<\/p>\n
The past few weeks have been a roller coaster for consumers. Inflation is still a fact of life, tariffs have influenced what we buy, and from whom. Earnings season has been marked by a slew of companies pulling guidance, because things are so uncertain. But consumers are keeping a tenuous hold on their spending patterns.<\/p>\n
Webster made the comments as part of her interview with Bart Stankiewicz, managing director of asset-based credit at Fortress Investment Group. In many cases, Webster said, struggles to meet basic expenses are apparent, because there\u2019s a gap between what consumers take home in earnings and what they need to spend.<\/p>\n
\u201cAs these prices go up,\u201d Webster pointed out, with the insights gleaned from that study, \u201cthey are looking to credit to fill the gap.\u201d\u00a0<\/span><\/p>\n FinTech platforms such as peer-to-peer lender Prosper have helped fill that gap, extending personal loans and access to credit cards (via the Prosper Card) across digital channels to borrowers. At the moment, the pressures would seem to be massing for the consumer lending platform. As Stankiewicz said, of the overall lending landscape, \u201cexpect to see an uptick in delinquencies if the environment worsens and unemployment rates go up.\u201d<\/p>\n There may not be much relief on interest rates, observed Webster \u2014 as the Fed deigned not to cut rates at its most recent FOMC meeting. \u201cThey\u2019re trying to navigate and balance the often conflicting measures of the economy, employment, wages, and obviously, inflation.\u201d<\/p>\n Amid that mixed and uncertain environment, Fortress sees promise in the lending platform business model, having announced a pact late last month that it had entered a $500 million forward flow agreement, along with Edge Focus, to buy a portion of the unsecured loans originated across Prosper\u2019s platform.<\/p>\n There\u2019s a two-sided strategy at work, Stankiewicz said, where Fortress sees significant opportunity to realize positive returns on its investment, while the capital being deployed helps Prosper expand credit access to more borrowers.<\/p>\n Fortress, for its part, has found that the machine learning technologies used by Prosper have helped underwrite loans that should provide strong returns \u2014 even with loans that might have been extended during the pandemic, when FICO scores might have been inflated with stimulus funds and debt paydowns. Even if losses increased to the levels seen in 2022. \u201cLosses would have to go up beyond those levels,\u201d he told Webster, before base case returns were impacted.<\/p>\n That\u2019s because, as Stankiewicz said, the underwriting models move well beyond static FICO scores to take into account other credit held by the consumer. The loans themselves are personalized to the consumer, taking into account that person\u2019s unique financial profile. \u201cIf the tariff impacts are sustained,\u201d he said, \u201cProsper has the ability to tighten up underwriting to control future losses.\u201d<\/p>\n The risk\/reward, said Stankiewicz said, works both ways: If the loans perform better than expected, there are alignment structures in place where Prosper is able to share in additional upside. The data collected by Fortress and Edge Focus, viewed daily, will help fine-tune risk appetites and ensure that returns are within expected ranges.<\/p>\n Looking ahead, he said Fortress will continue to look for more opportunities in the lending space, adding that \u201cIf we see a forward flow opportunity that is attractive, appealing because we believe we have enough downside protection, we\u2019re \u2026 going to engage on those situations as well.\u201d<\/p>\n <\/p>","protected":false},"excerpt":{"rendered":" The past few weeks have been a roller coaster for consumers. Inflation is still a fact of life, tariffs have influenced what we buy, and from whom. Earnings season has been marked by a slew of companies pulling guidance, because things are so uncertain. But consumers are keeping a tenuous hold on their spending patterns. 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