INV #Fintech, the sister accelerator to this site, announced its #fifth class of startups today. The six companies were chosen from among a wide array of applications from across the globe. Here are the six companies comprising the new class of INV Fintech: Active.ai is a conversational AI tool for facilitating intelligent financial micro-conversations. They […]
Bank Innovation
Over the past few years, mobile #payments has become a service that customers expect from their #banks, FIs and e-commerce platforms. Most countries have their own idiosyncratic mobile payment platforms. In the US, we have PayPal-run P2P platform Venmo, and the bank-backed Zelle, among many others. If there is one overarching promise mobile payments makes, […]
Bank Innovation
#Zelle is not working on a point-of-sale payments #solution right now. “Zelle moved $ 25 billion last quarter,” said Norm Marraccini, vice president of product management and marketing, digital payments at FIS. “When are we going to see Zelle at the point-of-sale?” Marraccini pointed out that Venmo’s payment volume for that quarter was less than half […]
Bank Innovation
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.
#Fintech #startups have taken note of the vast opportunity in the SME #space, which has been underserved by #banks since the financial crisis. Add to this the growing number of freelancers and independent contractors, and the market becomes even more attractive. “Small businesses are extremely profitable banking customers,” Trevor Dryer, CEO of Mirador, an SME […]
Bank Innovation
INV #Fintech, the sister accelerator to #Bank Innovation, announced a partnership today with the Berlin-based #Open Bank #Project to provide #sandbox and development services to the startup and its 13 partner companies. The sandbox will #offer startups in the INV Fintech accelerator a secure digital space to access and incorporate bank data into their applications. […]
Bank Innovation
The #innovation lab is becoming a hallmark feature of any bank or other financial institution. But once in the lab, what determines whether a startup will make it past the proof-of-concept stage? “It’s all about those relationships and that trust,” Jason Mars, CEO of conversational AI company Clinc, told Bank Innovation. Clinc currently has 34 […]
Bank Innovation
A common scene in the African savanna is a small, yellow-billed oxpecker perching on the back of a zebra. They are collaborating for mutual benefit. The oxpecker feeds off ticks and parasites that live on the zebra’s skin and—when it senses danger—it flies up near the zebra’s head and sounds a distinct warning. The oxpecker gets a free ride and a constant source of food, while the zebra gets constant pest control and a head start on predators. Each benefits from the collaboration.
Nearly 80 percent of the senior banking executives interviewed for our recent Future Workforce Survey plan to use AI to automate tasks to a large or very large extent in the next three years.
In banking, we see a similar synergistic relationship emerging #between bank employees and artificial intelligence (AI). Our analysis¹ indicates that between 2018 and 2022, #banks that commit fully to AI and human-machine collaboration could boost their revenue by an average of 34 percent and, critically, increase employment levels by 14 percent. There are many things that #machines do very well and also things that #humans do very well, but we are increasingly recognizing that in many activities, man + machine is the most powerful combination.
We are also at the beginning of a material investment wave. Nearly 80 percent of the senior banking executives interviewed for our recent Future Workforce Survey plan to use AI to automate tasks to a large or very large extent in the next three years. Findings from our 2018 North America Banking Operations Survey show that 22 percent of banks are already using AI, machine learning, and natural language processing—and another 55 percent intend to do so within the next year.
Following industries like manufacturing, banks have already embraced the power of AI to automate processes and lower costs. Yet to win against digital startups and non-banks, incumbents will need to move beyond automation—applying in more nuanced ways AI’s ability to sense, communicate, interpret and learn within a broad enterprise structure that elevates human capabilities and unlocks new value. It’s what Accenture calls “applied intelligence,” combining #technology and human ingenuity across all parts of a bank’s core business to solve complex challenges, delight customers, break into new markets and generate entirely fresh revenue streams. Rather than working in isolation, humans and machines are going to be working together just like the oxpecker and the zebra to produce a combined effect greater than the sum of their separate outcomes.
While they see the potential, most banks have yet to take a disciplined enterprise-wide approach to AI. A significant barrier is banking executives’ anticipation of resistance from employees. Most cite a growing skills gap as the leading factor influencing their workforce strategy, and they believe that, on average, only 26 percent of their workforce is ready to work with intelligent technologies.
We think this pessimism is misplaced, and that they are in for a pleasant surprise. In part two of this topic, I’ll discuss what bank employees told us about their views on human-machine collaboration.
Until then, I invite you to read the entire report to learn more.
¹ Accenture econometric modeling, “Reworking the Revolution”, 2018, page 42
The post Identifying the synergies between humans &038; machines appeared first on Accenture Banking Blog.
SANTA CLARA, Calif. – New takes on #lending and underwriting dominated the opening day of demos at FinovateSpring 2018 here yesterday. But this being #fintech‘s leading demo showcase, the featured startups offered up these basic, fundamental aspects of banking in a new way, often with “artificial intelligence” under the hood. Six of the 28 demoing […]
Bank Innovation
SANTA CLARA, Calif. – Largely triggered by Google’s demo showing Google Assistant imitating human voice to book a hair appointment (see here; it’s pretty impressive), the chatter on Day 3 of FinovateSpring here was all about #conversational #banking. Many #banks are adopting conversational chatbots, but there is #still no equivalent of Amazon’s Alexa or Google’s Assistant […]
Bank Innovation
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