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When economy Strictly speaking, financial institutions face a number of interrelated challenges. Increases the temptation of bad behavior on customers. This creates additional regulatory oversight, with non-compliance subject to significant fines.
The desire to cut costs is driving continued investment in innovative financial products and services, while at the same time customers have higher expectations than ever for simple, efficient and great experiences.
On paper, this sounds like a name-dunk scenario for a burgeoning industry of new nimble fintech providers. No – unless those fintechs can learn some lessons about customer onboarding from established firms. Those lessons will ultimately trickle down to the marriage of process automation and the data fabric.
Why focus on boarding?
The onboarding experience is the customer’s first impression of the organization and sets the tone for the relationship. It is also the point at which the organization must determine exactly who the customer is and the true purpose of their business. Fast and accurate customer onboarding is always important, but in an economic downturn, it’s doubly so — as regulators crack down on risk in the financial sector, investors lose patience with startups that can’t deliver growth and margins quickly.
Effective onboarding is fintech’s Achilles heel. A data fabric that unifies data without moving it from systems of record is the answer.
Effective onboarding is fintech’s Achilles heel. See WISE, which was fined $360,000 by the Abu Dhabi regulator. Or the UK’s Financial Conduct Authority fines GT Bank £7.8m for AML failures. Or, Solaris, a German bank-as-a-service (BaaS) provider, has imposed a ban on future customers without government approval.
Failure of fintechs to properly manage the information and processes required for proper onboarding may account for most investment failures in 2022.
Data fabric and process automation improve onboarding
Onboarding begins with verified data, such as name, address, tax ID, details of the proposed business, where the money is coming from and where it is going. The problem is that financial institutions are large, complex organizations with countless IT systems and applications containing siled data sets. These legacy systems across different products, customer types and compliance programs do not integrate well.
That means there’s an incomplete view of the subject at hand, and trying to complete that view often means manually cutting and pasting between systems and spreadsheets. The possibility of human error alone should be enough to strike fear into the heart of any bank manager.
The data fabric—the technology that unifies all of an organization’s data—without moving from systems of record—is the answer. The data fabric creates a virtual data layer where dynamic enterprise data and the relationships between those data are managed in a simple, low-code environment. The data is protected at the row level, meaning only those who need to see it can see it, and only when they need to see it. The data may be on-premises, in a cloud service, or in multiple cloud environments.
With the Data Fabric approach, you can integrate business data in completely new ways. This means you can gain new insights from not only a 360-degree view of a customer, their identity, history, product(s), but also a holistic view of your organization’s data.
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