Automated loan decisioning – solving the transition from manual to automatic loan origination process

A recent McKinsey report shows that only 18% of banks are halfway or more done with their digital transformation.  

And even the large banks that managed to digitize during Covid are 40% less productive than digital natives due to organizational silos and the need to migrate with complex legacy infrastructure.  

These inefficiencies, delays, and overhead costs inflate the price borrowers pay for financing. For lenders implementing automation across the loan lifecycle, particularly in decision-making, this presents an unprecedented opportunity.  

Manually gathering and processing credit scoring data instantly puts lenders at a disadvantage compared to competition offering instant approvals. However, with modern lending technology, creditors automatically pull and process data from various sources, including credit bureaus and bank statements based on their own evaluation criteria, reducing decision time and mitigating risks. 

But first, wanted to check if you (or your staff) would like this white paper with all important details about TurnKey Lender’s AI-Powered Credit Decision Engine

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What data can lenders use in automated loan decisioning 

Data is the cornerstone of automated loan decisioning. The more diverse and comprehensive the data set, the more precise and reliable the decisioning process.  

Traditional data points used by lenders include

• Loan application form – the information you gather in the loan application lets you get the necessary insight for all further analysis.
• Borrower’s credit history and credit score – these provide insights into past financial behavior and repayment habits.
• Income and employment statistics – these data points give an understanding of the borrower’s capacity to service the loan. 

But alternative credit scoring can provide even more insight in many cases where traditional data isn’t sufficient or accessible. It can include:  

• Utility payment history – regular payment of utilities suggests financial responsibility.
• Rental payments – consistent rental payments can demonstrate a borrower’s ability to manage long-term financial commitments.
• Social media behavior – non-traditional yet insightful, this can hint at a borrower’s lifestyle and spending habits.
• Psychometrics – behavioral analysis of the borrower during the loan application process using the built-in browser and smartphone metrics proved reliable. 

How automated loan decisioning process works 

It’s easy to say that automated loan decisioning streamlines the loan approval process, making it more efficient and accurate.  

But here’s a high-level overview of how it works: 

1. Borrower data collection – the borrower or business enters their personal and financial details into a personalized and localized application form. The richness and accuracy of this data are crucial for the next steps.
2. Data pulling – an advanced credit decision system pulls relevant data from various external sources like credit bureaus, the customer’s phone, utility companies, or even social media platforms. This enriches the data set for processing.
3. Data processing – the collected data is processed through predefined scoring models and decision rules. The accuracy of the scoring here depends on your knowledge of the market and your borrowers. With a system like TurnKey Lender, you have complete control over how the system interprets different parameters and what weight is assigned to what scoring factors.
4. Decisioning – if the application meets the set rules, the system makes an automatic loan decision. Should any issues be flagged during processing, the application is forwarded to the lender’s dedicated workspace. Here, a summary of the findings is presented, which can be expanded for detailed viewing and manual intervention if necessary.

Embracing this automated process significantly accelerates loan decisioning while reducing the chance of errors and bias. This sounds obvious until you realize the difference it makes.  

The average loan cycle time to this day is typically up to 1 week. For business loans it’s 4-5 weeks. Imagine the selling value of being able to offer same day approval.  

Using artificial intelligence and big data to grow a lending business 

According to the report on Artificial Intelligence and the Future of Financial Services by the New York Fed, AI could automate up to 40% of loan origination tasks, saving lenders an estimated $100 billion per year. Furthermore, AI could improve loan approval rates by up to 5%, leading to an additional $50 billion in loan originations, and reduce the time it takes to originate a loan by up to 50%, allowing lenders to focus on more complex tasks.  

Similar findings can be found in a mutlitude of other reports like this one by Moody’s Analytics, which underscores how automation can further reduce the time it takes to originate a loan by up to 50% and increase loan approval rates by up to 20%.  

In a nutshell, the consensus in the industry is clear: AI and automation are not just the future, but the present of the lending industry. The efficiencies they introduce in terms of speed, cost savings, and improved approval rates are pivotal for lenders aiming to stay ahead in this rapidly evolving landscape. 

But how real is it really? 

With AI, it’s often hard to instantly see if it’s really necessary or it’s used mostly for marketing buzz. 

In the case of digital lending, it is inevitable, and it is here.  

Simply because of the deep dependence of credit decisions on data which is becoming more and more accessible to business owners and technology vendors.  

Artificial intelligence gives us the ability to process immense amounts of data almost instantly. If you’re using the right approach to automating loan decisioning, these powers can be harnessed to do analytical heavy lifting for your team vastly improving the speed, depth, and accuracy of research. 

Most commonly these AI and Big Data are used to identify creditworthy borrowers who are overlooked or unfairly penalized in traditional scoring models, by analyzing non-traditional data sources. 

This is where TurnKey Lender’s Decision Engine shines most. Proprietary AI and Big Data technology praised by the industry, delivers superior automated loan decisioning. The Decision Engine is equipped to analyze diverse data sets, from traditional credit scores to alternative data like financial statements or online behavior. As a result, lenders using TurnKey Lender’s platform can confidently extend credit to a broader range of borrowers while minimizing risks. 

How TurnKey Lender automates loan decisioning 

TurnKey Lender is pioneering technological innovation in credit since 2014 with unprecedented lending intelligence and automation solutions.  

From the start, the key advantage of the company were its proprietary intelligence and sophisticated risk management and credit scoring solutions. So let’s delve into how TurnKey Lender enhances various aspects of your loan decisioning process 

1.Modern automated underwriting with AI  

TurnKey Lender’s automated underwriting software makes use of artificial intelligence and machine learning to quickly and accurately gather and evaluate borrower’s creditworthiness based on the data and the criteria you select. 

2. Advanced credit scoring techniques

Our team has configured, tested and deployed hundreds of scoring models for our customers using the TurnKey Lender’s platform. And the more tech-savvy clients make scoring changes to adjust risk levels with new insight themselves daily. TurnKey Lender provides a flexible credit scoring system that’s adaptable to different lending scenarios and regulatory environments. Analyzing these vast arrays of borrower data let’s our loan origination software deliver reliable credit assessments and automated loan decisions. 

3. Efficient loan decisioning for consumers and businesses

Be it for personal loans or business loans, TurnKey Lender’s robust capabilities can handle both. The consumer lending software ensures a streamlined decisioning process for individual borrowers. On the other hand, for businesses, the commercial lending software caters specifically to the more complex analysis allows to use business accounting and CRM data for credit scoring too.  

4. Holistic borrower evaluation for better risk management

TurnKey Lender doesn’t just stop at traditional evaluation methods. For our clients, the most common alternative credit scoring data often includes: 

• Bank statements  
• Employment data 
• Rent payment data 
• Utilities payments  
• Online behavior  
• Third-party scoring data  
• Guarantors’ data 
• Collateral assets evaluation 

5. Seamless legacy system integration

Understanding the challenges of migrating from complex legacy systems, TurnKey Lender ensures its platforms can integrate smoothly. Whether you’re looking to update your underwriting or decisioning process, the decision management system offered by TurnKey Lender guarantees a transition that doesn’t disrupt your productivity. 

Joining the new industrial revolution in credit 

The shift from manual to automated loan decisioning is not just a trend – it’s an industry imperative. And it’s not even just about the tangible benefits like the drastic cost savings and improved loan decision time/quality. It’s just where all your borrowers live. And as a lender in the world where credit gets more accessible every day, you have both bad and good news.  

• On the one hand, you have to compete online. This is different and takes effort and investment.  
• But on the other hand, with the right offering and experience, your audience reach isn’t limited by anything anymore. 

We at TurnKey Lender will be honored to be your trusted ally in conquering this new reality.