What Causes a False Rejection Rate in Customer Onboarding and What Can You Do About It?

05.31.2022

False rejections can generate real frustration during customer onboarding. Your false rejection rate is effectively the percentage of instances in which potential or existing customers are incorrectly rejected. According to Thomson Reuters, 89% of clients go through an onboarding that creates friction and frustration, and as a result, 13% choose to switch to a competitor. Additionally, the time spent collecting data and documents and engaging in regular monitoring adds a further layer of friction. It is worth noting that customers don’t appreciate having their requests or transactions blocked. They generally find being asked for additional supporting information — after they’ve been told the onboarding process is complete — to be unnecessarily invasive and a waste of time.

At the same time, Know Your Customer (KYC) and Anti-Money Laundering (AML) regulatory compliance is becoming more ubiquitous. According to Aaron Nicodemus at Compliance Week, “Global costs were estimated at $180.9 billion in 2019. The $213.9 billion figure in compliance spending in 2020 represents an 18 percent increase.”

The comprehensive report surveyed 1,015 financial institution compliance decision-makers globally, with these notable findings:

  • U.S. and Canadian spending on financial-crime compliance totaled $42 billion.
  • Financial crime compliance spending in the U.S. increased in 2020 by 33% year-over-year.
  • The top challenge in financial crime compliance was sanctions screening.

“Mid- to large-sized U.S. financial services providers were much more likely to see a dramatic spike in compliance costs partially because of the pandemic, respondents said. Some pandemic-driven costs stemmed from increased alert volumes and suspicious transactions, inefficiencies with alert resolution and due diligence, more manual work, and limitations with proper risk profiling/sanctions screening/PEP identification, the survey said.”

What Causes a False Rejection in Customer Onboarding?

Any number of things can trigger a false rejection. Some common causes of higher false-rejection rates include:

 

Information Overload

Requesting or giving too much information can be overwhelming to your customers. Asking too much during the customer onboarding process could lead to miscommunications and bad inputs, triggering a false positive.

Potential solution: Provide educational video solutions as an integral part of the KYC, AML, and overarching customer onboarding process. It’s effective, faster and more convenient for both customers and your team.

 

Weak or inadequate customer support

Customers are most likely to need help and assistance from you during the onboarding process. Not having sufficient customer support can lead to frustration and unnecessary errors.

Potential solution: Provide multiple channels of customer support to accommodate your future customers’ preferences, such as chat, text, phone, email, in-app support, video support, etc.

 

Manual processes

Any onboarding process requiring manual human interaction, like manual reviews, is a double-edged sword. While it is possible to generate a potentially deeper relationship due to in-person advantages, it is far slower and more prone to missed or rushed compliance steps.

Potential solution: Allow the onboarding process to be digital. Work with trusted partners to streamline and strengthen your processes. The net result will be a better customer experience and faster acquisition times. With Instnt, you can provide your customers with a frictionless experience, enabling you to quickly verify, accept, and onboard more new online customers without fraud loss or compliance issues.

 

What Causes a False Positive in Customer Onboarding?

The primary cause of false positives or higher false rejection rates is fundamentally over-screening. That said, the cost of noncompliance can be severe. According to Fintech Global, a total of $937.7 million in fines were issued for noncompliance with AML, KYC, and data-privacy regulations in the first half of 2021. North America issued the largest share of fines, totaling $716 million, with an average value of $29.8 million.

In order to comply with regulatory requirements, organizations will naturally opt to be more selective rather than relaxed with the screening process. In effect, potentially suspicious activity is made a broader and farther-reaching box for customers to fit into. Unfortunately, not every KYC and AM

 

L alert means that some kind of criminal activity is happening. This gray area then triggers a manual review for clearance by an officer or team member at the appropriate level. If the flag is eventually cleared, then it is by default a false positive.

According to Joseph Otting, the 31st comptroller of the currency (2017-2020), “Today our AML/BSA relies upon a lot of systems to kick out a lot of data that often has an enormous amount of false negatives associated with it that requires a lot of resources to go through that false negative, and I think if we can get to the point where we have better-fine-tuned data with artificial intelligence about tracking information is and the type of activities that are occurring, I think ultimately we’ll have better risk management practices within the institutions as well.”

 

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False Rejection Rate Solutions

For companies thinking to cover all the bases through one extended and thorough onboarding process, consider the following: Customers regularly abandon arduous and confusing applications. According to Signicat:

  • 12% of potential customers have abandoned after 5 minutes.
  • 40% of potential customers have abandoned after 10 minutes.
  • 70% of potential customers have abandoned after 20 minutes.
  • 86% of potential customers have abandoned after 30 minutes.
  • 93% of potential customers have abandoned after 60 minutes.

In order to stay competitive, your organization should use a robust identity verification system like Instnt Accept™ to sign up more good customers and lower your rejection rates. Instnt Accept™ uses geo-location, personally identifiable information (PII) validation and user behavior to onboard the right customers. Other features include:

  • Customizable neural networks to concentrate on compliance checks that you set.
  • PKI keys to encrypt your customer data.
  • One single line of code for faster deployment and maintenance.
  • Indemnification for up to $100MM in annual fraud losses.

Work with a proven partner like Instnt Accept™ with a fraud liability guarantee. Contact us today to try a demo!

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About the Author

Instnt's fraud loss indemnification technology provides coverage of up to $100M for fraud losses stemming from synthetic, third-party, and first-party fraud. With Instnt's comprehensive fraud loss protection, businesses can confidently extend their services to a wider customer base, enabling them to embrace more opportunities and enhance revenue streams while maintaining a secure, fraud-free environment.