#Marcus, the #consumer #lending arm for #Goldman Sachs, wants to become the one-stop shop for many of your financial matters, except for one: #credit #cards — at least for now. “Our fundamental thinking on the credit card space is that there is a lot of innovation that is required. It is true that the industry has a […]
Bank Innovation
PREMIUM – #Facebook #built a bot called a “classifier” in order to identify #credit, housing, and employment ads, in order to exclude them from the social network’s “multicultural affinity” #targeting tools, but the bot #failed, and the result is that Facebook may have violated multiple federal laws concerning fair lending. This is according to new […]
Bank Innovation
PREMIUM – Millennials have Venmo, #banks have #Zelle, but what’s the P2P payments preference for #credit #unions? It’s not that credit unions cannot connect to the bank-backed (and bank-owned) payments system that is Zelle. In fact, credit unions like America First Credit Union and Mountain America Federal Credit Union are already connected to Zelle’s platform. […]
Bank Innovation
PREMIUM – Financial institutions and #fintech #startups have realized the potential in working with the enormous and previously untapped market of underbanked consumers. The means of assessing creditworthiness are as varied as the #alternative data points companies are starting to use. From psychometrics to gauge the propensity to pay back, to the #blockchain and geolocation […]
Bank Innovation
For years, as financial services became increasingly digital, #credit scoring remained stubbornly unchanged, but there are indications, #from the regulators on down to startups, that this is finally changing. From machine-learning-based underwriting to #blockchain-based identity solutions, new #technology is transforming the business of borrowing money. New companies in the credit-scoring space are using AI and […]
Bank Innovation
Many #banks have started using artificial intelligence to enhance customer service, whether through chatbots, customer acquisition or money management capabilities. However, when it comes to using AI in the backend of banking, those capabilities remains relatively unexplored, except for the most common use cases such as security, AML, KYC or fraud. One area where AI […]
Bank Innovation
#Banks today are facing stiff competition from innovative fintechs focusing on niches in the retail banking value chain. The advent of Open Banking will also facilitate the creation of new products and services that were previously impossible to imagine.
This creation of new products and services is blurring the gaps between banks’ traditional lines of business, such as payments and #credit. Fintechs and banks see the importance of linking credit and payments, self-evident for many years with credit cards, but which is an emerging theme in payments #innovation currently.
The millennials of today are uneasy carrying credit card balances, particularly as an aftermath of the struggle with debt during the financial crisis. They lend with more certain repayment terms, which helps them fund their big-ticket as well as smaller purchases while also consolidating their debts. #Point-of-#sale lending has emerged as a new category of lending to help such consumers finance new spending and to help merchants reduce basket abandonment. By partnering with merchants and embracing digital technologies, some disruptive fintechs are competing directly with credit cards and store cards to provide customers with quick and easy short-term credit at checkout.
One such disruptive #fintech in this space is Klarna, which provides a “buy now pay later” option at the checkout. When visiting a website powered by Klarna, shoppers need to simply input their email ID and shipping address, without the need to set up an account or type in credit card information. The maximum purchase limit is different on each account and is determined by a credit assessment by Klarna. For retailers, Klarna assumes all the financial risk of encouraging shoppers to close the deal without #payment. When the online retailer ships the product, Klarna pays the merchant directly, then sends a message to the consumer allowing 14 or 30 days to pay or return the item. Shoppers can also choose to pay on monthly installments with an interest component added. Behind the scenes, Klarna does checks that quickly determine if a shopper is a legitimate person and has good credit based on his or her email and shipping address.
Other companies in this space, like PayPal credit (formerly known as Bill me Later), have been steadily growing since 2008; PayPal credit offers a digital reusable line of credit to shop anywhere PayPal is accepted. Customers get up to six months to pay on purchases of $ 99 or more. Another player in this space is Affirm, which is also partnering with merchants to offer payment options, including financing as an alternative to credit cards.
Payments systems, like those offered by these players, are growing, are profitable and are encroaching more and more on traditional banking systems. The primary benefit of such a service is that removal of the payment step greatly reduces friction and shopping cart abandonment in the checkout process. The model proves to be a win-win for the customer and the retailer alike. The granting of a banking license to Klarna has enabled the fintech to move into ‘big bank’ territory and start offering its customers a larger range of financial services.
Banks such as Wells Fargo and Citigroup have been big players in point-of-sale loans historically—but these types of loans are now becoming increasingly popular. This is due to the advent of #technology that enables merchants to offer the option of a loan at the moment of purchase, where they may have previously only accepted cash or credit cards. Of late, consumer loan growth has become a top priority for banks to diversify their loan books, which historically have been over-burdened with commercial loan portfolios.
Some banks have taken the route of partnering with fintechs to have their share in the POS lending scene—e.g. banks like SunTrust, Regions Financial Corp, Fifth Third Bancorp, etc. have been offering their loans through GreenSky, a fintech which enables merchants selling furniture, home improvement and medical firms to provide POS credit to their customers. GreenSky provides loans—from $ 5,000 to $ 55,000—which are funded in minutes by any of the banks in their network.
POS lending provides the much-needed portfolio diversification which banks need in their books. Burgeoning fintechs in this space are claiming their share of these loans from customers—and banks need to ensure they have their own plans in place to either partner with them, or speed up their digital innovation processes to get their fair share of the POS lending market. With the advent of technology and regulations aimed at removing friction in the customer journey, the linkage between payments and credit are strengthening like never before, and banks need to have their strategies ready to retain their dominant foothold in this space.
The post Payment innovation extends the marketplace for credit at the point of sale appeared first on Accenture Banking Blog.
As purchase volume and receivables continued to rise during the recent quarter, several issuers reported material increases in returns resulting from tax reform. Read more about the key themes and notable happenings below.
Investment is ongoing in digital, mobile and self-service capabilities.
Transactions:
New Partnerships:
Partnership Developments:
New Products/Features:
Mobile & Tech:
1 Total receivables for non-retail issuers at end of 1Q18. 2 Total purchase volume of non-retail issuers in 1Q18. 3 After-Tax ROA excludes Wells Fargo, Chase, Bank of America and US Bank, which do not report credit specific income. 4 YoY = Year-over-year change versus 1Q18. 5 QoQ = Quarter-over-quarter change versus 4Q17. Note: Purchase Volume is reported volume for the quarter (it is not annualized or TTM)
1 Chase no longer discloses an ROA measure directly attributable to Card Services. 2 Citi: Purchase volume includes cash advances. Citigroup data includes Citi-Branded Cards and Citi Retail Services. 3 Capital One: U.S. card business, small business, installment loans only. Purchase volume excludes cash advances. 4 Bank of America: Receivables, purchase volume, and net loss rates are for U.S. consumer cards. 5 Discover: includes U.S. domestic receivables and purchase volumes only. Restated: ROA reflective of Direct Banking segment (credit card represents ~80% of loans) and implied U.S. Cards tax rate of ~22%. ROA denominator estimated from total loans ended figures.
6 American Express: Changed reporting method as of 1Q16. Figures are for U.S. Consumer segment only and exclude small business. 7 totaled $ 343M as of 1Q18, compared to $ 309M in 4Q17 8 A/R and PV for Retail Card unit only. 9 Loss rates and ROA include all of SYNCHRONY ’s business lines (i.e., Retail Card, Payment Solutions, and CareCredit). Retail Card accounts for about 70% of total receivables. 10 Average Receivables.
We are excited to share Q1 2018: Credit Card Issuer #Snapshot with you. Stay tuned for next quarter’s analysis.
The post Q1 2018: U.S. credit card issuer snapshot appeared first on Accenture Banking Blog.
Since the global financial crisis, #consumer #credit #cards have become a relatively stable and profitable asset class within US retail banking. However, with increasing movement across multiple, high-visibility areas of the credit card P&L from rates to rewards and charge-offs, issuers and their stakeholders are asking, “How are we performing?” and in a larger sense, “How should we be evaluating program performance?” An illustrative scan of publicly disclosed key performance indicators—such as interest yields on credit card loans, credit line utilization rates, and return on equity—provides topical insights into the complexities of a credit card portfolio, the risk of “mono-variabilitis” at portfolio levels, and the importance of evaluating performance holistically within the context of the customer portfolio, business strategy, and operational capabilities of different issuers.
At a cardholder level, most large and mid-sized credit card issuers assess higher annual percentage rates (APRs) for cardholders deemed to be more at risk for payment default, a concept generally known as risk-based pricing. As would be anticipated, empirical data from US FDIC call reports for the top 100 US financial institutions (FIs) with at least $ 10 million in credit card loans (Figure 1) depicts a correlation between (a) interest yield, which is the weighted average APRs on revolving balances divided by revolving and transacting balances, and (b) net charge-off rates on credit card loans.
What is interesting is the substantial statistical variance at the portfolio level that cannot be explained by just looking at rates and charge-offs, even when segmented by portfolio type. From our past experience with credit card portfolios, sources of this variance are wide-ranging and interlinked: from customer heterogeneity and different product types (the upper right of the dot plot of Figure 1, for example, that includes several card portfolios focused on the “building credit” consumer segment, such as secured cards) to variance in customer treatment and other portfolio management practices throughout the account lifecycle.
Reflecting the wider range of factors, just because an issuer is over- (under-) indexing the line, with higher (lower) yield at a particular charge-off level, does not necessarily mean the business is over- (under-) performing. Even for common and widely held relationships at the cardholder level, the portfolio picture is more complex and calls for knowledge of both the pieces and the interlinked relationships to ascertain the business meaning of relative industry performance.
Source: Accenture analysis of FDIC call report data for US commercial #banks, savings banks, and savings & loan associations with at least $ 10 million in consumer credit card balances as of year-end 2017. National Banks had $ 10+ billion in credit card receivables for the period; Super Regional Banks had $ 1 to $ 9.9 billion; Regional Banks had $ 100 to $ 999.9 million; and, Community Banks had $ 10 to $ 99.9 million. Specialist portfolios had (i) >$ 25M in credit card receivables per branch and fewer than 100 branches or (ii) yield greater than 30%. n=100.
The nuanced nature of portfolio management becomes even more apparent when credit line utilization is examined. Based on data from Figure 1, Accenture analyzed credit line utilization rates for a subset of 69 of in-scope FIs (excluding those portfolios with net charge-off rates in 2017 in excess of 5 percent and utilization outliers that imply a distinct product type). Credit line utilization was defined as credit card balances owed on transacting and revolving accounts divided by credit line commitments, inclusive of these balances, to extend credit to individuals for household, family and other personal expenditures through credit cards.
Figure 2 shows significant dispersion of line utilizations by FIs with virtually no direct statistically correlative relationship at the portfolio level between credit line utilization and net charge-off rate, even when segmented by portfolio type. At the cardholder level, one would anticipate credit line utilization to increase with net charge-off rates as FIs look to more closely manage credit lines for higher risk cardholders. And indeed, when customers are segmented within portfolio, we have observed portfolios to generally depict an inverse relationship between credit risk and line utilization.
Although operational practices—and the soundness of those practices—may not always be visible without knowledge of the particular internal factors, the variance at a portfolio level may also reflect a wide array of approaches to credit line setting and ongoing account management observed in-market. These range from FIs that have halted proactive credit line increases ever since the global financial crisis, to those that are becoming more progressive in setting and revising credit lines, including through automated means of obtaining ability-to-pay information and cardholder-level multivariate decisioning. Together with the difference in portfolio dynamics and operational treatment, these variations in overarching strategy can have meaningful implications for contextualizing and evaluating performance.
Source: Accenture analysis of FDIC call report data for US commercial banks, savings banks, and savings & loan associations with at least $ 10 million in consumer credit card balances as of year-end 2017, consumer credit line utilization rates ranging from 5% to 30%, and 2017 net charge-off rates on consumer credit card loans of up to 5%. National Banks had $ 10+ billion in credit card receivables for the period; Super Regional Banks had $ 1 to $ 9.9 billion; Regional Banks had $ 100 to $ 999.9 million; and, Community Banks had $ 10 to $ 99.9 million. Specialist portfolios had (i) >$ 25M in credit card receivables per branch and fewer than 100 branches or (ii) yield greater than 30%. n=69.
Reflecting the full suite of drivers, including those above, and how issuers manage them, return on equity (ROE) figures for credit cards are typically both higher and more variable than other bank assets. Credit card banks—defined as FIs with at least 50 percent of total assets in consumer credit cards and which account for roughly half of the consumer card market—have a five-year running average ROE over double that of the banking industry average of 8.64 percent for 2017, per the US FDIC Quarterly Banking Profile for Fourth Quarter 2017.
As alluded to above, return is not without risk. Although banks have been generally disciplined in requiring higher returns for riskier assets; the range of outcomes grows as charge-offs grow, magnified by leverage and real differences in strategies and operational capabilities. However, it is the combinations of these factors that not only make credit cards a challenging business, but also make them all the more rewarding over the long term for those banks that appreciate the variances in portfolio behavior and can manage the full suite of portfolio levers towards an overarching vision.
As a whole, the credit card industry is viewing today’s market as attractive for growth and providers are looking to outperform. With a healthy respect for the complexities of managing a card portfolio and appreciation of holistic interactions, leading FIs are clearly defining their business strategy, taking an integrated approach to portfolio management, and continually optimizing their business assets.
The future always has elements of terra incognita and more so in today’s market. Unified approaches, facilitated by communication among the necessary parties across the cardholder lifecycle, can help individual issuers deliver portfolio performance improvements in the context of their credit card business vision, mission, risk tolerance and market conditions.
For further reading, see how a major Brazilian financial services provider transformed its credit card processing and how a Latin American Bank used customer analytics to increase its credit card revenue.
The post The risk-returns roller coaster for US consumer credit cards appeared first on Accenture Banking Blog.
Elevates AI and machine learning make it possible to lend safely to subprime borrowers and help them build a #credit history. It lends directly or through #banks which are taking a new look at this market as regulators reduce restrictions.
Financial Technology
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