debt collection, loan servicing, reporting, supervision, and regulatory compliance. The meaningful use of deep neural networks and machine learning combined with big data is what makes TurnKey Lender stand out.  

To see it in action, get a free TurnKey Lender trial or schedule a demo and see exactly why we’re the best in the business. 

Share:

Digitalization leaves no industry untouched. In the last decades, lenders, traditional and alternative, have been on the lookout for new technologies to take them ahead of the competition. Software that would make credit decisioning and loan management safer, faster, and cheaper. Naturally, AI has been a focus for most.  

Many of the AI applications are still in the R&D phase, but many are already here and helping real businesses save money and streamline processes. 

But before we start looking at the specifics, let’s straighten up our vocabulary. Artificial Intelligence (AI) is quite a vague term. Feels like lately it’s used for marketing reasons far more commonly than for solving actual problems. Some of the more specific niches of AI that can apply to lending include machine learning, deep learning, natural language processing (NLP), and image recognition.

AI in credit decisioning and underwriting

Credit scoring and underwriting are still some of the biggest challenges and risk sources for most lending operations. That is why TurnKey Lender focused its efforts on these two domains first. 

The end-to-end lending system comes with all the functionality one needs to run a crediting business of pretty much any kind. And the benefits of deploying TurnKey Lender’s AI-driven solutions manifest both for the lender and the borrower. There’s no guesswork involved in the credit decisioning anymore, even when there’s virtually no data about the borrower. 

Thanks to the sophisticated self-learning algorithms, lending businesses make faster and more accurate decisions based on the proprietary scoring technologies. Now the application can be analyzed and the loan issued to the right people within minutes where it used to take days. Besides, lenders can tap into previously underserved or unserved demographics — the people who may have been overlooked in the past. 

Lending operations tend to process large amounts of consumer data which remained unused up until recently. This left space for human error, lengthy loan approval process, and weak fraud protection. TurnKey Lender solved this problem with advanced self-learning algorithms. They analyze large sets of consumer data, learn the behavior patterns, and make risk evaluations and credit scoring based on this data.

As mentioned above, TurnKey Lender mainly uses machine learning for credit decisioning and risk evaluation. TurnKey Lender’s CEO, Dmitry Voronenko (Ph.D. in Artificial Intelligence), guided the development of the system. He has put together a team of scientists that did machine learning and scoring projects for Boeing, LG, Bank of America, and Stanford University in the past. 

They utilized deep neural networks with self-learning scoring models based on both traditional and alternative evaluation approaches and data sources. The system learns to use prediction, classification, clustering, and association to process loan applications through user data. 

For safety purposes, the system doesn’t just use the data client is providing but also pulls the available information from various sources (like the credit bureaus and social networks). TurnKey Lender’s algorithms process the data and then present it in the form of a risk evaluation. 

Credit decisions backed by psychology and AI

Even though the credit decisioing that comes built-in with the TurnKey Lender’s platform presents an excellent usage of AI on its own, the team didn’t stop there. The algorithms and models are polished and upgraded to account for more factors and learn faster with each new release. The experience the team got working with clients from all over the world led it to create a unique, standalone, product called TurnKey Lender Psychometrics. 

It’s an app that uses the original AI-powered decisioning engine as a starting point and enhances it with a psychological evaluation. The test, combined with the deep neural networks which analyze its results, allows to accurately evaluate loan risks and potential borrowers even in cases when there’s no access to their credit history or even bank accounts.

Here are fresh comparisons of TurnKey Lender’s solutions and its closest competitors, nCino and Cloudlending.

Regulatory compliance and AI in lending

Problems with compliance cost some businesses billions. So even though implementing end-of-the-line AI into your compliance workflow is costly, it’s still way cheaper than having expenses required for a bigger staff of compliance officers. Not to mention the cost of running a higher risk of getting fined.

Of course, AI for compliance relies heavily on specific jurisdictions and the law differences. But keep in mind that some things are universal. For example, no matter where you work, you got to fight identity fraud and any unlawful activities. In addition to regulations, weeding out wrongdoers is in the best interests of any lender. 

As of now, you still need to have proper compliance blueprint and human involvement in the compliance process. But you can implement AI software to address the following:

  • Regulatory updates – tracking and monitoring 
  • Borrower identification
  • Stress testing of the system
  • Identity fraud

[related-solutions]

AI use cases for lending security 

Cybersecurity is an endless race between fraudsters and white-hat developers who struggle to create protected systems. And the good guys sometimes lose. Big time. 

 

Biggest data breaches of the 21st century

Source: CSO

The thing about data security is that the software requires regular updates and maintenance to combat evolving threats. That is why self-teaching AI already plays a massive role in preventing and fighting cybercrime. 

An important innovation here is, of course, image recognition technology. For example, JPMorgan Chase’s tech already surpasses humans abilities. Not to mention, saves the company a whopping 360,000 hours of work. The technology is at a stage when accurate image recognition isn’t something special. It’s a rather mundane thing you can (and probably should) have in place in a serious lending business. 

The specific parts of the security process that can benefit from AI implementation are:

  • Spam filter applications
  • Network intrusion detection and prevention
  • Fraud detection
  • Credit scoring and next-best offers
  • Botnet detection
  • User authentication

Intelligent self-learning software can see patterns and help lending business eliminate security threats. And not just that. 

Due to strict regulations and high sensitivity of data, financial businesses tend to be very cautious, not willing to take any undue risks. So other than protecting from the dangers, smart technology can also help reduce the number of false positives, thus increasing profits. 

A 2015 study by Javelin Strategy shows that false positives (wrongly rejected legitimate transactions) account for $118 billions of dollars in annual losses. And that’s not counting the potential lost business that won’t come back after being rejected once. Machine learning can help address that by learning about your customers and approving more of the safe accounts.

Accounting and AI in lending

As per the article Jean Baptiste Su wrote for Forbes, “…by 2020, accounting tasks including tax, payroll, audits, and banking will be fully automated using AI-based technologies, which will disrupt the accounting industry.” 

And even though we’re no fans of disruption, there’s no stopping technology. And the best business can do is embrace change and enjoy the benefits of automated processes.

AI-driven accounting software for lenders can analyze receipts and invoices extracting information like VAT identification numbers from it in the form of data points. Then it may pass the data to the reporting module of a platform like TurnKey Lender. It, in turn, will help with regulatory compliance. 

Keep in mind, that generally, this software learns continuously. And over time, it will handle each client with more insight and accuracy and extract more information about borrowers faster. 

Streamlining user experience through AI

The automation is here to stay, but this doesn’t mean that your users don’t expect to receive a personal experience. Live chat solutions and various bots powered by AI can help you provide instant quality support 24/7 and only escalate complex issues to a real person. So you cut costs while improving service. 

If you collect the right data and feed it to the right algorithms, you can automatically offer tailored loans and plans based for each client. Another approach would be to do the little things like greet them by name in their language, adjust the offering on the website based on their location, etc. Your users will be thankful for personalization of experience, products, and services.

Funding insights in P2P with AI

We’ve already covered how big a phenomenon peer-to-peer lending is right now. And no wonder, since with the right wealth management, it can be extremely beneficial both for the investor and the borrower. But making money of investing is hard unless you know what you’re doing. That’s where investors can benefit from choosing a P2P platform that runs on TurnKey Lender. 

We use the same AI-driven credit decisioning techniques to evaluate borrowers who opt-in for funds within our P2P platform. This way, AI helps investors make safer and more beneficial decisions. In this scenario, the investor only deals with one metric – borrower evaluation. And for the lender everything from filling out the form for the first time to collection and payment reports is automatic.

Next steps

Real and practical AI applications aren’t matters of science fiction anymore. This software already brings real value to the business owners. And in the lending space, TurnKey Lender’s intelligent software leads the race by example. 

Biggest benefits AI brings into lending space are:

  • Faster and more accurate decision-making
  • Increased sales through repeated business
  • Reduced operational costs
  • Identification of potential defaulters
  • Increased speed of work processes
  • Boosted operational efficiency
  • Reduction of operational costs
  • Simplified regulatory compliance process
  • Streamlined and personal customer experience
  • Easier analysis of large volumes of data 

TurnKey Lender easily integrates with other solutions. If a business needs to implement AI automation of some processes, our team can take care of that. 

But TurnKey Lender isn’t just about AI. On a higher level, we offer an all-in-one intelligent platform that automates the entire lending process. The solution includes functionality that covers loan origination, underwriting, collateral management, borrower evaluation, risk management, debt collection, loan servicing, reporting, supervision, and regulatory compliance. The meaningful use of deep neural networks and machine learning combined with big data is what makes TurnKey Lender stand out.  

To see it in action, get a free TurnKey Lender trial or schedule a demo and see exactly why we’re the best in the business. 

Share:

RELATED SOLUTIONS

DV interview blog article november 2023

How traditional finance providers can capitalize on the embedded lending revolution

auto-dealership-financing-software-basics-turnkey-lender

Why Auto Dealers Should Consider Digitizing Their In-House Lending Programs

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