How to Implement Digital Onboarding in Online Lending

Lending services have many wolves – fraudsters – to contend with, regardless of whether they’re living in a brick-and-mortar bank or a house of digital straw.

Increasingly, companies from across the lending landscape are adopting a fully-digital customer experience. Of course, this process was traditionally completed inside a legacy bank’s actual premises. When onboarding new customers, banks could vet people applying for a loan in person, checking for solvency, the likelihood of default, and the possibility of financial crime.

Naturally, some of the safeguards that in-person loan applications provide lenders are not present in a purely digital environment. How can digital lenders onboard new applicants with safety, fraud prevention, and compliance in mind? SEON answers below.

Why Is Digital Onboarding a Challenge for Online Lending?

Digital lenders are faced with all of the safety, customer satisfaction, and compliance challenges that a legacy lender has, without the safeguard of assessing an applicant’s risk in person.

For online banks and neobanks, BNPLs, microlenders, mortgages, and P2P services, risk must still be considered in respect to smart business practices, despite the fact they only have digital risk assessment methods at their disposal.

Balancing risk mitigation with a welcoming customer experience is, thus, the primary hurdle for online lenders to jump.

In an increasingly competitive market, ResearchAndMarkets estimates the growth rate of the Global Digital Lending Platform Market to be 25.9%, with an estimated value of $44.5 Billion by 2030. The need to roll out the red carpet for new customers is obvious.

As more customers turn to lenders through the economic uncertainty of a recession, many will prefer options with less friction and certainly less of the red tape associated with legacy bank lending.

On the other side of the scale, the legal scrutiny that online lenders face means they have many kinds of risk they need to mitigate to maintain a healthy bottom line.

This includes the risk of fraudulent loan applicants essentially stealing money with synthetic identities or willfully defaulting on loans. This is why organizations should adhere to mandates for best practices in terms of consumer protection, data privacy, internal processes, cybersecurity, and AML regulations.

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Complying with KYC and AML Requirements

As with legacy industries regulated by financial authorities, online loan providers have to adhere to Know Your Customer (KYC) and anti-money laundering (AML) regulations. This is inclusive of peer-to-peer lending platforms, BNPL providers, payday and installment lenders, and digital credit unions.

KYC and AML mandates exist in most international jurisdictions and serve to fight the financing of organized crime, terrorism, and other entities deemed to be malicious.

These mandates are specific and stringent, and failure to comply with them can result in fines – the UK’s Financial Conduct Authority, for instance, issued over £200m in fines to non-compliant companies last year. For AML violators, global fines totaled over $5bn last year, with the most flagrant violations potentially landing their perpetrators on sanctions lists themselves.

Broadly, KYC and AML legislation requires online lenders to:

  • collect identifying information of customers and verify the validity of that information via official documentation
  • cross check verified names against all relevant sanctions lists
  • monitor customer transactions for signs of money laundering
  • maintain records of their customer transactions and report potentially suspicious transactions

For a more detailed look at both of these processes, you can read about it in our article on the difference between KYC and AML.

How Do You Implement Digital Onboarding in Online Lending?

Digital loan providers will inevitably find themselves building a deep software stack to handle the various challenges presented by the onboarding process without the security of in-person verification.

Such a stack will certainly include products that provide an efficient and low-friction customer experience, identity verification software (IDV), document and data management, fraud monitoring, AML checks, and customer relationship management. The market for each of these products is expansive, so when designing your stack, consider which of them provides solutions that most closely match your challenges.

Look for software that acts on the following facts:

  • IDV software is a crucial part of adhering to KYC mandates. Personal information submitted must be verified by software that can assess the validity of government-issued identification documents.
  • Document management software should provide a secure environment to store documents collected through the IDV process. It should organize these documents to provide a transparent audit trail in case regulators want to scrutinize a company to ensure customer due diligence (CDD) is being executed and for simple data hygiene. This archive must be highly secure as leaks of this particular database will inevitably result in sensitive personal information being released online. Customer safety regulators will close in soon after with punishing fines.
  • Fraud monitoring software with risk-based assessment should be implemented in several places during the onboarding process. It should be able to detect signs of synthetic identities by checking the personal information submitted for anomalies and risk indicators. Solutions like SEON can also help measure creditworthiness of loan applicants by leveraging alternative data sources that inspect the likelihood that an applicant is a genuine person, while also making a data-driven guess on their financial status.
  • AML checks are also a crucial part of a compliant onboarding process. Naturally, persons appearing on sanctions lists, PEP lists, crime lists, and other watchlists should be considered high risk and in some cases – depending on what is known about the individual – barred from proceeding any further. Some individuals named on PEP lists may represent a risk while not being malicious themselves, owing to the fact they present easy targets for account takeovers or blackmail. Their accounts should be monitored for signs of this.
  • Customer relationship management software will also be an essential part of an onboarding stack and throughout the customer lifecycle. CRM software should be able to organize customer onboarding data into a single profile and be the first point of contact for digital loan applicants. By introducing such a system at the onboarding stage, customers will be more accustomed to engaging with other automated communications, such as reminders of terms and payments, promotions, and general customer service queries. Valuable insights on your customer base should also be developed by CRM software to better provide an optimal customer journey.

Some of these solutions may do double or triple duty, covering multiple bases. Fraud prevention platforms like SEON, for example, can handle parts of the verification process, AML checks, and of course, fraud prevention – as well as some aspects of customer relationship management protocols, particularly data management and data insight generation.

Top 3 Custom Rules for Digital Onboarding in Online Lending

With the necessities above in mind, here are some rules that you can deploy in the SEON platform to shut down fraud and streamline the onboarding process.

#1: Multiple Applicants with Same IP or Device

To combat instances of fraudulent loan applications, fraud prevention software should be tuned to look for suspicious IP connections or device information.

Knowing that many credit agencies take up to 30 days to process credit scores and have those scores appear on user credit profiles, some fraudulent borrowers may hope to take out as many loans as possible inside this window with no intention of paying any of them back.

This may manifest as loan stacking, where a fraudster uses borrowed or stolen IDs to take out many loans quickly. Often, these fraudsters will connect to the lending domain on the same device from the same premises.

Below, we see how SEON can detect these anomalies.

referral fraud velocity rules

This screengrab shows a custom rule that has been implemented to see if multiple users have the same IP address in a day, which adds to their risk score. This rule has also been set up to raise the risk score if multiple account registrations have taken place with the same password hash, strongly suggesting that the users are the same person.

If this rule is adjusted to tip the risk scales from “APPROVED” to “REVIEW”, a member of the given fraud team can scrutinize the accumulated data and make the final call on which of the accounts, if any, should be trusted.

#2: Applicant Is from High-Risk Country

Fraudsters who have to submit personal information when onboarding to a loan provider will, generally speaking, be attempting to hide their true identities, including location. AML regulations stipulate that sanctioned persons should not be allowed to conduct business in applicable jurisdictions, and some regions are also classified as being generally high-risk.

In the screengrab above, we see that SEON has identified the connecting country as representing a high risk. This rule has added enough to the overall risk score that this user’s onboarding should certainly be escalated to the manual review stage, where a fraud team member can decide whether or not to accept this applicant.

#3: Applicant Has No Social Media Presence

When users submit their email address during the onboarding stage, lenders have to assess the validity of the user, which includes ascertaining whether they are a real person, and if so, whether this applicant is a good candidate to underwrite.

From the given email address, SEON can populate a list of various associated social media accounts. Nowadays especially, it’s unlikely that a trusted email address has no registrations whatsoever.

Depending on your business model as a lender, or the nuances of the region in which you operate, social media registrations could be used to check a user’s “human-ness” or even help develop a credit score.

Above, we see SEON’s social media widget, which shows that the queried user has none of the most common social media registrations. This is a check of 50+ sites, so the likelihood that a genuine user is registered to at least a couple is very high. Lacking any registrations, this user cannot have their alternative data scrutinized for potential creditworthiness. It may also be a dummy account set up by a fraudster to borrow money and never pay it back.

Note that, in the screenshot, particularly telling accounts like Amazon and Netflix have timed out (which is why they’re marked red), but these timeout thresholds can be adjusted within the SEON platform.

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How SEON Helps Online Lending with Digital Onboarding

SEON can be implemented alongside loan origination software to secure the onboarding process from marauding fraudsters. Criminals who approach your loan-providing company with stolen or synthetic IDs, multiple accounts, or even automated bots can be spotted by leveraging checks like device fingerprinting, digital footprint analysis (including social media checks), and password hashes.

Costs associated with KYC checks, including hardened KYC checks, can also be mitigated with SEON. The platform’s automated risk assessment can be tuned to help organizations monitor for certain customers that represent obvious potential fraud or are otherwise risky – and thereafter siphon them away from the expensive IDV process in favor of simply barring them.

All users within the online lending perimeter have to be directed towards KYC gateways, or even hardened KYC gateways that may require additional documentation like proof of income, background checks, or criminal records checks. These costs associated with these processes adds up quickly for any business, so being able to not waste the price on a clearly bad actor could help shore up ROI significantly.

SEON’s AML API also helps your review teams bring your loan provider into AML compliance, allowing you to check applicants against relevant sanctions lists.

Further down the road from the actual onboarding, SEON can retroactively secure that process by providing an audit trail of the customer’s loan applications. While doing so, SEON also develops insights on emerging patterns in your datasets.

These insights should then be used to inform your risk rules. For example, fraud analysts may use SEON to draw out usage patterns during the onboarding process that indicate signs of automation or particular recurring device setups. These could even indicate a ring of loan fraudsters.

For online lenders, the onboarding process is the most important part of the customer acquisition process, as it represents the point of underwriting assessment, as well as being the point at which fraudsters can be sniffed out. SEON helps secure the onboarding process and beyond, making sure your loan transactions can be efficient and informed, turning your house from straw to bricks, and securing it from even the biggest and baddest wolves.


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Author avatar
Jimmy Fong

Jimmy Fong is the Chief Commercial Officer of SEON. His expertise in payments saw him supervise the acquisitions of companies by Ingenico, Visa and American Express. Jimmy’s enthusiasm for transparent sales and Product-Led-Growth companies drives SEON’s global expansion strategy, and he interviews both fraud managers and darknet fraudsters in our podcast to stay on top of the latest risk trends. Yes, it’s also him wearing the bear suit on our YouTube channel.

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