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  • user 12:53 am on December 10, 2019 Permalink | Reply
    Tags: , , , , credit, , Ondot, ,   

    Ondot Brings Apple Card Functionality To Banks And Credit Unions 

    Every financial institution wants to be like , or more specifically Apple — “Created by Apple, Not a Bank,” as its slogan brushes off the role of Goldman Sachs.
    Financial Technology

     
  • user 12:53 pm on May 11, 2019 Permalink | Reply
    Tags: , , , credit, , , , ,   

    World Council Of Credit Unions Helps Develop Technology In Asia And Africa 

    The of new , like mobile banking, that credit unions need but cant afford to develop on their own.
    Financial Technology

     
  • user 3:35 am on September 8, 2018 Permalink | Reply
    Tags: , , , , credit, ,   

    Q2 2018: US credit card issuer snapshot 

    Each quarter, Paul Sammer, Manager in the Issuing offering, compiles key metrics on US consumer cards, tracking spend, receivables, loss rates and returns reported by the largest US .

    US consumers are showing an increased preference for credit cards.  Banks reported robust growth in purchase volume over the past quarter, along with solid growth in receivables and benign loss rates. Read more about the key themes and notable happenings below.

    Key themes

    • Banks reported favorable credit trends in the past quarter as purchase volume and receivables continued to grow, and loss rates remained benign.
    • Credit card purchase volume increased at a significant pace over the past year, led by Capital One, American Express and Chase.
    • Receivables also grew at a healthy rate, most notably at American Express, Capital One and Discover.
    • New products and product refreshes were prevalent in Q2. Many of these new products are offering high-value incentives to open/activate.
    • Investments in digital capabilities are evident across the industry with new all-digital products (e.g., Chase’s Finn), and full-service functionality in digital channels.
    • Bank of America and Chase reported notable declines in card originations in the past quarter (nearly 10 percent YoY).
    • Issuers pointed to rewards (and associated cost) as a basis of differentiation, but there was a general theme of rational competition in most respects.

    Notable happenings

    Transactions

    Citibank completed $ 1.5B acquisition of L.L. Bean credit card portfolio from Barclays; Synchrony and PayPal finalized transfer of $ 7.6B in receivables; Signet Jewelers closed last phase of credit outsourcing, selling its non-prime portfolio to CarVal Investors and Castlelake.

    New Partnerships

    Alliance Data and IKEA introduced new co-brand offering 5 percent rewards on IKEA purchases; American Express announced new partnership with Amazon to offer a small business co-brand credit card; Wells Fargo launched no-fee Wells Fargo Propel American Express card.

    Partnership Developments

    In July, Walmart announced its intent to partner with Capital One and end its Synchrony relationship; Citibank renewed its card partnership with Sears, paying $ 425 million up front in a highly customized structure; Alliance Data and Victoria’s Secret renewed their PLCC partnership.

    New Products/Features

    American Express launched its no-fee, 1.5 percent cash back Cash Magnet card; Citi and American Airlines introduced new no-fee AAdvantage MileUp card, offering 2 miles per dollar; Chase and Hyatt introduced $ 95 annual fee World of Hyatt Card; Chase and Marriott introduced $ 95 fee Marriott Rewards Premier Plus card; Chase and Southwest Airlines introduced $ 149 annual fee Southwest Airlines Priority Card; Synchrony and Belk will introduce a co-brand credit card.

    Mobile & Tech

    Chase announces a partnership with Tock, a high-end dining program.

    Stay tuned for next quarter’s report on US consumer credit card trends.

    Industry trends (based on non-retail card issuers in scorecard section)

    1 Total receivables for non-retail issuers at end of 2Q18. 2 Total purchase volume of non-retail issuers in 2Q18. 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 2Q17. 5 QoQ = Quarter-over-quarter change versus 1Q18. Note: Purchase Volume is reported volume for the quarter (it is not annualized or TTM)

    Scorecard—Q2 ($ in Billions)

    1 Chase no longer discloses an ROA measure directly attributable to Card Services. 2 Citigroup: Purchase volume includes cash advances. Citigroup data includes Citi-Branded Cards and Citi Retail Services. 3 Capital One: US 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 US consumer cards. 5 Discover: includes US domestic receivables and purchase volumes only. Restated: ROA reflective of Direct Banking segment (credit card represents ~80% of loans) and implied US Cards tax rate of ~22%. ROA denominator estimated from total loans ended figures. 6 American Express: Changed reporting method as of 2Q18. All figures except ROA are for US Consumer segment; Amex has stopped reporting net income attributable to US consumer segment. ROA is estimated based on US receivables comprising 88% of Global Consumer segment and 22% US effective tax rate. 7 US Bank: Net Income attributable to Payments Services totaled $ 361M as of 2Q18, compared to $ 282M in 2Q17; Payments Services includes revenue from consumer credit cards, as well as commercial revenue and other sources. 8 A/R and PV for Retail Card unit only. 9 Loss rates and ROA include all of SYF’s business lines (i.e., Retail Card, Payment Solutions, and CareCredit). Retail Card accounts for about 70% of total receivables. 10 Average Receivables.

     

     Paul Sammer, Manager, Payments

     

     

     

    The post Q2 2018: US credit card issuer snapshot appeared first on Accenture Banking Blog.

    Accenture Banking Blog

     
  • user 12:18 am on August 30, 2018 Permalink | Reply
    Tags: credit, , ,   

    3 Startups to Watch in Credit Scoring 

    The rise of alternative data has allowed fintechs to go beyond Fico scores to determine the financial risk of a borrower. With this data, some fintechs are looking to facilitate more loans to thin-file consumers. By using artificial intelligence (AI) and machine learning (ML), the can determine a borrowing candidate’s financial health and attitude towards [&;]
    Bank Innovation

     
  • user 12:18 am on August 28, 2018 Permalink | Reply
    Tags: , , credit, , , ,   

    3 Notable VC Rounds in Alternative Credit 

    funding this year has been on the rise. In the second quarter alone, funding for financial companies around the world reached $ 20.3 billion in nearly 400 deals. Right now, venture capital firms, , and investors are pouring funds into companies Artifical Intelligence, the clear flavor of the year. But AI means more than chatbots [&;]
    Bank Innovation

     
  • user 12:19 am on August 18, 2018 Permalink | Reply
    Tags: Agricole, , , credit, , , Staves   

    How Crédit Agricole Staves Off Competition From Fintechs 

    Bank Innovation has learned that Crédit , a €1.76 trillion ($ 2.01 trillion) bank headquartered in France, has achieved 70% digitization of its service offerings among its worldwide network of throughout Europe and North Africa. A spokesperson at the bank said the financial institution network hopes to achieve 100% digitization of its services by the [&;]
    Bank Innovation

     
  • user 12:18 pm on July 27, 2018 Permalink | Reply
    Tags: , credit, , , Navy, ,   

    Navy Federal Credit Union Mobile Usage on Par with Big Banks 

    For smaller FIs where “digital transformation” may still mean establishing a app, some are far ahead of their peers. Bank Innovation previously reported on the mobile app user numbers of the country’s biggest , and on average 44% of the top banks&; customers use their mobile app. On par with this metric is the [&;]
    Bank Innovation

     
  • user 3:35 am on July 25, 2018 Permalink | Reply
    Tags: , , , , credit, , imperative   

    The data imperative for credit cards 

    Over the past dozen years, numerous US regional have relaunched consumer card programs on a self-issued basis. At the outset, the growth component for many of these relaunch strategies relied heavily on branch channels, customer loyalty and the desire to consolidate banking relationships. In recent years, the banks’ credit card programs have been plateauing to low, single-digit growth rates without obvious incremental prospects for growth in accounts, spend and balances. Although credit card portfolio health and returns continue to be favorable, without the ability to demonstrate further stepwise growth potential, these programs are at risk of atrophy in key areas, such as attention from senior executives and ongoing investment in innovation.

    Often, the keys to reinvigorating growth include identifying and addressing root-cause growth inhibitors (which often relate to approval rates, credit line assignment and service experiences), and finding ways to digitize and integrate customers’ credit card experiences with those of their overall banking relationships. exhaust created by these card programs and other players in the payment value chain could hold a secret to vast amounts of information value to unlock growth opportunities.

    Card issuers and, in particular, the payments industry generally have been early adopters of data-driven insights to grow their business; and rightly so, since the industry generates a massive volume of data. Banks are increasingly recognizing and reaching the point at which they need to drive innovative applications of the insights in functions that traditionally do not leverage them fully or consistently—for example, for enhancing customer experience or devising new product strategies.

    In addition, as depicted in Figure 1, prospect and customer segmentation can be a key component of focusing growth strategy investments on areas of greatest opportunity. For instance, segmentation can help a bank determine areas for product refinement to both improve experiences for existing credit cardholders and tap into unserved or underserved markets. We also see segmentation as the prudent way for many banks to carefully venture outside of their existing retail banking customer bases through twinning analysis to identify characteristics their most profitable cardholder segments may share with non-relationship prospect pools.

    Figure 1. Actionable segmentation driving key customer/prospect insights
    Source: Accenture research and analysis

    Card issuers see only one dimension of customers. However, there is significant information asymmetry with other players in the value chain, namely, payment networks, merchant acquirers and merchants. Issuers capture data about and cardholder details only, while merchant acquirers see details on merchants and transactions, merchants collect data on their customers and purchase basket, and the payment networks record data on movement of funds between these players and authorization tokens. Building a cross-payment cycle data view allows creation of rich micro-segments for hyper-personalization (Figure 2). It also enables banks to conduct merchant, store and product-level marketing studies, generate early warning indicators for fraud and delinquency, and create visibility into customer and industry trends.

    Figure 2. Types of data captured and analyzed across different parties involved during the payments process
    Source: Accenture research and analysis

    Collection, cleaning and deciphering this data exhaust is an onerous task. However, advancements in artificial intelligence capabilities, like machine learning and Big Data, is making it easier and faster than ever before.

    Capabilities, such as Accenture’s Intelligent Enterprise Platform that sits on top of the Accenture Insights Platform allows banks to layer third-party data from social media, web browsing and geo-tagging over the payments data. This further deepens card issuers’ understanding by manifolds around customer needs and behavior. It’s opening previously unimagined use cases, like real-time mood-/persona-based recommendations, geo-tagging and location-based offers to customers.

    Looking forward, we anticipate that a cross-payment cycle data ecosystem together with machine learning will play a broader role in how banks generate new growth in accounts, spend and balances, as well as how they harvest value in their credit card programs.

    We invite you to read about data as the new ecosystem currency in our report, The New, New Normal: Exponential Growth

    Special thanks to Sanjay Ojha for his insights, as well as Rajat Mawkin and Uday Gupta, who also contributed to this blog. 

    The post The data imperative for credit cards appeared first on Accenture Banking Blog.

    Accenture Banking Blog

     
  • user 12:18 pm on July 21, 2018 Permalink | Reply
    Tags: Alliant, Allocates, , credit, , , , , Size, Twice,   

    Alliant Credit Union Allocates Nearly Twice as Much For Innovation as Banks of the Same Size 

    ’s budget allocation for is almost as high as the average bank of the . Most won’t readily share exactly what they spend on innovation, but Alliant Credit Union has offered up that 15% of their expense base is allocated to innovation. Although credit unions aren’t required to publicly [&;]
    Bank Innovation

     
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