Merchant underwriting is a critical task; when done correctly, it protects acquirers and mitigates costly risks. For wholesale Independent Sales Organizations (ISOs), payment facilitators and payment processors—all of which already operate on thin margins—proper underwriting can be the difference between profit and loss.

Since it can be a slow and difficult process, many organizations consider underwriting a weakness rather than a strength. Luckily, advances in payments technologies are changing that. Today, artificial intelligence (AI) is redefining how payment providers approach risk management by making underwriting faster and more efficient.

The Underwriting Paradox

The primary problems with manual underwriting are inconsistency and speed. Running identity checks, checking the internet for red flags, verifying application data and reviewing databases takes time. Underwriters sometimes need a week or more to complete a thorough risk assessment on a new merchant. This slow onboarding process is frustrating for merchants; it delays time-to-processing, which delays residual generation.

Unfortunately, many underwriters are pressured to do their work too quickly, making it impossible to assess merchants effectively. The result is often a rushed, incomplete process that onboards the merchant but risks overlooking red flags.

How Artificial Intelligence Is Redefining Underwriting

Automation is the key to solving the underwriting dilemma. In the past, automated underwriting solutions were only marginally better than the manual process. Today, faster, more reliable AI-powered underwriting tools are changing how acquirers handle the complexities of due diligence.

AI Empowers Underwriters by Performing Checks at Superhuman Speed

Traditionally, to check a merchant against a sanctions list or negative file, a human would log in, search for information, review the results and assess their meaning. A single search could take 10 minutes or more. Now, a computer can do the same job in a fraction of a second. Multiplied by dozens (or potentially hundreds) of checks per merchant, these solutions eliminate the inefficiency associated with traditional underwriting.

The right tools minimize repetitive tasks, allowing human underwriters to focus on customer support and complex decision-making.

AI Ensures Completeness in Every Risk Analysis

Examining data to verify a merchant processing application (MPA) can be exhausting. Even the most thorough underwriters can miss checks and overlook key data—especially in a crunch.

AI, on the other hand, doesn’t get tired or take shortcuts. AI-powered systems analyze merchant data with the same level of accuracy every time and will never miss a check due to fatigue or pressure to finish quickly. This consistency offers human underwriters peace of mind, knowing that results are accurate and complete.

How AI-Powered Automated Underwriting Works

Multiple automated underwriting tools are available, each with unique processes. The following describes the general high-level process a payment provider can expect from a tool like NMI’s ScanX.

Underwriting During Initial Onboarding

The initial underwriting of a new merchant through an AI-powered system consists of four basic steps:

  • Initial underwriting
  • Analysis and checks
  • Risk scoring and reporting
  • Final decision-making

Step One: Sending the Merchant to Underwriting

The first step in automated underwriting is getting the MPA data into the system. For companies using digital MPAs, the system automatically pulls key information from a mapped PDF or web form.

Payment providers using a merchant relationship management (MRM) system can also send a merchant to underwriting with a simple status change. The MRM then sends all the necessary data to the underwriting tool and begins the process automatically. In either case, sending an MPA to underwriting can be done in a few clicks, and it takes well under a minute.

BNPL platforms offer payment flexibility with no risk to the merchant. As economic conditions tighten, consumers may rely more heavily on BNPL to cover the cost of everyday purchases, including groceries, rent and gas.

Step Two: The AI Begins Analysis

Once the merchant application data is received, the AI-powered underwriting system will perform several checks. Users can determine which checks the system performs by pre-defining different merchant categories. For instance, some merchants might require 100+ checks, while others only need 20 or 30.

The system will automatically verify the data included in the merchant processing agreement (MPA). Then, it will check this information against various sources, including commercial databases, review sites, Google Maps, law enforcement and sanctions lists, legal filings and more. Depending on the number of checks it runs, the system can complete the entire process in less than two minutes.

Step Three: Returning a Risk Score and Red Flags

With the checks complete, the system returns a report with two key components. The first is a risk score out of 100, which indicates how risky the AI thinks the merchant is. The second is a list of any flags triggered during the analysis.

The risk score makes it easy for underwriters to assess overall merchant risk, while the detailed flag breakdown tells them where additional investigation is needed. For MRM users, the system automatically passes reports back to the CRM (customer relationship management) tool and changes the merchant status depending on the outcome of its analysis.

Step Four: Approval for Onboarding

The final step is to approve the application, decline it or pend for further investigation. Users can program the system to automatically decide the outcome based on the overall risk score and triggered flags.

Users can also program the system to require human approval for specific scores or for all applications. This allows underwriters to choose how much of the workload they automate based on risk tolerance.

Offer Peace of Mind: Make Checkout Feel Secure for Shoppers

Certain automated underwriting systems monitor merchant risk for the lifetime of the processing relationship. These tools continually review each merchant’s account to detect changes in their risk profile and trigger alerts if they find something strange.

This enables payment providers to quickly catch changes in a merchant’s behaviors, business practices or vital information. AI-powered monitoring systems minimize risk, ensuring optimized pricing and eliminating merchant fraud like bust-out schemes, identity swaps and business model swaps

Stop Merchant Fraud in Its Tracks with NMI’s AI-Powered Underwriting

NMI offers the industry’s most advanced AI underwriting system—ScanX. With this tool, providers can significantly reduce the time it takes to underwrite a new merchant. They can also monitor evolving merchant risk transparently and automatically for the lifetime of a processing relationship with MonitorX. These solutions integrate seamlessly into existing workflows and tech stacks, making them easy to adopt and use.

To learn more about how AI-powered solutions can push your underwriting to the next level, reach out to a member of our team today.

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