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Why AI in Commercial Underwriting is Rewriting the Future of Lending

AI in Commercial Underwriting: What You Need to Know

‘Underwriting as we know it today will cease to exist by 2030.’

In 2021, management consulting company, McKinsey made this bold claim regarding AI in insurance underwriting. As we move into 2022, GiniMachine believes they’re not only right about insurance underwriting, but, in fact, about the future of AI in commercial underwriting as a whole. 

AI is rewriting the future of underwriting across all industries—from insurance to lending and everything in between. However, many providers remain unclear about how AI-based underwriting benefits their company and the best way to implement it. 

To answer that, let’s look at AI credit underwriting, how it works and why the investment is more than worth the cost. 

AI and Underwriting: What Is AI-based Underwriting?

When making a decision to underwrite a loan, numerous data has to be taken into account. For this process to be effective, it’s essential that this data is correct and up-to-date. If it isn’t, the loan risk changes and that could put your business at risk, especially if it isn’t just a singular loan affected. 

When choosing to underwrite with AI tools, you automate the process and can account for a much wider range of data, while ensuring it stays accurate and current. For instance, it can take into account of:

  • if a borrower has recently changed their job
  • has additional debt
  • small amount for their down payment
  • other information that may impact the loan decision

What’s more, it does so automatically. 

From the Dow to Covid: Why Do You Need AI Credit Underwriting?

You’ve probably heard the claims that when compared to manual underwriting services, AI can automate the process, making it faster, more accurate, and, as a result, more efficient. And it’s all true. But why does your business need AI-based underwriting?

Remember the financial crash of 2008? When the Dow Jones Industrial Average dropped over 770 points, followed by an additional 15% drop the next month. A recession ensued that saw the losses of jobs and livelihoods. 

That crash was the result of subprime mortgages and poor lending practices, in particular lending to those who weren’t particularly creditworthy. This saw the industry turn sour and collapse, with the impact felt worldwide. 

Although lending practices have moved on with tighter regulations to ensure more responsible lending, it highlights an extreme result of the impact of poor analytics and bad data. The question remains, could it happen again?

The answer is yes, but not as it did before. 

The Covid-19 crisis impacted many industries, changing the world from its traditional form, into a newer, remote, and technologically upgraded version. On the flip side, the market is also facing new challenges as businesses and individuals contend with decreases in earnings, less financial security, and lower amounts of disposable income than in previous years. Meanwhile, inflation has caused prices to increase. 

In this new setting, the lending industry has to quickly adapt to the new reality to ensure the services they are offering are appropriate, have accounted for risk, and are competitive in the new market. But how can they do so effectively?

How AI-based Underwriting Improves Loan Underwriting in Real Terms?

In the past companies have utilized custom underwriting models created with tools such as Python to assess risk. However, this process can be quite monotonous, time-consuming, and cost-ineffective to adjust these models every time your company needs to and hire much-in-demand developers to get the job done.

Alternatively, AI-based underwriting software is able to undertake this task with ease. Here’s what AI credit underwriting can do for your business:

More accurate loan repayment predictions

After all, when underwriting a loan, the bottom line is ‘how affordable is this loan and will the client be able to repay it?’ Knowing this, you can establish whether or not the loan is likely to be repaid. Although no model can boast 100% accuracy, AI-based underwriting does lower the risk and looks at data from a vast range of sources to establish accuracy.

Saves your team time

Concentrating all their time and energy on manual underwriting is a waste of your team’s precious time. By automating the process, you can deploy your team into more pressing matters and boost your team’s efficiency. 

Allows your business to grow 

Estimates show a 14% increase in sales volume within two years when companies onboard AI solutions. While these are just estimates, they highlight the potential that time-saving, efficient software tools can have on your company’s ability to scale. 

Let’s Talk about GiniMachine’s AI-based Underwriting Capabilities

GiniMachine is an AI-based prediction tool that can be used to help your company make underwriting decisions. It works using historical records and data to make predictions about future behavior. 

With as few as 1,000 records of clean data, you can get accurate data predictions in a matter of minutes. While GiniMachine doesn’t aim to make your lending decisions for you. It does give you the data you need to make efficient and accurate decisions. For example, the technology can help you to:

  • Reduce risks by up to 45%
  • Lower poor-performing loans and improve your portfolio
  • Help with customer retention and reduce churn rate
  • Bring your valuable data into the spotlight and make your data work for you.

Next Steps to Get AI in Commercial Underwriting for Your Business

Depending on your company’s needs, there are many pathways to digital transformation. Some businesses prefer to implement changes incrementally to avoid any upset with current systems. Meanwhile, others prefer a total overhaul approach. 

No matter your business needs, GiniMachine is on-hand with our smart AI underwriting solution. Our team is always ready to talk you through the ins and outs of digital transformation. The only thing left to do is get in touch. 

Interested in GiniMachine for underwriting? Get in touch with the team to know more.

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