Predictive analytics and your customer base

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Confidently Expand Your Customer Base with Predictive Analytics

In today's competitive environment, financial institutions (FIs) know they need to grow their customer base while keeping fraudsters out. Unfortunately, some FIs are hampering their growth opportunities because they are relying on legacy screening tools to drive their onboarding processes.

To explain how better data and better analytics could help FIs power their growth initiatives while mitigating risk, American Banker sat down with Robin Love, Vice President of Product Management at Early Warning Services, a financial technology company that delivers payment and risk solutions to financial institutions nationwide.

The onboarding process is the foundation for building solid customer relationships. How can data improve that process?

Robin Love: For FIs to confidently grow, they need onboarding tools that can identify synthetic and manipulated identities, as well as confidently and accurately estimate risk of true identities. This all needs to happen in real-time and without friction as the FI begins the relationship with the prospective customer. For this to be effective, new account onboarding must be data-driven and utilize predictive intelligence. For example, we are able to use bank-contributed data, including broad DDA transactions, along with account and history information, to provide FIs with insight and intelligence about millions of consumers.

The analytics generated from this collaborative database lets FIs confidently validate a consumer is who they say they are, predict likelihood of first-party fraud and account default, all while reducing fraud losses. At the same time, this data can enhance an institution’s Customer Identification Program (CIP) and Know Your Customer (KYC) initiatives, helping to ensure compliance with federal regulations.

How do these tools work?

Love: Using a unique cross-institution data set, combined with sophisticated analytics, we have developed a set of predictive scores to provide intelligence that enables FIs to improve new account opening decisions. By coupling data from the banks with predictive models, we can provide deeper intelligence that goes beyond a binary “match” or “no match” response against a negative database to confidently determine the individual’s identity and risk of account default or fraud.

Early Warning’s Real-time Identity Chek® Service – New Account Scores is comprised of three separate scoring models. The ID Confidence Score indicates the likelihood that a consumer is presenting valid identity credentials in real-time, before the application is approved. Our First-party Fraud Score provides predictive, data-driven insight into the potential for the applicant to commit first-party fraud within the first nine months of opening the account. The Account Default Score predicts the likelihood that a consumer will default due to account mismanagement in the first nine months.

Armed with this information, institutions can better distinguish between authentic and suspicious identities. Plus, this data will help the institution to work with the consumer to select the appropriate account types and privileges. That transparency helps FIs confidently expand their customer base, improving account opening decisions, while reducing risk.

What’s the difference between using these scores and more traditional, legacy onboarding processes?

Love: Legacy onboarding solutions have traditionally focused on Know Your Customer (KYC) initiatives to verify the identity of an applicant and to assess their potential risk threshold. As fraud and regulatory requirements evolve, it is important that your onboarding solution relies on current, accurate and complete data. It is no longer enough to rely on a single piece of data such as a credit score or a piece of negative data to screen potential customers.

Using collaborative intelligence instead, an FI can get a more holistic view of what kind of customer that person will be in the future by also looking at both positive and negative attributes and consumer banking behaviors. Not only can our solutions help solve for KYC, but our broad intelligence can help you validate your customer as well as determine risk and account privileges. Taking all of this data into consideration, you can now provide an account to someone that you may have rejected in the past. Better data translates into customers who are more aligned with the appropriate privileges and services and helps support financial inclusion with more traditional banking options.

How can data and analytics help FIs manage risk in digital channels?

Love: As FIs focus on growing their customer base, they have to consider increasing demand for access to account opening in the digital channel. In order to mitigate the risk with these faceless transactions, it’s imperative to use behind-the-scenes tools to prevent fraud and thoroughly authenticate both the customer and the device they are transacting with, while minimizing friction wherever possible. The use of predictive analytics and data can also help the FI to be able to grow their customer base while accurately assessing risk, both from an identity and behavioral perspective. Additionally, it’s also important to have solutions that can verify the risk associated with the opening deposit, whether in the branch with a teller or through mobile capture, which can also be linked to new account fraud.

How can these tools help improve the customer experience?

Love: Today’s customers demand a fast, efficient and frictionless interaction with their FIs at every touchpoint, whether they are online, using a call center or coming into a branch. They also want to know that their money—and their identities—are safe. Data can provide the real-time insight FIs need to optimize new account openings and tailor account offerings to each customer’s needs, ensuring a consistent customer experience across all platforms.

For more information on mitigating new account fraud, click here to watch a webinar.

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