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  • user 4:52 am on December 4, 2018 Permalink | Reply
    Tags: , , , Intelligence, Reducing,   

    Reducing KYC Costs With Digital And Artificial Intelligence 

    Getting right isn’t easy, EXL worked with HSBC to apply digital tools to KYC.
    Financial Technology

  • user 12:18 am on August 24, 2018 Permalink | Reply
    Tags: , , Beginning, Intelligence, , Limitations, ,   

    Banks Are Just Beginning to Understand the Power (and Limitations) of Artificial Intelligence 

    Citi Ventures&;s recent investment in Anaconda, an Austin, Texas-based AI and machine learning (ML) software company, shows the industry&;s commitment to staying at the forefront of this growing and developing field. AI has certainly generated a lot of chatter and buzz in the financial world, but are still challenged to implement it properly. Citi [&;]
    Bank Innovation

  • user 3:35 am on July 1, 2018 Permalink | Reply
    Tags: , , Bronze, Intelligence, ,   

    Will artificial intelligence launch a new Bronze Age? 

    In my last blog, I discussed how and talent are the building blocks for ’ transformation to what Accenture calls “the New”.

    But now let’s take a step back. Around five thousand years ago, humans in what is now China and Europe began working with an alloy of copper and tin. Combined, these two soft metals formed , a material harder than other metals available at the time.

    In the Bronze Age that followed, civilization made great leaps in agriculture, writing and government, all enabled by the gains in productivity from this valuable alloy.

    I don’t think it is unrealistic to believe that we are looking at the start of a new Bronze Age, an era of unleashed potential made possible by a new alloy: the combination of human and (AI) in the workplace.

    Read the report

    Our recent research into the attitudes of financial services executives and workers toward the future of the workforce indicates that this belief is widely shared. Nearly seven in ten (69 percent) financial services executives said the industry would be completely transformed by intelligent technologies, and nearly two-thirds (63 percent) said they expect AI to result in a net gain in jobs in their organization over the next three years.  Bankers were even more optimistic at 74 percent and 67 percent, respectively.  And 62 percent of all financial services employees (67 percent in banking) said they expect intelligent technologies to create opportunities for their work.

    Across the board, survey respondents said they believed that AI would cause more jobs to be reconfigured than eliminated and that reconfigured jobs would be more strategic. Contradictions emerge, however, as many firms indicate that their people may not be ready for this transformation. Financial services executives say only one in four of their employees are ready to work with intelligent technologies, and nearly half (47 percent) say the growing skills gap is the leading factor affecting their workforce strategy. Yet only a small number (3 percent) indicate they plan to significantly increase their investment in reskilling over the next three years. Firms will need to resolve these contradictions to make real progress in creating the human/AI alloy needed for the new Bronze Age.

    Digital in general, and AI, in particular, can transform financial services HR support in multiple ways, with three levels of transformation to be reached:

    1. The first level of transformation is to digitize the existing processes linked to workforce management, lightening the process weight and facilitating new ways of working—ranging from tackling processes such as role fulfillment and evaluation to personal development and enhanced collaboration.
    2. The second level of transformation—which, like the third level, cannot be done without reimagining the way people and machines work together—is to pivot the workforce by supporting employees as they reinvent their role within the organization. Our research indicates that a large majority of workers are eager and willing to be retrained (with as many as 85 percent saying they would invest their free time to learn new skills).  Accenture recently announced a $ 200 million commitment to education, training and skills initiatives over the next three years, to equip people with the skills needed for the new work environment.
    3. The third level of transformation is “scaling up to the new”—that is, augmenting people’s capabilities to develop new business models using artificial intelligence. Scaling up means promoting innovation within the whole organization, through a different HR management model, different organizational structures (such as the tribes model) and different evaluation KPIs.

    A few banks and insurers have already started applying AI to their HR management, but the journey through the three levels has not yet been made at scale and will require significant investment in talent management, retraining and redeployment.  The new Bronze Age will confer advantages on firms that can harness the human/AI alloy, but doing so will require a serious commitment to the human as well as the AI part of the mix.

    Learn more about Accenture’s research into automation and the future of the workforce in our report, Reworking the Revolution.

    The post Will artificial intelligence launch a new Bronze Age? appeared first on Accenture Banking Blog.

    Accenture Banking Blog

  • user 12:18 am on May 27, 2018 Permalink | Reply
    Tags: , Alone, , , , , , , Ingenuity, Intelligence,   

    Artificial Intelligence Can’t Fight Fraud Alone — Human Ingenuity Is Also Needed 

    , machine learning, and compliance were some of the topics that dominated day 1 of conference Data Disrupt, taking place in New York. The panel “Consumer Finance: Fighting with Fire” brought together three fintech companies, who discussed different methods of combating fraud. AI and ML play undeniably large roles in fighting financial [&;]
    Bank Innovation

  • user 3:35 pm on December 16, 2017 Permalink | Reply
    Tags: , , , Intelligence, , , , ,   

    Artificial intelligence: Unlocking value from process 

    I have recently moved to Dublin for a six-month secondment, and have the pleasure of leading our small but growing Accenture Research team based at The Dock, Accenture’s state-of-the-art R&D hub.

    This is an amazing space to work in, where that terrible phrase “the art of the possible” isn’t so cringingly hackneyed, and actually means something. In a room close to where I am sitting writing this, there is a team creating software for a space “cube” that will be launched into orbit to gather data for a project (I could tell you what that involved, but then it would automatically self-destruct etc., etc). In this environment, automation could almost feel old hat.

    Not so intelligent automation though. This is definitely in the realm of “anything is possible”. Intelligent automation learns as it works. It isn’t just doing what it is told; it is constantly adapting to new situations. Imagine a -advisor that remembers when a customer started to sound agitated during a call, and adapts the number or style of questions they ask on their next interaction, to try to improve the experience? Hyper-personalisation of services is an expectation by which customers will increasingly rank their banking experience, as they become used to having the choices available to them through Open Banking. And intelligent automation is one of the core tools available in a bank’s armoury to get them to this level of service, without (ahem) breaking the bank.

    are in the perfect position to ride this wave of personalised services—if they can adapt to a platform that funnels a customer towards these slicker services. And thanks to intelligent automation, this need not come at a hyper-cost to the business, with fully automated approvals that adapt to a users’ preferences and usage of third parties. Even the potential for fraud could be reduced as a result of IA learning a customer’s patterns of use and being able to spot anomalies and potentially fraudulent transactions.

    Aside the pure efficiency benefits available from IA, this could also provide recommendations to customers for products and services available to them based on their current circumstances and financial needs, such as an overdraft facility if they are low on funds. Thanks to IA, the bank knows that based on previous spending patterns, the consumer will likely need £x amount to spend until their next bank credit payment is due.

    This intelligent automation of services is heavily reliant on data, the last but by no means least part of the AI trinity: People x x Data. And there are numerous ways in which banks are custodians of vast amounts of customer information, which is ripe for a reinvented approach. And they don’t even need to send a cube out into space to achieve this.


    The post Artificial intelligence: Unlocking value from process appeared first on Accenture Banking Blog.

    Accenture Banking Blog

  • user 3:35 am on December 12, 2017 Permalink | Reply
    Tags: , , , , Intelligence, ,   

    Artificial intelligence: Unlocking value from data 

    One of the key things I have learnt since recently moving to Dublin is that a little information goes a long way.

    For instance, I have already learnt that Guinness tastes infinitely better here than it does anywhere else in the world. Another vital piece of information I learnt the hard way, is that you should never, NEVER, go anywhere without an umbrella. Even if it is a sparkling clear day when you step out in the morning, by the time you reach the end of the road you could easily be under attack a sideways-driven sheet of rain…it is not the emerald isle for nothing!

    Information is the cornerstone of most of our decisions, and should be no different in making use of the vast quantities of that they have in order to determine their next steps or provide new hereto underestimated potential revenue streams.

    A slew of regulations about to be implemented, including Open Banking and GDPR, could be seen as an inconvenient obligation—or worse—a threat to the incumbency of the traditional bank. Allowing as they do, greater access to third parties, to the valuable relationship between bank and customer, and greater control to customers over their own data. Banks might take comfort from the fact that customers are currently nervous of sharing their data with anyone other than their bank—85 percent cited the potential for fraud as a key reason they would be reluctant to allow third parties to access their data—in one of our recent surveys. Yet this will only last until a critical mass of a customer’s peers start to recommend an alternative service (think Uberization), and suddenly the returns outweigh the risks.

    But fortunately, banks are coming around to the idea that these regulations regarding data management and access are a beneficial catalyst to embracing the next generation of banking services. And that using the huge amount of data they possess to break down revenue siloes centred around a particular product or service, and gain greater insight into their customers, will place banks squarely in the zone to be the innovators of the future.

    Banks are still in a position of trust: Most customers would prefer their data be used by the bank, rather than a third party, to provide better services. Although it would be prudent for banks to start adapting the type of service they have now, rather than waiting until they have fixed all their legacy issues, as some appear to favour.

    Adopting a data-driven platform model in which a bank is the custodian of this valuable data commodity, and can channel consumers towards products and services offered by others, could create a new revenue channel for banks. They would be able to still offer their own products, but for those they cannot help—perhaps due to risk appetite or a product/service they do not offer themselves—they could conceivably charge other providers a fee for product recommendations to customers.

    Providing a secure way for products to be offered and availed of by customers is also within the influence of banks. They have huge amounts of security experience, which incoming financial services providers may lack, and which a bank may also be able to monetise, based on what they know about customers’ needs and spending habits through their data.

    Timing is everything though, and waiting to fix all your legacy issues before moving forward could be very costly. Digitally decoupling and adopting a two-speed development strategy to leapfrog over some of these issues, should be more than just a “would like to have” strategy—creating an environment where data can drive forward new products and services, and create multiple new revenue channels concurrently. Developing, deploying, and scaling at speed is within reach of banks, so long as they adopt and adapt to the new narrative of the industry.

    As one of Ireland’s favourite sons once said, “Consistency is the last refuge of the unimaginative”, and while the quality of service offered must always be of a high standard, the way in which it is offered or charged for, based on new and innovative ways of interpreting data, is ripe for reimagining.


    The post Artificial intelligence: Unlocking value from data appeared first on Accenture Banking Blog.

    Accenture Banking Blog

  • user 1:53 am on November 21, 2017 Permalink | Reply
    Tags: , , Brighterion's, , , Intelligence, , , , ,   

    Brighterion’s Artificial Intelligence Software Wins Morgan Stanley’s First Fintech Award 

    Stanley issued its inaugural to Brighterion, a Mastercard company that fights fraud with AI.
    Financial Technology

  • user 3:35 pm on September 29, 2017 Permalink | Reply
    Tags: , , , , , Intelligence, ,   


    These are exactly the sort of words that would make you launch your phone into the nearest river, if they had been uttered by Siri. Fortunately, they are the fictional words of HAL 9000, the sentient system in the 1968 Stanley Kubrick film, A Space Odyssey: 2001. It told the story of a mission to Jupiter and the gradual realisation of the crew that the perfect piece of AI designed to help them, was in fact fallible, and plotting against them to preserve its existence.

    We don’t appear to have come much further in our collective sentiment towards trusting AI. The term “killer robots” has been splashed across the press headlines quite a bit recently, with some heavyweight names behind them, highlighting the potential dangers of using AI in warfare. Some of these warnings around the ethical usage of AI are undoubtedly justified. How do you prevent AI from learning bad characteristics as well as good? It doesn’t necessarily need to be as dramatic as the use of AI in war. It could be as simple as AI learning some of the sadly still intrinsic bias in society, such as that boys wear blue and girls wear pink. The stock archive this technology is likely to learn from has been written by humans. And humans have prejudices, fears, and ideas that they want to promote. AI may not be able to help learning some of these, and apportioning blame to the technology would be a mistake, but they could still have an impact on the service provided to us.

    Ethical issues aside, nervousness around AI in the workplace is much closer to home, and again in many ways, there is justification for some jitters from employees. Technology has a history of replacing humans in the —and the initial stages of this can be painful. Printing presses, weaving machines, mechanised farming, automated production lines, to name a few that have disrupted the workforce across industries. AI in banking could undoubtedly do the same if deployed without a long-term, sustainable plan from .

    In our upcoming series of reports on AI in financial services, Accenture looks at the potential advantages and pitfalls of embracing AI in banking, capital markets and insurance.

    “People x Process x Data = AI” is our view on the success of AI in the workplace. The process and data side we will come back to another time—but an equally important part of AI are the “people” that this technology will work alongside. Many have years of experience, most of which will not be written down for an AI colleague to pick up and assimilate into its own bank of knowledge. The importance of people is particularly significant in banking, where interaction between the bank and customer is still of vital importance to most, and must become a priority. Fifty-three percent of customers still go into their branch once a month or more. Customers like and want the reassurance of being able to speak to a person.

    That is not to say that many would not be happy with a “phygital” blend of interaction with their bank. But if this is to be a success, then the workforce needs to be ready and able to use this technology. And with 30 percent of banking executives unsure that their current workforce has the necessary skills and experience to use AI technology to its optimum, there is cause for concern that the rollout of this technology could pose a problem for banks.

    For it to be a success, a fully detailed proof of concept should be in place, with an inventory of the workforce skillset being of primary importance, before any decisions are made on how and where to use AI. Easier said than done? It needn’t be. Some simple “best practice” steps should help this along. To name a few:

    • Involving the workforce in decision-making and investigations into how and where AI could help them in their roles would go a long way towards easing any transition of jobs
    • Providing training to understand what the technology involves, and showing its limitations as well as its advantages
    • Showing how AI could take away some of the more repetitive and frustrating parts of a function, leaving the employee to do the more interesting parts of their role, and take part in more creative and stimulating work
    • Introducing roles that will make use of AI to create value within the business, and which need some human imagination to create. The lack of differentiation in products has long been lamented by customers. Using AI to simulate how a new product might work for a bank, in a fail-fast, low-risk environment, has its obvious advantages

    Maybe the ethics of using AI is less around whether there is a risk it will learn our worst traits, and more around what our intentions are from using it. If it is just to slash the costs of the workforce, then employers are missing a trick, and could find themselves on the receiving end of public and regulatory disapproval. Their employees have something AI cannot learn: empathy and understanding of human nature. Both of which are vital in a customer-facing service, and which in its current format AI cannot provide on its own, meaning a combined AI/human workforce is necessary to get the best from this technology. The future is bright; the future is still human.


    The post ARTIFICIAL INTELLIGENCE: AUGMENTING THE HUMAN WORKFORCE appeared first on Accenture Banking Blog.

    Accenture Banking Blog

  • user 7:14 am on May 23, 2017 Permalink | Reply
    Tags: , , CardLinx, , , CrossIndustry, , Intelligence, , Spearheads,   

    CardLinx Retail Tech Forum on Commerce Bots and Artificial Intelligence Spearheads Cross-Industry Collaboration 

    Interactive forum with speakers from Hilton, Discover, Verifone and others will be held on Sept. 12, 2017 in Chicago. sales as a percentage of GDP exceed 50% for the largest economies in the world, and increasingly the future growth of the retail sector will be tied to the development and adoption of new [&;]
    Bank Innovation

  • user 2:48 pm on February 10, 2017 Permalink | Reply
    Tags: , , , Intelligence,   

    Why 2017 Will Be the Year of Artificial Intelligence in Banking 

    is coming to &; scratch that, it&;s already here, but customers may not have noticed. AI is already playing a role in consumers&8217; lives, whether they know it or not. Talking to Siri, looking at recommendations from Amazon or Netflix, or chatting with Google Home about theRead More
    Bank Innovation

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