Point Predictive Launches ConsumerCheck, Providing Greater Insight into Prospective and Current Customers’ Identity, Income Employment, and Risk History
Point Predictive Inc., the San Diego-based company that provides artificial intelligence solutions to lenders, launched ConsumerCheck. This solution offers personal loan lenders, credit card issuers, buy-now-pay-later providers, and other financial institutions access to Point Predictive’s 19 billion consumer risk insights to reduce or eliminate onerous consumer information requests and make better-informed risk management decisions for current and prospective customers.
ConsumerCheck enables lenders and financial institutions to streamline the customer origination process and more deeply evaluate the risks associated with both new and existing customers. The solution complements existing credit risk management tools by providing additional, rich, consumer-specific data points that create a more holistic analysis of a borrower’s risk potential without inconveniencing customers and applicants. ConsumerCheck provides data that reduces or eliminates the need for requesting information on an application that causes consumers to abandon the application process. This is crucial as consumers demand shorter and simpler lending applications.
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ConsumerCheck extends exclusive, real-time access to the largest consortium of U.S. consumer risk data that houses 19 billion insights and covers more than 63 million U.S. consumers. The solution makes all of the information Point Predictive knows about a consumer’s income, employment, occupation, identity, and historic risk profile available to be used to improve the performance and predictive power of lenders’ risk management models and augment the customer data used to make profit-boosting portfolio management decisions.
“A complete view of the risks associated with credit applicants is imperative to a successful customer acquisition process, but lenders struggle with consumer demands to provide as little information as possible in an application,” said Tim Grace, CEO of Point Predictive. “Lenders need to augment what consumers are willing to provide with robust income, employment and identity data, and historical risk indicators to help them make the right risk determinations for extending credit. Avoiding costly and onerous requests for verification of income, employment/employer and other identity information typically needed to make informed decisions a thing of the past. With information now available from Point Predictive, making quick and consumer-friendly, yet better-informed risk decisions on current and new customers can prevent millions of dollars in losses.”
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ConsumerCheck can reduce the number of solutions lenders need to engage in the origination process and gather a more holistic view of risks associated with customers. Using a combination of a consumer’s name and address or telephone number, ConsumerCheck allows financial institutions to access up to 120 fields of data on identity, income, employment, loan collateral, and straw borrower risk. This unique feature set allows lenders to ask for fewer data fields in loan applications, improve customer experience, and reduce application abandonment rates.
The Point Predictive data consortium was purpose-built for risk management with more than 120 million historical applications, reported income for more than 61 million consumers, 17 million employer records with 8,200 fake employers, more than 400,000 social security numbers tied to default, 103 million social security numbers of deceased individuals, more than $7.2 billion in l**** with early payment defaults, $2 billion in l**** identified as fraudulent and millions of addresses and telephone numbers linked to risk of fraud or loan default.
With access to this unique data asset, financial institutions can feel more confident in their risk management decisions by seamlessly obtaining critical information; falsified employer history, multiple suspicious applications, or inflated income, ultimately reducing the lender’s risk of loan defaults and increasing approval rates for improved customer acquisition.
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