Explore the impact of AI in commercial loan origination - reducing human error, improving customer experience, and appealing to a broader customer base.
The arrival of artificial intelligence (AI) tools is rapidly changing commercial lending.
Although many banks already incorporate digital information management systems, these banks also rely on manual data entry and analysis performed by brokers whose labor would be more valuable on other duties. About 90% of employees who use AI tools have more time for those important tasks.
In the commercial loan origination space, AI tools provide the opportunity to cut costs, streamline loan processes, and enhance decision-making and risk analysis. By transitioning manual processes into the digital space with an AI overlay, commercial lenders can improve efficiency and appeal to a broader customer base.
Incorporating AI into your loan process reduces human error and improves the customer experience.
No matter whether you already incorporate AI into your origination process, the commercial lending cycle typically follows these steps:
A customer begins the commercial loan process by contacting the prospective lender. At this point, the customer provides preliminary documents, such as bank records, tax returns, and income verification.
If the customer satisfies your prequalification criteria, you may then collect personal information about the client. This includes the borrower’s financial health, the intended purpose of the loan, and any other information necessary to analyze the requested transaction.
The formal application is then evaluated by the credit or risk department. Your analysts likely cross-check any discrepancies with the customer and perform necessary internal audits.
Arguably the most important step in the loan origination process, underwriting is when you create a risk profile and evaluate the customer’s credit worthiness. Factors to consider include credit history, debt to income ratio, employment history, income, etc.
With the green light from your risk department, you can now provide a conditional approval. At this point, you’ll also conduct your final review and put together a loan package that may include offers from third-parties, such as optional insurance coverage.
Final approval occurs with the closing of the transaction. You’ll provide the closing disclosure and review any final loan estimates and covenants.
One task common to each of the loan origination steps is manually completing physical paperwork. This creates redundancy, invites human error, and drives up costs. By incorporating AI into your origination platform, you can improve loan processing, enhance your risk management analysis, and appeal to a broader customer base. Not to mention some companies have experienced a return on investment of hundreds of thousands of dollars.
Incorporating AI into your origination platform streamlines the origination process. Borrowers initiate the application process through digital platforms, like your website, and provide electronic documents that can be verified instantaneously through optical character recognition (OCR) and neuro-linguistic programming (NLP). The AI’s machine learning algorithm then extracts and analyzes the data rapidly, which reduces man hours and decreases human error.
AI loans can also incorporate real-time market activities to capture market trends. By relying on data inputs, the AI software can generate predictive models and detailed forecasts that assist you with business planning and decision-making. The AI then uses market conditions and actual customer data to provide personalized financial advice.
Another example of human error caused by manual data entry and review by brokers is the introduction of bias. AI technology analyzes customer data with an objective lens that removes, or at least reduces, human bias. This not only promotes fairer lending practices but also ensures equal access to affordable credit for all individuals and businesses.
Some lenders anticipate that implementing AI technologies into the loan origination process is more risk than reward. But that doesn’t have to be the case. While AI is an emerging and rapidly evolving technology, you can reap the benefits without suffering adverse effects by applying traditional data security and corporate governance principles.
One truth of the modern economy is that our data is out there. The nature of online banking, e-commerce platforms, and social media platforms requires consumers to regularly expose their personal information. Machine learning algorithms and AI platforms then consume data to provide analytic models. Before using your customers’ data to create a more efficient and reliable origination process, obtaining their consent is crucial.
In the same way that you implement employee training procedures to show loan officers how to handle sensitive customer data, you can also apply these procedures to an AI platform. This requires applying a data protection framework with a clear permission structure, defined data hierarchy, and rapid-response recovery approach.
With data breaches costing the American economy hundreds of millions of dollars, a robust data protection program is essential, especially considering the global average total cost of a breach rising to USD 4.35 million in 2022.
While you have a responsibility to protect the customer data you receive, you also have a duty to ensure that internal and external stakeholders understand the AI’s decision-making processes. For instance, internal users need the ability to adjust the AI’s model on a go-forward basis. Customers need to be able to understand your loan decisions and the factors considered by the AI. By avoiding a black-box model, you ensure a predictable response from your technology.
Although AI loan systems have the power to eliminate discrimination, the system’s outputs are only as good as its inputs. Because machine learning algorithms aggregate broad swaths of information, it’s important to ensure that this information is anonymized and free of personally identifiable information (PII). If not, the lender – whether online or human – is more likely to make higher profits from minority borrowers.
The benefits of adding AI and machine learning tools to your commercial lending operations outweigh the potential risks. Combining existing corporate governance and data protection protocols with your preferred AI tool will solve security issues before they arise.
This provides commercial lenders an opportunity to collaborate with a third-party vendor whose sole function is to facilitate the seamless integration of AI technologies into your existing processes. This may look like building upon widely available large language models, such as Open AI’s ChatGPT or Alphabet’s Bard, or constructing a model from scratch using customer data and market trends.
To summarize, the benefits of AI loans include:
Reduce labor costs by adding AI tools to routine processes.
Provide customers – who overwhelmingly look for speed – with an online interface that collects and aggregates data.
Construct predictive models suggesting loan outcomes and default rates using customer data.
Chatbots and virtual assistants using AI technologies can answer routine customer questions, address basic concerns, and keep customers apprised of their application status.
Machine learning and AI technologies are already revolutionizing commercial industries, and lending is expected to become the second-largest fintech sector by 2030. In the commercial lending space, AI can make the loan origination process more friendly toward the customer. Third-party software vendors now provide tools that collect, aggregate, and sort customer data. This eliminates the need for workers to spend valuable hours completing mundane tasks. Adding AI to your commercial loans can increase fairness, reduce costs, and provide a speedier onboarding process.
To learn more and request a demo, visit FileInvite today.
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