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  • @fintechna 3:35 am on May 26, 2018 Permalink | Reply
    Tags: 7e00ff, Automating, , , , , , operations, , wide   

    Automating bank operations? Keep eyes wide open 

    Customer experience is the grand basis of competition in today’s business world. Unfortunately, most financial services institutions remain mired in manual, bespoke, paper-based processes—often siloed by customer, channel and product groups within a . That is beginning to change.

    RPA can reduce time to perform tasks by up to 90% and lower costs by up to 80%

    Automating bank operations? Keep eyes wide open fintech
    Read the report

    A key theme from Accenture’s recent survey of 80 bank COOs in North America is the need for back-office to become more digital and to act as the new front office. The survey report highlights several opportunities for to improve their operations—such as re-skilling back-office workers, creating agility through digital decoupling and robotics process automation (RPA). Sixteen percent of bank COOs we polled are using RPA, while 63 percent plan to use it over the next year or are piloting the . Half of those surveyed are looking towards straight-through processing and almost 75 percent have or plan to use analytics and data automation to truly unlock latent value in operations data.

    This presents a unique opportunity for banks to accelerate the use of modern automation techniques given their fundamental ability to enhance the customer and employee experience.

    Why is automation so important for banks?

    Intelligent automation has the power to impact operations. Here are five key reasons why:

    1. Simplifies work routines. Not all work is created equal and in many banks simple work is intermingled with complex work. This can create issues such as process bottlenecks, complicated workflows and slow customer service. Separating the simple from the complex can go a long way in making bank interactions better for customers and employees.
    2. Reduces process re-work. Enabling repeatability, enhanced predictability and streamlining the process helps a bank reduce hand-offs. Couple this with synergies of combined human-AI skills to run the process as a highly efficient factory and the benefits grow exponentially.
    3. Improves work quality. Automation aims to reduce errors by eliminating human touchpoints and judgment for routine activities across the banking value chain.
    4. Enhances efficiencies. RPA can free up resource capacity to focus on higher value activities.
    5. Speeds up innovation and time to market. Increased throughput, lower re-work and fewer errors all result in quick turnarounds.

    Banks should start their automation journey with the goal to look beyond cost savings. Five keys for success:

    1. It’s not a one-size-fits-all. Organizational processes can be repetitive or event-based with different types of data exchange. Assessment of process types and data is required to plan and using RPA or intelligent automation will actually simplify targeted processes to enhance efficiencies.
    2. Cost is only one piece of the puzzle. Automate because you want to create an innovative employee experience by focusing your people on the right activities, thus reducing errors and eliminating re-work. And improve the customer experience and speed to market. Efficiency will be a collateral advantage, but it should not be the going-in driver.
    3. Draw on operational data to drive front-office behavior. Operations is a treasure trove of data—from complaints and service/product issues to customer life events. Data automation with advanced analytics can extract valuable insights that banks can use to delight customers by anticipating their needs based on past transactions.
    4. Think big but start small. Circumvent the product-versus-customer-versus-channel debate by selecting a starting area and get going. Deliver in sprints, build momentum and stay the course.
    5. Agility is a mindset. Work through sprints without over-studying the current state, and then reimagine how the future could work in the context of an automated process.

    The power of RPA to invigorate bank operations is real—reducing time to perform tasks by up to 90 percent and lowering costs by up to 80 percent, by Accenture estimations. Before jumping on the bandwagon, however, business and IT must join together to strategically plan an optimal journey to an agile bank future.

    Read our 2018 North America Banking Operations Survey for more insights.

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  • @fintechna 3:35 pm on May 21, 2018 Permalink | Reply
    Tags: 7e00ff, , , , , coordination, , Meeting,   

    Meeting banking risk management coordination challenges 

    Accenture’s Global Risk Management Study highlights ongoing integration and that face teams. In our study’s first year (2009), only 15 percent of respondents reported having an integrated IT risk infrastructure. Over the years, that gap has closed only incrementally. This year, 67 percent of respondents report roadblocks resulting from a lack of integration across the enterprise.

    To centralize or not?

    New this year, though, is how our banking respondents view centralization. We first examined centralization trends in risk management coordination by risk type (market, credit and liquidity risks), and the results are somewhat contradictory. The 16 percent who are currently fully centralized expect to see an increase in coordination to 24 percent. Even the 20 percent of respondents who are fully decentralized, operating at mostly regional levels, expect more centralization in two years’ time.

    However, the majority of respondents that currently operate both a group and regional level believe the trend is toward decentralization. Forty-three percent of this cohort believe that coordination by risk type will actually decrease by nearly 10 percentage points overall in the coming two years.

    Interestingly, we see the same pattern of results in our examination of the coordination of risk management across lines of business. Those fully centralized across lines of business expect an increase of 10 percentage points in two years’ time and similarly those fully decentralized expect almost a halving of their full decentralization rate. Similarly, the majority of respondents fall in the hybrid model of centralization and believe that only 25 percent of risk functions will be coordinated across the business in two years&; time.

    Lastly, we looked at coordination of risk management activities across the overall business and found a lack of strong sentiment regarding coordination one way/another.  While 40 percent of respondents felt there was limited coordination between local- and group-level risk management functions, nearly 30 percent felt that this was neither true or untrue.

    Where do these seeming contradictions lead us? We see the role of risk manager becoming more integrated with the business and thus, demand has been put on the risk function to respond to both global and local needs. One intensive local need to highlight from our study findings is regulations; 78 percent of study respondents cite they are facing increasing demands in this area.

    Being an integrator of risk is a challenging role, not only in terms of serving global and local needs but also in terms of cost.  Over 50 percent of respondents reported duplication of risk management efforts across lines of business.

    An ongoing gap

    While ’ risk functions have had steady success since 2009 in coordinating with the business, a lack of integration with other business functions has always been a gap cited for improvement. We see an upward trend in improvement. In 2015, 7 percent of respondents said the risk and finance function worked closely together and provided joint input into enterprise risk strategy. That number more than doubled, to 16 percent, in this year’s study. And in two years, 30 percent of respondents expect that level of coordination between risk and finance.

    The other good news is the steady growth in influence among our survey respondents. Risk leaders have evolved from leading a very siloed function in 2009 to gaining a direct line to the CEO by 2013, and even a seat “at the table” in 2015. That positive trend is tempered by the challenge to integrate finance and risk. Only 38 percent of respondents say the finance and risk functions are working together—but they are not working together to help guide enterprise strategy.

    So, will risk leaders in banks take their seat at the leadership table to drive further integration? Time will tell, but we believe that working with common data sets and flows can be a powerful lever in addressing coordination challenges cost-effectively.

    We expect risk leaders to raise their game and be talented in many disciplines in order to rise to the integration challenge. In my next post, we’ll explore talent needs.

    How can risk managers balance both coordination and cost management? We believe sharing data is the key. Integration can be driven with increasing efficiency when data is at the core of the bank’s operating model. To effectively and efficiently share and use data means being a smart technologist, employing new technologies and a coordinated approach across the business.

     

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  • @fintechna 3:35 am on May 20, 2018 Permalink | Reply
    Tags: 7e00ff, , , , eager, ,   

    Bank employees are eager to collaborate with machines 

    Ancient Greek playwright Aeschylus wrote that “When one is willing and , the Gods join in.” In my first post of this series, I pointed out that executives believe their are resistant to AI and that, on average, only 26 percent of their workforce is ready to work with intelligent technologies. We think that pessimism is misplaced, as our survey of bank employees indicate that they are more willing and eager to work with AI than their bosses believe.

    need to seize this opportunity and leverage their employees’ enthusiasm for AI.

    Bank employees are eager to collaborate with machines fintech

    Of the more than 1,300 bank employees from large organizations who participated in our Future Workforce Survey, 40 percent are very confident in their abilities to work with intelligent technologies (vs. 33 percent cross-industry). Just over two-thirds said they believe AI will create opportunities in their work, while 72 percent expect it to make their jobs simpler. The majority foresee improved career prospects, while two out of three think AI will improve their work-life balance. Despite this optimism, they know these benefits won’t accrue automatically and 75 percent say it’s “important” or “very important” that they develop their skills to be able to work with AI over the next three to five years.

    Our research identifies three primary ways in which will enable people to work more effectively:

    1. Machines will amplify the capabilities, effort, and impact of humans by allowing them to be smarter and more productive. For example, the combination of customer service chatbots plus live customer service representatives (CSRs) intervening where needed, will allow each employee to greatly increase their impact, both within the organization and with customers and partners.
    2. Machines will give humans the ability to interact with powerful databases and computing engines in unprecedented ways. Humans will be able to leverage insights that will enable meaningful personalization and support better decisions in areas like credit risk management or fraud detection.
    3. Machines will help bank employees better embody everything that the bank stands for. By converting principles, policies and processes into consistent human practices, interactions and experiences, machines will help the bank’s people understand what to do, when, and in which way. More than that, they will bring the vision of the bank to life in the form of a multitude of everyday actions.

    Banks need to seize this opportunity and leverage their employees’ enthusiasm for AI. Their people are not only impatient to thrive in an intelligent enterprise that can disrupt markets and improve their working experience; they are also eager to acquire the new skills required to make this happen. Yet, somewhat surprisingly, only three percent of bank executives said their organization plans to significantly increase its investment in training programs in the next three years. This low level of commitment, at a time when a new era of work is imminent, will radically curtail their ability to deploy and benefit from AI at scale. This is the primary disconnect at the heart of our survey findings and a wake-up call for bank executives.

    Banks fully capitalizing on human-machine collaboration depends on their ability to fundamentally reimagine work. It means redesigning jobs as people move to project-based work. It means refreshing traditional job descriptions and thinking more about the tasks and the interactions between humans and machines in executing those tasks, rather than traditional job descriptions. It also means ensuring that almost all bank employees are conversant with new IT skills and can master new tasks. The employees are willing and eager, so the c-suite gods of the banking industry must now join in to give them the help they need to thrive in the world of the intelligent enterprise.

    I invite you to read the complete survey.

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  • @fintechna 3:35 pm on May 18, 2018 Permalink | Reply
    Tags: , , 7e00ff, , , , , ,   

    Q1 2018: U.S. credit card issuer snapshot 

    Guest blogger Paul Sammer reviews U.S. consumer use of cards to pay for transactions, fund loans, and receivables and transaction volume in Q1 .

     

    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.

    Key themes

    • Purchase volume in Q1 2018 continued to increase at a significant pace year-over-year, along with strong growth in receivables.
    • Chase, Capital One, Bank of America, and American Express reported robust purchase volume growth year-over-year, while American Express, Discover and Capital One led in terms of receivables growth.
    • cited increased consumer confidence and tax reform as drivers of strong purchase volume.
    • Loss rates continued to normalize although several banks suggested that losses may be stabilizing.
    • ROAs were bolstered by tax reform, which had a substantial impact on reported returns.

    Investment is ongoing in digital, mobile and self-service capabilities.

    Notable Happenings

    Transactions:

    • American Express and Citi complete sale of Citi’s $ 1.2 billion Hilton portfolio to American Express.

    New Partnerships:

    • Starbucks launches a new with Chase; Synchrony announces partnership with Crate and Barrel to offer a new private label credit card and co-brand card; Alliance Data and Lucky Brand agree to introduce a new private label credit card; Synchrony becomes preferred financing partner for Mahindra Powersports.

    Partnership Developments:

    • Due to retail partner bankruptcies, Synchrony replaces qualifying Toys “R” Us credit card accounts with a 2 percent cash back Mastercard and Alliance Data closes Bon-Ton accounts; Synchrony announces that it plans to onboard the PayPal Credit portfolio in 3Q18.

    New Products/Features:

    • Amazon introduces 5 percent back at Whole Foods on Amazon Prime Rewards Visa card; Chase announces new ultra-premium Marriott Rewards Premier Plus card and Amex announces new ultra-premium SPG Amex Luxury card (with single loyalty program branding coming in 2019).

    Mobile & Tech:

    • Synchrony invests in Payfone, provider of identity authentication in digital channels; Goldman Sachs acquires credit card startup Final.

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

    Q1 2018: U.S. credit card issuer snapshot fintech1 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)

    Scorecard—Q1 2018 ($ in Billions)

    Q1 2018: U.S. credit card issuer snapshot fintech
    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 with you. Stay tuned for next quarter’s analysis.

     

    Q1 2018: U.S. credit card issuer snapshot fintech

    Paul Sammer, Manager

    Q1 2018: U.S. credit card issuer snapshot fintechQ1 2018: U.S. credit card issuer snapshot fintech

     

     

     

     

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  • @fintechna 3:35 am on May 14, 2018 Permalink | Reply
    Tags: 7e00ff, 808080, , , coaster, , , , riskreturns, roller   

    The risk-returns roller coaster for US consumer credit cards 

    Since the global financial crisis, 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.

    Interest Yields

    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.

    Figure 1:  Interest Yield vs. Net Charge-Offs on Credit Cards

    The risk-returns roller coaster for US consumer credit cards fintech

    Source: Accenture analysis of FDIC call report data for US commercial , 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.

    Credit Line Utilization

    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.

    Figure 2:  Credit Line Utilization vs. Net Charge-Offs on Credit Cards

    The risk-returns roller coaster for US consumer credit cards fintech

    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.

    Return on Equity

    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.

    Implications

    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.

     

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  • @fintechna 3:35 pm on May 12, 2018 Permalink | Reply
    Tags: 7e00ff, , , , , , synergies,   

    Identifying the synergies between humans & machines 

    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 bank employees and artificial intelligence (AI). Our analysis¹ indicates that between 2018 and 2022, 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 do very well and also things that do very well, but we are increasingly recognizing that in many activities, man + machine is the most powerful combination.

    Identifying the synergies between humans & machines fintech
    Read the report

    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 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.

    Our research points to three key actions banks can take to transform their workforce, an essential step in creating positive synergy between their human and machine workers:

    1. Reimagine work to better understand how machines and people can collaborate.
    2. Pivot the workforce to areas that create new forms of value.
    3. Ramp up “new skilling” to enable people to work with intelligent machines.

    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

     

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  • @fintechna 3:35 am on May 11, 2018 Permalink | Reply
    Tags: 7e00ff, , , , purchasing, Supplier   

    Supplier acceptance of purchasing cards grows 

    Enhancing of card payments continues to be an important lever for growth and expansion of distributed plastic (“P-Cards”) and virtual card programs (“ePayables”). New findings from the recent NAPCP and Accenture Supplier Acceptance of P-Card and ePayables Payments Survey highlight industry progress in this area since our 2013 and 2009 survey findings.

    In summary, supplier acceptance continues to show signs of improvement:  

    • Supplier acceptance of P-Cards across most supplier spend categories has increased (Figure 1)
    • ePayables acceptance by suppliers has crossed the 50 percent milestone
    • Card acceptance has become more integral to supplier selection by corporate buyers
    • Suppliers are increasingly recognizing the benefits of faster payment/cash flow
    • Maximum allowable P-Card transaction sizes have risen
    • Educating suppliers continues to correlate with better program performance
     Figure 1:  Supplier Acceptance of P-Cards by Spend Category

    Supplier acceptance of purchasing cards grows fintech

    Source: NAPCP and Accenture

    Suppliers have many reasons to take cards and are increasingly handling card acceptance in a more automated manner. Figure 2 documents several key reasons why suppliers accept cards for B2B payments.

    Figure 2:  Reasons Suppliers Take Card Payments, According to End-Users

    Supplier acceptance of purchasing cards grows fintech

    Source: NAPCP and Accenture

    Looking forward, corporates and their P-Card and ePayables providers should continue working more closely with their suppliers to increase their knowledge of lower acceptance costs available through passing Level 3 line item detail transaction data. Qualifying for larger transaction size rates and assisting suppliers in automating the receipt and reconciliation of payment instructions and remittance data is also necessary.

    I invite you to read the full report to find out more about the link between acceptance and payments growth.

    For more information on the NAPCP, visit http://www.napcp.org.

     

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  • @fintechna 3:35 am on May 8, 2018 Permalink | Reply
    Tags: 7e00ff, , , brief, , , ,   

    A (brief) moment of opportunity for banks 

    The chaos related to data privacy concerns and the use of customer data has had a major, negative impact on the valuation of the so-called FAANG (Facebook, Amazon, Apple, Netflix, Google) companies, reducing their market capitalization by a range of five to 15 percent in just a few weeks and raising questions about the sustainability of the business models of these companies going forward. Chinese Internet giants such as Alibaba, Tencent and Baidu have also been affected.

    As the investing community sorts through the news and assesses the prospects for FAANG and other tech companies, European have an to reposition themselves as trustworthy, technologically sophisticated companies with opportunities for growth after a lengthy period of reorganization and, in some cases, downsizing.

    In the bad news for FAANG, there are some potential positives for banks, including:

    • The likelihood of new regulations on FAANG and other tech companies. New regulations could impose additional costs and put obstacles in the way of non-traditional competitors—particularly those that obtain and handle large quantities of customer data—that are seeking an easy path into the banking business. The required recent investments in GDPR at the European level thus potentially provides banks with a new competitive advantage.
    • Even greater emphasis on customer privacy and the protection of customer data. This is something banks have, in general, handled reasonably well—both in terms of data security and client privacy. With new safeguards and more concentration on cybersecurity, banks can position themselves as a more reliable alternative to online providers of financial services.
    • Better access to talent. Top people (as well as top operations and finance people) may look at alternatives to working for tech giants facing headline, reputational and regulatory risks. 

    While looking at these positive elements, we also need to look closely at the ecosystem for signs of stress in the wake of FAANG developments. So far, however, fintechs’ ability to raise venture capital and attract early stage investors seems undiminished.

    Similarly, the gap between the valuation of banks vs. digital players has hardly diminished over the past weeks, with FAANG price-to-book valuations still at 10 times those for banks. The differential reflects contrasting expectations of the group&;s growth potential, with future value reflecting more than 50 percent of the enterprise value of FAANG throughout 2017, vs. only 16 percent of the enterprise value for leading banks, and about -7 percent for the non-leading banks.

    Despite the efforts of some banks to be perceived (and valued) as technology players, they have not received tech-type market valuations. The current crisis of trust associated with some FAANGs presents banks with a unique opportunity to leverage the trust and security built into the DNA of many banks.

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  • @fintechna 3:35 am on May 5, 2018 Permalink | Reply
    Tags: , , 7e00ff, , , , , ,   

    Banks: We need to talk 

    Forget mobile apps— to start talking to customers

    As part of our guest blog series, Accenture Nordic Banking Practice Lead Satu Pulkkinen explores how banks can take the next step in evolving customer relations. 

    First came online and mobile banks, with Nordic banks leading the way. The next wave of digital banking? The conversational bank that operates within messaging applications. that can see and hear us, continuously growing ecosystems around increasingly popular messaging applications, as well as the amazing progress of artificial intelligence (AI), are enabling personalized, fully digital banking assistants that you can to anytime, anyplace.

    Technology is an integral part of our daily lives. Increasingly, devices that used to simply respond to our commands and actions can now also hear and see us. We use mobile applications for almost everything, especially instant messaging. Since the beginning of 2015, WhatsApp, Facebook Messenger, Snapchat and WeChat have become the world&8217;s most used social media applications.

    Over 60 percent of customers prefer messaging applications over email or phone calls. And we are moving on from using several different mobile applications to services that are integrated within ecosystems of those applications.

    Towards digital assistants with human understanding

    The development of artificial intelligence (AI) technologies, like machine learning and deep learning, has progressed at such a pace that the chatbots many Nordic banks use today are already starting to look outdated. As AI technologies continue to mature, bots will become even more human-like.

    The increased volume of data and number of analytic tools create the possibility of offering individualized digital services on a mass scale. This has already led us as customers to expect each digital interaction to be as good as our best last experience—regardless of the brand or industry in question.

    The result is a bank that can talk

    Conversational banking exploits these technology trends in an intelligent way. Banking bots within messaging applications and virtual assistants (like Apple&;s Siri or Google Assistant) connect cost savings brought by the previous generation’s online and mobile banks, with the personal touch previously provided by bank clerks.

    Banks: We need to talk fintech
    Read the report

    What is behind all this progress? Talking is natural for people. Complex language and communication separate humans from other animal species. Stories form the cornerstones of civilizations. Talking is, therefore, genetically encoded in all of us.

    In much the same way, messaging applications are natural to current mobile devices. These applications are easy and funand effortless to use, even on the move. We can type or speak and we can hold one- or two-way, personal or group conversations.

    Therefore, brands have rushed to embrace messaging applications. For example, Facebook Messenger has over 33,000 bots offering customer assistance and counseling as well as providing interactive experiences. And we seem to like them: over 60 percent of consumers use messaging applications to communicate with brands.

    Paying the bills or looking for investment tips—all accessible from your couch just by using your voice

    For example, in the future, a bank bot could interact like this: &;Hi Satu! I noticed that there’s €100 left over in your bank account. Should we put it in a fund that matches your expected return by only investing in environmentally friendly companies?´´

    Capital One in the US is one of the first financial institutions to move into conversational banking. It offers its customers an opportunity to check their account balances or pay bills just by talking with Amazon&8217;s Alexa—and without once touching a device. The customer just has to link his or her bank account to an Echo device. Once that’s set up, the bank literally obeys the customer’s voice.

    Now it’s time for Nordic banks to move on from online and mobile banking and start talking to customers. Who will be the first?

    Banks: We need to talk fintechSatu Pulkkinen, Nordic Banking Practice lead at Accenture

    Banks: We need to talk fintechBanks: We need to talk fintech Banks: We need to talk fintech

     

    The post Banks: We need to talk appeared first on Accenture Banking Blog.

    Accenture Banking Blog

     
  • @fintechna 3:35 pm on April 27, 2018 Permalink | Reply
    Tags: 7e00ff, , , , , , ,   

    Focus on fintechs? How banks can make the most of fintech partnerships 

    My colleagues Elena Mazzotti and Francesca Caminitti recently pointed out that collaborating with can move more rapidly and more effectively than they could on their own to introduce new products, streamline processes, enhance the customer experience and accelerate growth. It is a good time for banks to re-examine their strategies and explore the investments and necessary to get to the next level of digital sophistication.

    Focus on fintechs? How banks can make the most of fintech partnerships fintech
    View the report

    Indeed, Accenture analysis has found that banks’ revenues at risk from competition are typically in the range of two to three percent from lower loan origination, lower net income and fewer customers acquired. On the flip side, banks can gain a potential three to five percent in revenues by collaborating with fintechs, through enhanced customer acquisition, more fee-based revenues, better pricing accuracy and lower cost of risk.

    Three major challenges stand in the way of banks’ collaboration with new technology players:

    1. Ability to create open, collaborative environments with multiple players. While fintechs are often interested in collaborating (especially since it takes successful fintechs from 8 to 14 years to become profitable), their culture is generally very different from that of banks, and there is a need to create a new common culture—compatible with the current bank culture—to have significant market impact.
    2. Avoiding development of a “new legacy” by choosing some fintechs (particularly those providing technology services) that will not scale up to serving multiple players. This pitfall can be avoided by selecting fintechs such as Finastra or Avoloq, which have already been identified by incumbent technology players.
    3. Ability to “scale” the “New”. While proofs of concept (PoCs) have flourished over the last two years, we now see the era of innovation labs and digital factories. These initiatives aim in the right direction but are often sub-scale and lack the ability to attract talent, due to limited investments or lack of urgency to scale.

    Finally, we could take the discussion one step further and question the current on “fintechs”. Client journeys are going outside the scope of the purely financial, and relationships could benefit from partnerships between banks and players in other industries such as real estate, health, and education. The focus on fintechs may ultimately prove to be too narrow for banks seeking to enter underserved new markets.

    The post Focus on fintechs? How banks can make the most of fintech partnerships appeared first on Accenture Banking Blog.

    Accenture Banking Blog

     
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