Over the last couple of weeks, Trust Science attended and exhibited at the 2018 CFSA Annual Conference and the 2018 AFSA Independents conference. It was a busy couple of weeks where we were able to talk to a number of lenders and learn about the issues driving the alternative lending industry. We were also excited to launch our new Early Adopter Program – more on that later.
While these two conferences serve slightly different audiences (CFSA largely represents single pay lenders while AFSA represents a broader audience including instalment installment and auto lenders), some common themes emerged on market demands and challenges. Here are some highlights:
Market Dynamics: Positive Indicators. Both conferences featured reports on the state of the consumer credit market. The good news is the credit environment continued to show positive trends since the crash of 2008/2009 with demand stable across the US. However, there is some evidence the installment loan market is taking share from the single pay market with 20-30% YoY growth and increasing movement to online channels. The movement to online channels is also evident in a decrease in store visits.
Technology: The Innovation Impact. At both conferences there was a lot of buzz around technology innovation and impacts across the business including increases in loan volumes and fees. While consumer demand was a driver, there was also attribution to innovation by lenders in terms of lead generation and customer acquisition, online customer experience and, importantly, improvements in technology and automation related to the use of data for marketing, underwriting and loan servicing.
CFPB: Friend not Foe. There was a lot of positive energy related to the changes at the CFPB and the refocusing of the agency’s mandate and attitudes towards regulating alternative lending. Both CFSA and AFSA are active in lobbying the CFPB and Congress when it comes to regulations guiding alternative lending. The combination of the efforts and a receptive GOP government are clearly bearing the fruits of their labor including the repeal on auto lending guidance as well as a delay on in the implementation of pay day lending restrictions.
In addition to getting up to speed on market and regulatory trends, we spent a lot of time talking to lenders about the future of credit scoring. Every lender we spoke to during both these events were challenged by how they could originate more new loans with new customers while balancing the reality of the risk associated with the thin/no-file nature of their borrower customers. Take Millennials for example. They are the largest generation in (surpassing the Baby Boomer generation) and they are coming of age and entering the credit markets. However, over two-thirds of Millennials are considered subprime under traditional scoring models.
In an effort to get a better picture of these borrowers, we talk about alternative data, a lot. Rental information, employment information, bill payment history, presence of car insurance and similar data points are now being incorporated into underwriting/scoring models to improve assessment of credit worthiness. However, our belief is alternative financial data suffers many of the same flaws as traditional data in credit scoring; historical/backward looking, prone to inaccuracy and are based on negative events (didn’t pay) versus positive events (paid every bill, every month).
Trust Science Early Adopter Program
There is a large source of rich, dynamic, real time data being missed by traditional (or even alternative) risk and scoring models: mobile and social data. Let’s go back to our large, Millennial market segment, for example. Almost 100% of this population owned smartphones and in 2017, Millennial internet users spent an average of 223 minutes per day on mobile devices. They live on mobile, and their digital footprint is a treasure chest of data. Combine that rich mobile and social data (acquired by consent) with traditional (where available) and alternative financial data and then, apply technology like artificial intelligence and machine learning to continuously improve models and scores. Now lenders have powerful tools to not only find new borrowers but better serve those borrowers at higher profits and lower risk.
This is why we were really excited to launch our new Early Adopter Program at these events. This program allows early access to Trust Science mobile technology designed to collect consent-based social and mobile data from which we deliver next generation of risk models based on complex (and patented) artificial intelligence and machine learning algorithms through our SIXSCORE ™ platform.
The Trust Science Early Adopter Program (EAP) is a unique opportunity for a select group of highly-qualified subprime lenders to help shape the future of credit scoring. Download more information here.
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