<img height="1" width="1" src="https://www.facebook.com/tr?id=316029722675592&amp;ev=PageView &amp;noscript=1">

It’s a familiar story. You go online to apply for a loan or open an account with a financial institution only to encounter barrier after barrier:

We need a copy of your three most recent paystubs

Provide the address of the house you were residing at with your fraternity buddies ten years ago

Please make a copy of your birth certificate and fax it to…

Who still has a fax machine?

While this may be an exaggeration of the hoops that financial institutions make their prospective customers jump through, it reflects an unfortunate truth: too many organizations, both large and small, rely on outdated, archaic rules-based processes for digital identity verification.

Luckily that is starting to change. While consumers are demanding a more frictionless experience, machine learning and artificial intelligence technologies are enabling companies to approve more new customers more easily, while better detecting fraud.

The need for customer-facing brands to satisfy users and eliminate barriers to commerce often requires onboarding new applicants without ever having met them, but it doesn’t preclude the need to verify each customer’s identity. Businesses still must be certain beyond a reasonable doubt that the identities provided by their customers are legitimate.

For banks, independently acquiring data and developing in-house technologies for identity verification can be expensive and time-consuming. Moreover, organizations that do not have fully automated systems and still rely on manual reviews by human beings run the risk of alienating users to the point that they abandon the process completely.

This is where artificial intelligence (AI) and machine learning (ML) enter the picture. Using AI and ML allows institutions to draw on reliable databases and software programs, as well as numerous offline and online data points from social and institutional channels, to create a holistic model of customer identity in matter of milliseconds. It means a more seamless customer onboarding process, less fraud and virtually no manual reviews.

These new AI-driven solutions also get better over time. Because they continuously source live digital data and correlate thousands of data points from the online and offline worlds, they continually refine the process and build an ever more accurate picture of customer identity.

As these technologies make further inroads into the market, more and more financial institutions will be able to automate the entire identity verification lifecycle, from onboarding to the final decision, virtually eliminating the need for manual intervention, and producing outcomes that are far more accurate.

And you just might be able to stop searching for a fax machine.

Topics: Identity verification, Machine Learning

Peter Curtis

Peter Curtis

Peter is Senior Marketing Director at Socure with the focus on redefining identity verification in the financial space with superior data science. He is passionate about educating prospective customers on the positive impact of the Socure solution on auto-acceptance rates and fraud detection. He has handled marketing for companies over the years with an emphasis on driving strategy and execution.