2018: New Payday Rules, New Era for Savvy Lenders

January 17th, 2018

The roller coaster ride called Payday Lending promises some all new twists and turns in 2018 as the legislators and the courts try to sort out the new payday rules. When will the dust settle? Will the outcome leave the payday industry in crisis? Or create new opportunities for savvy lenders who understand how to leverage fintech resources to maximize operational efficiencies and portfolio yield?

CFPB in Disarray

It looked like new payday loan regulations were set in stone when the CFPB (Consumer Financial Protection Bureau) published their Final Rule on Payday, Vehicle Title and Installment Loans in the Federal Register on November 17, 2017. These restrictive new rules have an effective date of January 16, 2018, and a compliance date of August 19, 2018.

Hang on…not so fast.

This scrappy industry isn’t going down without a fight, and they’re supported by some strong allies in the US Congress. On November 30 a bipartisan group of lawmakers filed a joint resolution under the CRA (Congressional Review Act). This resolution states in part, “…Congress disapproves the rule submitted by the Bureau of Consumer Financial Protection…and such rule shall have no force or effect.”

The CRA filing triggers a lengthy new review process at a time when the Director’s seat at the CFPB looks more like a game of musical chairs than a position of power. The resulting regulatory limbo could delay any changes for the next several months, or maybe the next several years.

Let’s Get Back to the People

It’s easy to get bogged down in the complexities of Washington’s political machinations. So let’s stay focused on the people these regulations, and these loans, are both designed to serve.

The Pew Charitable Trusts has conducted extensive studies over the past few years on payday borrowers and how they use the funds. According to Pew research 12 million Americans use payday loans each year, and some use the service multiple times during the year. 5.5% of all adult Americans have used a payday loan at some time, and this number almost doubles to 9.0% when you look at the 25-29 age range. It’s interesting to note that the demand for mortgages in the US ranges from 9.0% to 18.2% depending on the state. So in some US states the demand for payday loans is equal to the demand for mortgages.

Pew describes the typical payday borrower as a single Caucasian female, age 25-44, who heads a household with 2 minor children. She likely has no college education, works at a minimum wage position, uses the funds to cover unexpected emergencies, and pays off the loan within the specified payment period. About 15% of payday borrowers use the funds to cover everyday living expenses. They’re likely to roll over the loan at the end of the payment period, or take out a new loan in a short amount of time. This frequent borrower pays an extremely high APR as they recycle the same $350 up to 7 times during the year.

Contrary to legislative opinion this consumer has weighed the pros-and-cons of the limited number of credit options available to them. And she has determined the payday loan is her best alternative when compared to a high overdraft fee if a check bounces, or a $500 deposit for a secured credit card. Plus the secured credit card will likely charge a monthly maintenance fee on top of an interest rate as high as 35%.

It’s no secret that legislators in the US are trying to limit the supply of payday loans by imposing onerous new policies on payday lenders. This approach will ultimately fail, because it doesn’t address the underlying cause of such high consumer demand for these loans. As long as the primary payday borrower is a single mother working to support two children on a minimum wage that’s just at or slightly below the poverty line, then the demand for small, short-term loans will remain high.

Payday Business Model Isn’t Simple

From the regulators’ perspective the situation looks simple. Payday lenders charge the most vulnerable sector of our society exorbitant fees and interest rates for small loans. So why can’t community banks like credit unions step in and offer the same loans with lower APRs?

Unfortunately, the business model isn’t as simple as it looks. According to the CFPB, the average payday loan is $350, and it’s paid off within a few weeks or a few months. The profit earned on an individual loan is very small, even though the interest plus fees when calculated as an APR looks extremely high. Payday lenders tell us their ROI is much lower than the APR. Dennis Shaul, the CEO of the CFSA (Community Financial Services Association of America) was quoted in a CNNMoney article saying, “We’re making about an average of 4% return on investment. We’re not making an obscene profit on the backs of people.”

The NCUA (National Credit Union Administration) approved a new type of loan in 2010 called a PAL (payday alternative loan). It allows their member banks to issue small loans ranging from $200 to $1,000 with terms ranging from 1 to 6 months. There’s a $20 limit on the application fee, and the loan cannot be rolled over at the end of the term. The APR can be as high as 28%, but borrowers can reduce their rate down to 18% by automating the payments via direct deposit.

In 2016 only 20% of credit unions offered PALs, because the stringent terms make it difficult for the typical credit union to breakeven on the transaction. The major problem is high operational costs due to legacy origination and payments processing systems that are overly manual.

Untapped Opportunity for Fintech Savvy Lenders

Fintech savvy lenders enjoy the unique ability to issue small, short-term loans with borrower-friendly pricing — and still make a solid profit.

The long-term demand for these loans will remain high. Regardless of whether the financial vehicle is a payday loan, title loan, or check cashing service. And regardless of whether the new payday rules take effect in 2018, 2019, or not at all.

We believe this ongoing demand represents an untapped opportunity to offer a payday loan alternative that’s socially conscious and still profitable.

There are several niche groups within the financial services industry that could capitalize on this opportunity, including: online lenders, crowdfunding platforms, micro lenders, small local banks, community banks and credit unions.

The key to profitability is booking a large number of accounts and managing them efficiently. So the successful lender will understand how to leverage fintech resources to create hyper-efficient processes for loan origination, funds transfer and payments processing.

Fintech lending platforms are tailor-made for small, short-term loans for two reasons. First, they use automation to gain operational efficiencies, which reduces costs. And second, the top fintech lending platforms use advanced credit scoring methodologies to improve credit decisions, which increases portfolio yield and profits.

When we look back on 2018 it will be interesting to see how many new lenders decided to capitalize on this large and lucrative loan category in spite of the new payday regulations.

Top 3 Challenges to Be Solved by Decision Automation Solutions in 2018

January 17th, 2018

Sun Tzu has said: Speed is the essence of war.

The ability to make wise decisions swiftly will place you well ahead of your competitors. With smart automation of the decision flow you will eclipse competitors.

Decisioning tools and processes range from excel spreadsheets and intuition to sophisticated enterprise solutions. But no one disputes anymore that speed and accuracy of today’s decisions determines tomorrow’s success.

To help you set up a robust decisioning framework we’ve identified the top three challenges to be addressed by decision automation solutions in the 2018.

Enhancing Business Decisions with Data from Non-traditional Sources

“In markets and market sectors that are still developing, the challenge is to incorporate non-traditional data sources into traditional models, to still leverage the analytical power of decision automation systems without imposing the same level of data rigidity that is standard in the developed markets.“ — says Brendan le Grange, Director: Research and Consulting at TransUnion.

We totally confirm the necessity of embedding alternative data sources into daily operations. We’d like to draw your particular attention to the importance of social media sentiment analysis. Sourcing and analyzing data from social media channels allows you to see the real-time picture of the operational environment while overcoming headaches of merging data from multiple influencers. For instance, you can use data on social media activity to uncover suspicious actions and detect fraudsters; to enhance customer pre-screening and cross-selling, and more.

It is very important to join insights gained through non-traditional data sources with your own analytical models. For example, you can boost customer retention efforts. Using metrics on social media authority of each client you can target your “Superstar” customers during your promotional campaigns and thus maximize the outcome of your promotions.

Presenting the Information in the Best Way

“Balancing accuracy which frequently requires advanced, black-box methods, and transparency, which requires methods to be understandable and explainable” is one of the strongest challenges to be solved by decision automation systems, according to Gregory Piatetsky, a founder of KDD (Knowledge Discovery and Data mining conferences) and the President of KDnuggets, which provides analytics and data mining consulting.

Decision automation systems need to instantly identify which data insights are expected by any given business role. This radically streamlines users’ access to large quantities of data, thus empowering businesses to resolve potential problems in real time or even before they arise.

Acting on Big Data in Real Time

Decision automation systems must follow through with the results of their analysis and actually transform them into profitable decisions. Today’s solutions learn to predict the best next action. Previously they have been operating on an if-then basis, and now artificial intelligence allows implementing a sophisticated self-learning mechanism.

An example of such advances is the inclusion of champion/challenger testing approach into a decisioning strategy. In this case, a decision automation application is supplied with different strategies, and selects the next best action based on how every strategy has performed in the past.

Magic Formula: Insights-Comprehension-Action

We’d like to encourage you to use decision automation applications in a way, which can be encapsulated into the Insights-Comprehension-Action formula:

  • Insights: use decision automation systems that are embracing advanced analytics on every stage of decisioning process, and that can enhance existing facts with data from non-traditional sources;
  • Comprehension: ensure that all the insights are presented in a transparent way, and that user interfaces are tailored according to their business roles;
  • Action: make sure that the system follows through the end of decisioning process and transforms the knowledge into actions. Take advantage of the self-learning capabilities of your system, instead of simply following rigid algorithms.

We hope that these recommendations will help you set up an efficient and robust decisioning process. Please comment and share your thoughts on top challenges to be addressed by decision automation systems in 2018. May all your decisions be fruitful, and may your New Year be filled with peace, joy and harmony!