Knowing which #startups to keep an eye on in #fintech can be a full time job (for some, it is actually a full-time job), especially as #more and more of them launch, get funding, and partner up with #banks. Take a look at the seven startups Bank Innovation is watching this month below: bonify Berlin […]
Bank Innovation
When #TransferWise first launched, CEO Kristo Käärmann did not expect a favorable response from incumbents, which still charge consumers considerably higher fees for cross-border transfers, compared to TransferWise’s 0.5% rate (in the U.K., on average). But the opposite trend began happening. “We learned overtime that #banks have an incredibly high cost-base to do the same […]
Bank Innovation
A #consortium of seven #European #banks will use #blockchain #technology to provide trade finance for #SMEs.
Financial Technology
For the third consecutive year, Bank Innovation has teamed up with Open Bank Project and (this year) the University of Warwick, to conduct a research survey on how financial institutions worldwide are prioritizing API initiatives in 2017. The report, which surveyed more than 200 high-ranking executives from financial services and banking industry, indicated a growing […]
Bank Innovation
Steve Jobs once said, “Your #customers dream of a happier and better life. Don’t move products. Instead, enrich lives.” Considering the degree to which Apple’s products are ingrained in people’s day-to-day lives, they’ve stuck well to Jobs’ guidance.
One of the areas of retail banking where it should be easiest to sell dreams, not products, is the mortgage business. People want to buy a house and build a future; they don’t want to buy a mortgage. Long before lifestyle reality shows conditioned us to always be thinking about remodelling, I remember walking the empty rooms of my first home in Scotland dreaming about the home it could become. Unless you’re a commercial developer, a mortgage is just a means to an end, but it’s still one of the most meaningful and intimate transactions that #banks can have with their customers. However, the entanglement of #mortgages with dreams and aspirations also makes it a very vulnerable product category. Customers’ dreams of a new home now tend to manifest themselves via a #digital footprint that ranges from simple real estate searches, to baby announcements, and relocation research. For lenders with the right analytical #tools, these digital footprints create an ideal opportunity to intersect customers before they ever think about contacting their bank. In the US, the result is that banks are now beginning to fade from the mortgage landscape, with non-banks occupying six out of the top 10 origination spots in 2016, up from just two in 2011¹.
Read the report
For banks to remain relevant in the mortgage category, they need to get into the dream-fulfilment business. That means going beyond the traditional bank credit offering to facilitate a compelling end-to-end home-buying journey. The goal must be to meet customers’ digitally groomed expectation that banks know them enough to anticipate their mortgage needs and delight them with relevant, hyper-personalized offers and service. To stay relevant, banks need to get out of their traditional reactive stance and develop a #predictive mortgage acquisition strategy.
Effective predictive mortgage origination draws on #three core digital tools that enable lenders to connect with borrowers and enhance their experience earlier in their journey to homeownership: programmatic marketing platforms, advanced analytics and artificial intelligence (AI). Together, these capabilities create predictive lenders who can put the customer at the center of their marketing efforts and act on moments of influence throughout the customer journey from dream to move-in date and beyond.
For example, good predictive lenders build data management platforms that store and cull rich customer attribute data to inform personalized, contextualized and precise offers. By analysing the data at a granular level, lenders learn more about customers’ device-usage patterns, behavioural trends, social media profiles, purchase history and search priorities, allowing them to respond to specific contextual cues instead of simply targeting segments. With AI, predictive lenders can automate personalized marketing to #acquire customers at scale, speed processes, limit manual intervention and cut costs. #This isn’t just about keyword search response where any customer behaviour vaguely related to a new home search results in them being bombarded with generic mortgage offers. That is the digital equivalent of dumb direct mail, and not surprisingly the hit rates are low and getting lower for that type of blunt-instrument marketing. Instead, sophisticated machine learning can glean real insights from patterns in customers’ behaviour and data relationships to refine and predict next-best actions to a level where bank interventions are seen as truly helpful and not annoying. The difference between the best and the rest is becoming dramatic. Those who can identify and interpret the right precursor home-buying signals from their customers have seen click-through rates improve to six times industry benchmarks.
Smart banks will help customers realize their dreams of a happier and better life in a new home by enriching the mortgage experience with greater predictability. To learn more about how, I invite you to explore our report: The power of prediction in digital mortgages
¹Wall Street Journal, November 2, 2016
The post This way to predictive mortgages: Three digital tools banks can use in the battle to acquire customers appeared first on Accenture Banking Blog.
#Banks #should approach points of digital friction in the same way e-commerce giants do, if they want to hold onto their customers. As noted in recent surveys, a single point of friction is all it takes for consumers to abandon a digital banking product—and thus, the bank itself. This means banks need to start taking […]
Bank Innovation
In my first blog of this series on our latest UK banking consumer survey—Beyond Digital—I explained why there’s still plenty of life in the bank branch, since even younger #customers still value human interaction. In this second post, I look at our findings on a much newer and more virtual channel to market: #robo-advice—the new generation of automated financial advice services powered by artificial intelligence (AI).
#Banks across the world are continuing to invest heavily in robo-advisery services, seeing them as a way to deliver personally tailored financial information and guidance at high scale and relatively low marginal cost. The headline findings from our study suggest that this investment is justified, with fully two-thirds of all UK customers and 74 percent of millennials saying they’d be willing to receive entirely computer-generated advice on relatively simple decisions such as which type of bank account to #open (see Figure 1).
Interestingly, an even higher proportion of consumers—74 percent overall, rising to 79 percent of millennials—say they’re willing to receive robo-advice on more complex issues such as what investments they should make. And as Figure 2 shows, when asked why they’d be happy to accept advice from a machine instead of a human, they point mainly to benefits around speed and convenience, cost, and impartiality.
A deeper analysis reveals further significant insights. For example, while 25 percent of all consumers say robo-advisers’ greater impartiality gives them an advantage over their human counterparts, the proportion believing this rises to almost one-third among OAPs—suggesting older consumers are more sceptical about the objectivity of human advisers. And our findings that only 19 percent of consumers think computers are less likely to make mistakes, and that just 13 percent believe their data would be more secure than with a human, suggest the overwhelming majority have limited trust in robo-advisers’ decision making and security.
Our study also indicates that there are some areas of financial advice where consumers feel human interactions have yet to be fully translated into the available technologies. As Figure 3 shows, almost two-thirds think it’s important to have human advisers on hand to provide advice on large, long-term products such as mortgages. In contrast, fewer than half feel they need human guidance on using their bank’s online and mobile services.
And in terms of what they value about speaking to a human representative, consumers rate the ability to ask direct questions and seek personalised advice as the top advantage, followed by being able to get what they need faster, and then humans’ better ability to explain complex issues. Interestingly, having a representative who knows the consumer well ranks very low as a benefit.
So, what does all this means for banks’ robo-advice strategies and investments? Combine these findings with those I presented in my first blog—including the fact that millennials are the heaviest users of branches, tapering down to OAPs as the lightest—and I believe a clear message emerges: Winning and retaining customers in the future will depend critically on striking the right balance between human-delivered and AI-driven services.
Put simply, banks need to recognise that for many consumers—including younger ones—the shift towards computer-generated services cannot succeed if it’s at the expense of access to human service at their local bank branch. And automation must be used to not only make banks work smarter, but also to improve and personalise the customer experience.
It follows that the next challenge for many banks is to reassure customers that they can receive the same level of service from a robo-adviser, and pull together the various threads of information they hold on their customers to create a personalised yet secure service. Consumers’ readiness to accept robo-advice for some financial decisions means that banks developing these services are pushing at an open door. But this doesn’t mean they can afford to shut off their customers’ access to interactions with real humans.
The post Customers are open to robo-advice—with a few conditions appeared first on Accenture Banking Blog.
In my first blog of this series on our latest UK banking consumer survey—Beyond Digital—I explained why there’s still plenty of life in the bank branch, since even younger #customers still value human interaction. In this second post, I look at our findings on a much newer and more virtual channel to market: #robo-advice—the new generation of automated financial advice services powered by artificial intelligence (AI).
#Banks across the world are continuing to invest heavily in robo-advisery services, seeing them as a way to deliver personally tailored financial information and guidance at high scale and relatively low marginal cost. The headline findings from our study suggest that this investment is justified, with fully two-thirds of all UK customers and 74 percent of millennials saying they’d be willing to receive entirely computer-generated advice on relatively simple decisions such as which type of bank account to #open (see Figure 1).
Interestingly, an even higher proportion of consumers—74 percent overall, rising to 79 percent of millennials—say they’re willing to receive robo-advice on more complex issues such as what investments they should make. And as Figure 2 shows, when asked why they’d be happy to accept advice from a machine instead of a human, they point mainly to benefits around speed and convenience, cost, and impartiality.
A deeper analysis reveals further significant insights. For example, while 25 percent of all consumers say robo-advisers’ greater impartiality gives them an advantage over their human counterparts, the proportion believing this rises to almost one-third among OAPs—suggesting older consumers are more sceptical about the objectivity of human advisers. And our findings that only 19 percent of consumers think computers are less likely to make mistakes, and that just 13 percent believe their data would be more secure than with a human, suggest the overwhelming majority have limited trust in robo-advisers’ decision making and security.
Our study also indicates that there are some areas of financial advice where consumers feel human interactions have yet to be fully translated into the available technologies. As Figure 3 shows, almost two-thirds think it’s important to have human advisers on hand to provide advice on large, long-term products such as mortgages. In contrast, fewer than half feel they need human guidance on using their bank’s online and mobile services.
And in terms of what they value about speaking to a human representative, consumers rate the ability to ask direct questions and seek personalised advice as the top advantage, followed by being able to get what they need faster, and then humans’ better ability to explain complex issues. Interestingly, having a representative who knows the consumer well ranks very low as a benefit.
So, what does all this means for banks’ robo-advice strategies and investments? Combine these findings with those I presented in my first blog—including the fact that millennials are the heaviest users of branches, tapering down to OAPs as the lightest—and I believe a clear message emerges: Winning and retaining customers in the future will depend critically on striking the right balance between human-delivered and AI-driven services.
Put simply, banks need to recognise that for many consumers—including younger ones—the shift towards computer-generated services cannot succeed if it’s at the expense of access to human service at their local bank branch. And automation must be used to not only make banks work smarter, but also to improve and personalise the customer experience.
It follows that the next challenge for many banks is to reassure customers that they can receive the same level of service from a robo-adviser, and pull together the various threads of information they hold on their customers to create a personalised yet secure service. Consumers’ readiness to accept robo-advice for some financial decisions means that banks developing these services are pushing at an open door. But this doesn’t mean they can afford to shut off their customers’ access to interactions with real humans.
In my next blog, I’ll look at the changing role of banks’ contact centres. Watch this space.
The post Customers are open to robo-advice—with a few conditions appeared first on Accenture Banking Blog.
In this episode, host Brett King is joined by Stephen Wolfram to talk about Artificial Intelligence and Machine Learning, and how those will affect the #future of #money, finance, and the ethical discussions we need to be having to plan for it. Stephen Wolfram is the creator of Mathematica, Wolfram|Alpha and the Wolfram Language; the author of […]
Bank Innovation
Javelin thinks #trust is the key to building long-term #relationships in banking.
Financial Technology
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