Robust digital onboarding requires a layered stack of capabilities working together to rapidly onboard legitimate users while creating barriers for fraudsters. Given the complexity of identity verification and regulations around the world, a business can’t rely on any single technique to meet its onboarding objectives.
For example, a data source check might not adequately verify people in countries with thin data coverage, so businesses can add document verification as an extra layer. That layered approach adds a point of good friction, identifying fraudsters while letting legitimate actors through.
A layered stack of verification techniques can help businesses minimise the risk of fraudulent activities – such as account takeovers, identity theft, and fake accounts – and safeguard customers’ sensitive information. Ultimately, layered verification helps to filter out bad actors while ensuring fast, convenient onboarding for good actors.
A layered approach to digital onboarding involves multiple active and passive processes to filter out the good actors from the bad. A typical verification process will collect personally identifiable information (PII) – such as name, date of birth, and address – from individuals and articles of incorporation from businesses. Meanwhile, passive data is collected in the background to confirm critical network and device information, such as an IP address. Those components must work harmoniously to establish strong fraud prevention measures without compromising customer onboarding experiences.
Artificial intelligence and machine learning (AI/ML) are revolutionising identity verification, helping to optimise onboarding at a scale humans can’t. AI/ML can find patterns in vast amounts of data – such as PII, network information, and geospatial analysis – to establish accurate customer risk profiles.
For instance, during manual document verification, a person can look at a picture of a driver’s licence and try to figure out if it’s real or fake. People do a reasonably good job but probably won’t catch more sophisticated fake identity documents.
AI can play a dual role in identity verification by enhancing security and delivering a better user experience. Using AI/ML, companies can quickly identify high-risk users and prioritise them for additional verification while letting low-risk individuals through.
While some identity platforms have integrated AI/ML on an individual service level, the future of identity verification is even more promising as AI evolves to build hyper-targeted workflows tailored to each user. AI’s role in preventing fraud is becoming essential, enabling smooth customer experiences and streamlined onboarding.
Finding the right combination of verification methods can be a challenge for any organisation. Many companies use multiple vendors for individual verification services, which can limit oversight and control of the process and create inefficiencies. Identity verification isn’t static, and companies need solutions that can adapt to changing fraud risks, regulations, and business needs.
Those challenges are amplified for companies with global footprints. Each country has its own set of regulatory requirements, identity verification sources, and best practices. Using an identity platform with global reach and localised expertise is crucial to finding the right layered approach for each country.
Agile capabilities become essential to a smooth onboarding process. Those companies that can strike a balance between the friction required for effective verification and a smooth onboarding experience can gain a competitive edge.
In this changing economic environment, more companies are focusing on onboarding the right people. Organisations can get a sense of how much it costs to onboard the right customer by factoring in the amount spent filtering out the bad actors from the good. Everything is a leading indicator, so businesses need the right instruments to accurately measure those numbers.
Some helpful metrics include:
The number of active versus passive verification techniques used;
The number of bad actors who were stopped;
The amount spent on direct vendors, staff, development, and resources.
To achieve smooth, secure digital onboarding, companies should leverage an identity platform with the expertise, tools, and layered capabilities to optimise verification. Those platforms can also provide a vision for broader AI implementation to accelerate workflow optimisation.
By partnering with a global identity platform, businesses can ensure enhanced customer onboarding experiences, setting the stage for long-term success.
This editorial was initially published in the Financial Crime and Fraud Report 2023 which dives into the captivating world of fraud management, digital onboarding, and financial crime in the financial services industry. You can download your free copy here.
Michael has more than 20 years of experience in the strategic execution of product strategies, particularly for the business-to-business technology industry. At Trulioo, he oversees the launch of new digital identity verification solutions and services.
Trulioo is the identity platform global businesses turn to for growth, innovation, and compliance. The platform helps companies achieve regulatory compliance, reduce risk, and expand their businesses by enabling the verification of more than 5 billion people and 300 million businesses across 195 countries.
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