Does Anyone Outside PR Firms Think Surveys Are Newsworthy?

In a recent blog at Articulate Communications I wrote about the number of surveys that public relations firms send out, and how useless many of them are. I just reviewed my Inbox to see what the recent evidence is…the results are below and include six surveys I have received so far today. They include such stunning news as John Hancock on mindfulness and  a bit on risk analysis that survey 499 residents of Tianjin, China on how they view self-driving cars.  Really, what  could I have done without these survey press releases?

I publish occasionally at the Articulate Communications blog  on issues of financial technology, banking and associated public relations and marketing topics. In the past I have written about design thinking, how to avoid bank PR-speak and whether banking and innovation belong in the same sentence.

Here are some recent surveys I have received and ignored, at least until now.

June 14 from the Society for Risk Analysis: Survey Says: Self Driving Cars Should Reduce Traffic Fatalities by At Least 75 Percent to Stay on the Roads…The survey was distributed to a convenience sample of residents in Tianjin, China. Of the 499 respondents…The broadly acceptable risk criterion for SDVs is set as two orders of magnitude lower than current global traffic risk…

June 14 — Not quite sure what this John Hancock release has to do with anything, but here it is:
According to the John Hancock Mindfulness Survey, Americans are missing out on the benefits of mindfulness, as only 12 percent of respondents practice meditation or mindfulness when they are stressed. Of those who do, nearly 70 percent cite meditation and mindfulness as the most effective activity for managing their stress, ranked above listening to music, sleeping or exercising.

June 14 Kount’s 6th Annual Mobile Fraud & Payments Survey Finds Complacency and Regression Among Merchants’ Mobile Fraud Mitigation Strategies…about 35 percent of merchants still do not track mobile fraud… Only half of surveyed merchants believe the mobile channel requires additional or specialized tools, compared to between two-thirds and three-quarters of merchants in each of the past studies…

• Most notably, merchant support for Apple Pay has gone down from 48% to 35%
• Google Pay (previously Android Pay), is down from 38% to 25%
• Support for PayPal increased (from 48% to 64%) while 10% accept AliPay and 10% accept other e-wallets.

June 14 Remitly Study Reveals 9 in 10 Immigrants in the U.S. Believe the American Dream is Still Achievable

Remitly found more than half of first-generation immigrants (60 percent) would still recommend relocating to the U.S. to a friend, family member, or colleague…Sixty-two percent of immigrants trust mobile technology to handle their finances

June 14 A global poll of SMEs and microbusinesses, conducted by global booking software platform, has discovered that tech skill shortages and the cost of administration are among the biggest threats to entrepreneurship in Britain after Brexit.

• The biggest surprise to business owners was needed to do ‘too many things at once’, with 43 per cent registering that as their biggest grievance ahead of admin at 39 per cent.
• 57 per cent of respondents chose time constraints (doing everything yourself) as the biggest challenge to growing a business ahead of not being able to hire the right staff (24 per cent).

June 14 A new survey among more than 100 founders of London tech startups, conducted by Studio Graphene in partnership with City RoadCommunications, has revealed the main staffing challenges and concerns that are holding back London tech companies. It found:
• 33% of the founders believe there is a shortage of skilled tech workers in London
• Worryingly, 30% also say their growth has been hampered as a result of them not being able to hire the right employees
• Finding people who fit the startup culture was also cited as a major issue:
◦ 39% of founders of London tech businesses say it is hard to find people who have the right mind-set and work ethic to be employed in a startup

June 12 Temenos
Latin American banks are racing to deliver digital banking to the masses says report released today by Temenos
• Regional change is driven by changing customer behaviour and demands according to 55% of banking survey respondents
• Latin American banks see a bigger impact coming from new entrants than their peers in the rest of the world (48% vs. 36% globally)
• For established banks, new payment players are the biggest threat according to 51% of respondents, followed by neo-banks (23%)
• Survey respondents think that in-house innovation centres (51%), accelerator/ incubator programs (48%), and creating closed bank hubs (48%) are the best way to innovate

June 11 Extend’s Millennials Report Shows Only 11% Of Millennials Have A Business Credit Card From Their Employer
The survey also found that nearly 25% of participants borrow a colleagues’ business credit card to make business purchases

• 44% buy travel, 55% food and car services, 56% business supplies or online services, and 24% pay for invoices (eg, marketing services, online research, conferences, etc.)
• 39% spend more than $500 a month on business expenses that are ultimately paid by their employer
• 30% find it difficult to have access to a mean of payment from their employer
• 25% borrow a business credit card from colleagues to make these business purchases while 67% use their personal credit card and then get reimbursed

May 2018 GlobalData

– 52.3% of global HNW investors reside in North America, but growth is more pronounced in Latin America, where the number of HNW individuals is forecast to grow by 48% between 2017 and 2021.
– Professionals make up 5 million individuals of the global HNW market, 4.8 million being entrepreneurs.
– 28.3% of HNW clients have been acquired through client referrals, making it the most successful channel.
– A longstanding advisor relationship is the most effective means of client retention, followed by portfolio performance and a firm’s brand image.


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SAS Beefs Up Cyber Protection With New Fraud and Security Unit

SAS has created a new global Fraud and Security Intelligence Division to help organizations better detect and combat threats from fraudsters and hackers. The division will further focus and sharpen the SAS efforts to combat fraud and cybersecurity threats. The Association of Certified Fraud Examiners estimates that the typical organization loses 5 percent of annual revenues to fraud, equating to trillions of dollars in losses worldwide each year.

SAS already has more than 400 employees in 25 countries across the Americas, Europe and Asia focused on this area and it plans to add 100 employees to the division over three years. According to PwC’s 2018 Global Economic Crime and Fraud Survey, 49% of companies say they’ve been victims of fraud and economic crime in the last two years – up from 36% the year before.

Stu Bradley will lead the new SAS division as vice president of fraud and security intelligence; the division has 250 people and plans to add another 100. Most recently the SAS vice president of cybersecurity solutions, Bradley has 20 years’ industry experience fighting fraud and abuse, the last nine at SAS.

“Over the last 15 years, SAS has built a reputation as the leader in fraud and security intelligence,” said Bradley. “The rise of the digital economy has been matched by the rapid spread of fraud and cybersecurity risks, making now an ideal time for SAS to redouble and refocus its leadership in this area. We want to meet customers where they are in their analytics journeys, particularly as they adopt technologies like AI, IoT and cloud. With SAS to help them, they will be even better equipped to break down data silos, adjust to shifting regulations, and safeguard against present and future risks.”

One of the great challenges in fighting fraud developing the intelligence and analytics to avoid false positives that can annoy customers and lead to loss of their business. SAS says that banks need a strategy and the right technology to manage risk while providing the service customers expect.

For Landsbankinn, the largest bank in Iceland, finding the balance between providing service for its 120,000 customers and screening transactions for suspicious activity is crucial for its compliance staff.

“Landsbankinn seeks to fulfill the strictest requirements regarding money laundering, criminal financing and other illegal activities,” says Thordur Orlygsson, chief compliance officer for Landsbankinn. “And to meet those demands, we need to have a sophisticated and robust solution.”

The company chose SAS®Anti-Money Laundering to identify patterns in its data. Landsbankinn also uses SAS Visual Analytics to provide data visualization capabilities for analysts across the organization.

While a vast majority of the transactions Landsbankinn processes won’t trigger any alerts, a handful may point to suspicious activity. That’s where the company’s compliance team comes in.

“It’s not possible for us to look manually at all transactions,” Orlygsson says. “We need a system like SAS to help us do pattern analysis to identify suspicious transactions to be referred for investigation.”
Computers are better than people at analyzing fraud. In e-commerce trails in the U.S., where customers don’t present a card — the transactions are known as CNP for Card Not Present — software like Forter and Radial have proven to accept many more good transactions than well-trained fraud prevention teams.

SAS said its new fraud and security intelligence division will drive greater innovation by bringing together software developers and technology professionals from across the fraud, compliance and security domains.

“SAS customers will benefit from hybrid analytic approaches with embedded machine learning, artificial intelligence (AI) and social network analytics,” the company said in its announcement.

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Consumers Prefer AI Supplemented By Human Interaction

Consumers are more comfortable with AI in healthcare than other industries, according to an SAS survey. Lack of human interaction is the most cited reason for discomfort with artificial intelligence.

While the buzz around artificial intelligence (AI) can seem ominous, consumers are surprisingly comfortable with the technology in healthcare than in banking or retail. The survey found that a lack of human interaction was the top reason respondents cited for feeling uncomfortable with the technology.

Just under half of respondents (47%) were comfortable with companies using AI in business interactions generally, with men (53%) slightly more comfortable than women (43%).

Data privacy is also a concern to those surveyed. Only a third of respondents were at all confident that their personal data used for AI was being stored securely. Those under 40 years of age felt more confident (42%) that their information was protected, versus just 31% of older respondents.

“Consumers feel positively about AI when they believe it s being used for good, ” said David Tareen, marketing manager for AI at SAS. “In this survey, healthcare scenarios were well-received, indicating that respondents were comfortable with a tangible benefit to the technology. Overall, a lack of understanding about what AI is and can do is a significant factor for those who fear it.”

AI technologies that assist physicians in patient care rated well with respondents, even when asked about surgery. Forty-seven percent of those surveyed were comfortable with AI assisting doctors in the operating room . More than half of respondents over age 40 were willing to go under the knife with the help of technology, compared with only 40 percent under age 40. Six in ten participants (61 percent) were comfortable with their doctor using data from wearable devices, such as an Apple Watch or Fitbit, to assess their lifestyle and make recommendations based on that data.

When it comes to dollars and cents, survey respondents were not comfortable with banks using AI to interact with them. Monitoring for fraud and other potential threats was the only exception, with 59% indicating they were comfortable with this use of AI.

Accessing a customer’s credit history to make a credit card recommendation was the least popular among potential real-world uses of AI by banks.

Of the three industries suggested by the survey, AI in retail made consumers most uncomfortable. Only 44% surveyed indicated they were willing to share location information in order to personalize their shopping experience. And only 36 percent were okay using their smart phones to enter and shop in a cashier-free store.

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Celent Seeks Nominations For Model Bank Awards

Dan Latimore, Celent SVP, said that after attending multiple conferences, including Sibos and Money2020 back to back, not to mention Finovate earlier in the autumn conference season, the Celent team remained coherent and was able to define some conclusions.


Now Celent is looking for nominations.

“I’m excited about the initial response to our Model Bank Awards (see below for details on how to submit). Last year we had over 150 submissions, half again as many as 2016, which was itself a record year. Our hypothesis: banks, who’ve historically been very shy about trumpeting their technology successes in any detail, now see that they need to demonstrate to their stakeholders – investors, management, and employees – that they’re being innovative. Winning a Celent Model Bank Award is a great way to do that.

“For 2018, we are again accepting nominations in five categories: Customer Experience, Products, Operations and Risk, Legacy Transformation, and Emerging Innovation , although if you’re not sure where your initiative fits, just take your best guess – we’ll be happy to slot it in appropriately as we assess the nominations.”

Send nominations to Dan through the Celent contact form or Twitter…

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Big Data = New Oil — What’s That Even Mean?

During Teradata’s annual Partners conference in Anaheim, CA toward the end of October an executive  almost inevitably referred to big data as the new oil. Antony Peyton, deputy editor of London-based Banking Technology asked what that meant, which led to a certain amount of inconclusive rambling discussion.

As a college friend said long ago, the only thing worse than reasoning by analogy is reasoning by bad analogy.

The analogy of big data and oil has apparently been around since 2006, much to my surprise.

For example, marketing commentator Michael Palmer blogged back in 2006: “Data is just like crude. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc., to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.”

Steve Brobst, chief technology officer at Teradata, said he is more interested in using big data in areas like health care to see if it is able to predict when someone is heading to the hospital.

“That’s more interested than selling stuff.”

Teradata 2017 6 622

Steve Brobst, CTO of Teradata

A health expert predicted heart attacks could become obsolete within a few years because sensors and analytics could detect changes days ahead, providing time for treatment before an attack.

In 2012 Ann Winblad responded to a CNBC question about the next big thing by saying “Data is the new oil.”

Big data is also Google and Facebook selling their users to Russian info warriors who are intent on disrupting American society. And it’s Equifax collecting details on American individuals and businesses and then allowing it to be hacked

Jer Thorp argued in HBR in 2012 argued Big data is not the new oil. “Information is the ultimate renewable resource.”

We have already seen “data spills” happen (when large amounts of personal data are inadvertently leaked). Will it be much longer until we see dangerous data drilling practices? Or until we start to see long term effects from “data pollution”?

Niraj Dawar in HBR last year wrote :

“The questions that need to be asked of big data are not just what will trigger the next purchase, but what will get this customer to remain loyal; not just what price the customer is willing pay for the next transaction, but what will be the customer’s life-time value; and not just what will get customers to switch in from a competitor, but what will prevent them from switching out when a competitor offers a better price.”




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To Compete, Companies Need To Use Data Better

Corporations have to decide what they want to be when they grow up, said Oliver Ratzesberger, EVP and chief product officer of Teradata. They need to learn how to incorporate data in their corporate strategy and decision-making, added Ratzesberger, co-author with Northwestern University professor Dr. Mohan Sawhney of a new book, “The Sentient Enterprise”,

The Sentient Enterprisewhich looks at how leading companies are doing just that. Their examples include Wells Fargo, Verizon, Dell, Siemens and General Motors.

“We wanted to put concepts of data agility in the hands not just of top executives, but any business user who interacts with data and wants to improve that interaction,” Ratzesberger wrote in a blog post.

Ratzesberger, who was a leader in eBay’s pioneering use of Teradata, said that incorporating data into the core of a corporation’s takes time and C-suite commitment

“Mohan and I are trying to advance an idea where data and analytics can do more than just act as a bean counter of what’s happening within a company . The sentient enterprise actually does some of the understanding itself and takes on aspects of operational decision-making, freeing the human mind to focus on high-level strategic analysis and creativity,” he wrote on Teradata’s Forbes page recently.

Disruptive technology won’t succeed if executive protect their profitable business from the potential change said Ratzesberger.

“Too many executives are telling teams not to cannibalize their high margin business,” he said during at interview at the Teradata Partners conference. “That leaves a company open to disruption from the outside.”

He likes P&G as an example of a company that is using technology to get closer to customers, although the only example he cited was an electric toothbrush that links to a mobile phone and can show a user which parts of his mouth he is neglecting. Apps and links to phones can help even a company that sells through retailers to connect directly to customers more effectively than trying to track them with coupons. A big wholesaler like P&G didn’t have direct customer data for analytics 10 years ago and has recently faced startling competition from such innovators as online razor blade sellers.

Oliver sees an organizational issue here…a company has to pay attention to its culture, its people, and process change and learn to become agile at scale, with governance built in. They also need to think long-term — 5 to 10 years out — to build sustainable change.

The Wild West works — for 30 to 90 days — and then crashes down like a house of cards, he added. “We talk to C-level executives and ask how they are thinking about their roadmap and disruption in their companies.”

He said they need “faster collaboration, learn to build at scale and get algorithms which will change business processes such as supply chain.”

When companies are faced with exabytes of data, they need to to something smart.

“At eBay, where the company had 800 analysts there was still too much data and we would miss changes in the market.”

Fortunately new capabilities are coming together, he added.

“Most corporations aren’t ready for data — they have silos and data drift. They often argue and can’t agree on even basic data such as their number of customers.”

Leading companies have learned what can be done with data such as Kaizen, Six Sigma and Lean to predict certain outcomes.

“We’ve learned in the last decades…that a you can predict certain outcomes very well.”

For Maersk, the huge global shipping company, when engines break at sea it is a big problem.

“With enough sensors you can predict failures and change pistons while the ship is in port.”

Artificial intelligence (AI) is a popular term these days, but Ratzesberger warned that the intelligence is only as good as the data, citing that old warning: Garbage in, garbage out.”

Chief Data Officers

In a corporation, “Chief Anything” doesn’t amount to much, Ratzesberger said.

“You see Chief Data Offices everywhere; the big new title is Chief AI officer. But
Chief whatevers are powerless offices; they are not Level 1. They are below the CIO or CFO. Many companies lie to themselves when they have a CDO who can’t change anything — it just turned into a blame game…they’ll just blame the CDO. The CEO needs a person who works directly for him and can make decisions [based on data] that may be disruptive. Boards around the world need to challenge the CEO on what they are doing with data, it is often just a check-the-box exercise.”

For company, becoming data-driven is a journey, he added.

“GE is getting it, Siemens knows they have to disrupt themselves. There are new kinds of companies that are based on this — banking, telecom, retailers — are starting to wake up. Technology is pushed by Walmart, they know they need to do things differently, often their tech leadership sits in Silicon Valley. I think most companies get a B- at best. eBay was great; now it is a legacy company. “

“Using data well is a board-level topic — how to build the next generation platform that leverages data at its core.”

Not everything can be based purely on data, he added. People can mis-interpret that data and confuse correlation with causation.

“Companies need to define their strategy and leverage data whenever possible. Data alone won’t make a strategy.”

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Teradata Focuses On Top 500 To Leverage Scarce Resources — Data Scientists, Analysts

Teradata faces a challenge – how to grow a company when a key resource — data scientists and top data analysts — is limited.

Victor Lund, who was named president and CEO of Teradata a year and a half ago, said the company is focused on the top 500 corporations around the world.

“We limit ourselves to 500 companies because we can only deploy X number of people,” explained Lund. Focusing on the largest companies makes sense with Teradata’s capabilities. “We scale better than anyone else, and in real-time analytics that matters. We look at long-term relationships with our customers.”

The company is training its sales force in how to interact with the business users without threatening the IT buyers who have been the company’s usual point of contact. As data, organizing it and making use of it become a topic for the CEO and in many cases the board, the Teradata sales force has to adapt.

“We need to understand how to interface with the business but avoid threatening IT so they don’t think we are driving over them.”

At the company’s annual Partners conference, senior executives briefed reporters and analysts on the company and the growing understanding of the importance of data and analytics.

Data can be used for asset optimization, they said, and this refers to physical assets, not financial. As an example they pointed to Maersk, the shipping company, which has millions of containers. Sensors can show where the containers are, monitor them for changes in temperature or air pressure, and feed a database with all the information — real-world example of the internet of things (IoT). With Teradata firms can analyze anything, display anywhere, buy any way, including pay as you go, and move the data anytime from in-house to cloud at no cost.

Teradata is the only company to use the same code across all deployments, whether AWS, Azure, or on-premise hardware.

The company said its solution is faster and cheaper than a leading competitor’s. One million queries on the competition costs $605,000 and takes nine months, while on Teradata it can run in 10 minutes for $60.

Companies still have a way to go in their use of data, said Rick Farnell, senior vice president at Think Big Analytics, which Teradata acquired in 2014. Fifty-two percent of firms in a survey said they are at a basic level of analytics maturity and 41% of CIOs said data scientists, business intelligence and analytics are among their top skills gaps. Nonetheless, 80 percent are investing in artificial intelligence even though 34% said they don’t have the right in-house skills.

To help companies fill the gap in skills, and to leverage the people skills at Teradata, the company is building accelerators composed of best practices, code, IP, and proven design patterns to help accelerate deployment of AI solutions and ensure quick ROI. They include AnalyticOps Accelerator, which provides an end-to-end framework to facilitate the generation, validation, deployment, and management of deep learning models at scale. This accelerator is available now.

The Financial Crimes Accelerator uses deep learning to detect patterns across retail banking products and channels such as credit card, debit card, online, branch banking, ATM, wire transfer, and call centers. It continuously monitors and thwarts fraudulent schemes used by criminal actors to exploit the system. This accelerator is being deployed in Q4, and will be available more broadly in the first quarter of 2018.

“We’re building capabilities into the product,” said Oliver Ratzesberger, EVP and chief product officer of Teradata.

A recurrent theme at Teradata is around analytics at enterprise scale, not in a lab or running as a proof of concept.

“Companies need to embrace analytics at scale,” said Ratzesberger. “Prepare to disrupt, put outcomes into production at scale. Companies struggle to derive the outcomes they aim for.”

Part of the trouble is finding clean data.

“It comes down to a single source of the truth,” said Rick Farnell, senior vice president, Think Big Analytics. “That’s difficult if you have multiple organizations [with their own data silos] out there. You need to base everything off the right data.”

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