Wallet.AI Aims to Serve Up Location-Based Financial Advice

As reported by MIT Technology Review:  While navigating this increasingly connected world, you leave a trail of data about where you go, what you buy, and who you interact with. If you use a smartphone, this trail intensifies with every tweet and Foursquare check-in.

This may alarm some people, but Omar Green sees it as key to a smarter way to manage finances than a spreadsheet or piece of paper.

Green is founder and CEO of personal finance startup Wallet.AI, which is among a growing number of app makers incorporating so-called 'contextual awareness' into their software. The company is building software that includes a mobile app to sort through your data trail and, combined with insights about your spending habits, offer up timely financial advice. It might range from warning you not to spend more than $20 a day if you want to make rent at the end of the month to, perhaps, nudging you during a daily Starbucks run to get a drip coffee rather than your usual vanilla latte.

Green, who previously worked as director of strategic mobile initiatives for financial software company Intuit and built contextually aware phone software at a previous startup, likens the approach to the quantitative trading methods used by many financial firms; these methods incorporate lots of data to help traders make rational, nonemotional decisions.

“That was one of the ‘ahas’ I had,” Green says. “Let’s think about what it means to build a machine that can do some of this for me.”

With a user’s permission, wallet.AI will gather many kinds of information from the handset’s built-in sensors, and the social networks and financial transactions a user lets it access. Wallet.AI would analyze this data remotely, and distill it into tips it can serve up at specific times and places.

The San Francisco-based company is still keeping many details under wraps, but says it hopes to have a product out in about a year. Green expects this will be sold to financial institutions who can offer it to their clients and, perhaps, to consumers via app stores.

For now, Wallet.AI is focused on building a prototype, which it is testing with a small group of customers. Eventually, he expects to have cloud software chomping on data sets built up by users, determining different insights about their finances. “Anything we can use to help you make better decisions,” Green says.

If Wallet.AI can help, he figures, consumers will be willing to let Wallet.AI track sensitive personal information and glean ambient data from the world around them, and pay for it. The company is likely to face skepticism from some potential customers, though, who are wary of sharing data with yet another service, even if it can mean saving some cash.

So says Rick Oglesby, a payments analyst with Aite Group. He could see Wallet.AI appealing to financial institutions, such as banks, who may be interested in offering it to their customers in the hopes that it will help them stand out from the competition. Even if banks feel comfortable with it, though, it’s not yet known if consumers will want it. “Some people just want to shop and not think about money, but some people want to think about money all the time,” he says.

The Need for Integrated Telematics

Telematics adds increasing value beyond insurance
risk valuation, when used for real-time liability analysis
and driving operational improvement; which can help to
actively decrease accident fraud.

As reported by Actuarial Post: As well as enabling drivers to lower their premiums, data-rich telematics devices offers insurers tremendous potential that extends beyond traditional areas of risk, discounting and pricing. For this reason, many companies are now looking to sophisticated data technologies to become their ‘eyes and ears’ on the ground.

 There is no doubt as to the growing importance of telematics. As the concept of the ‘connected vehicle’ continues to emerge, it is estimated that, by 2025, 600 million cars globally will have embedded telematics. The result will be that vehicles will represent 5% of all connected devices, compared to just 0.1% today.

 As a result, telematics has become a key industry issue, with providers offering a variety of solutions tailored to the insurance market. Yet despite the inevitable hype around the potential benefits to be gained, too many companies remain stifled by a traditional departmental approach to data management, constrained by concerns over legal issues of data ownership, privacy and the cost of data storage.

 Insurers are isolating ‘black box’ telemetry data within data silos and in some cases are not even bringing data in-house, as their goal is simply to establish customer driving scores as the basis of setting commercially-competitive premiums. By focusing on telematics as a way to secure operational improvement, they are missing out on the consequential value which telematics can offer.

 With tools available to enable the business to look at telematics in the broader context of other customer and context data within the business, the time has come to broaden the focus beyond the operational value of better pricing and segmentation.

 Beyond Telematics

 As in other areas of insurance, companies are trying to find out as much information as they can about their customers.In achieving this objective, the advent of telematics means that they can now gain a much clearer perspective on each individual’s behavior behind the wheel, including speeds, braking and other driving habits.

 This is extremely valuable but can only present part of the picture in developing premiums and responding to claims more effectively. Every insurer has a lot of other valuable customer and context data sitting within the business, yet this has remained hidden when making critical judgments around setting premiums and assessing culpability in the event of a claim.

 In responding to this, it is now possible to link telematics data with near-real-time customer behavioral and lifestyle information, images and other contextual data, in order to take into account everything relevant to the interaction with that customer. Technology solutions can bring together telematics data with other relevant information in order to make more informed assessments on all aspects of the customer relationship.

 Traditional data warehousing solutions can be integrated with a discovery platform as part of a unified data architecture. For the first time, this allows the business to access and analyse different data types and styles –multi-structured data – in a way that was simply not possible using data warehousing tools in isolation.

 By putting together a comprehensive picture of individuals and their lifestyles, this enables the insurer to create a more competitive personalized premium which more accurately reflects the level of risk in each case.

 At the same time, the greater analytic value of this approach will also reduce the growing number of fraudulent ‘cash for crash’ claims, for example, by identifying those behaviors which might indicate a higher potential risk. Greater customer insights also enable the creation of more targeted cross-sell and up-sell opportunities, into such areas as life insurance.

 An integrated approach

 Insurance companies now understand the need to make best use of telematics data, in order to maintain and improve their competitiveness. Yet to-date, very few have recognized that the real ‘win’
 here is to be able to analyse this information at a more granular level and in a broader context.

 They typically already hold all this information within the business. The adoption of a robust unified discovery platform takes the business substantially closer to the ideal 360 degree customer view, by pulling together telematics with established customer data, newer behavioral information around how the customer interacts with the business online and other social behaviors. And in so doing, this means that the insurer can achieve a significantly better return on their often substantial telematics investment.

 This broader approach also impacts dramatically on usage-based insurance (UBI) or ‘pay for how you drive’ programs. Again, telematics provides real insights into the behaviors and driving patterns of insured customers, yet leveraging this data in conjunction with non-telematic information delivers much greater benefits.

 For example, in the event of an accident, this enables the business to better assess a customer’s liability for the purposes of settlement and/or litigation. Apportioning liability in claims can be complex, as it is typically based on the statements of the parties involved and those of eyewitnesses, which may not always be objective nor accurately reflect events as they actually occurred.

 Comparing objective telematics data from all the vehicles involved makes allocation of liability much easier, enabling the process to resolved more quickly and efficiently. Yet by adding the ability to query traditional claims, policy information and weather and traffic conditions at the same time, this would go much further in presenting a complete picture of the circumstances around the claim.

 Determination of liability could be made solely by running a query, avoiding the time and expense of taking statements. By cutting expenses and resolving claims more quickly, the cost of settlements would be reduced and customer satisfaction levels raised.

 Benefits for all

 The race is on for insurers to get the most from the rich vein of data telematics offers, in order to make the most effective and informed decisions. Yet as in many other aspects of the business, this can only truly be achieved through moving away from yesterday’s silos to a more transparent centralized view of all aspects of the customer journey.

 By incorporating telematics within a broader unified delivery platform, the insurer can increase retention rates, improve operational efficiencies and cut fraud, while the customer benefits from a faster, more personalized response to claims and other interactions with the business. Everybody wins.

Left-hand Turns Can Cost You

As reported through Yahoo! News: With a delivery fleet of 96,173 package cars, vans, tractors, and motorcycles, the United Parcel Service or UPS knows a great deal about efficient driving.

WAGA Fox 5 News interviewed UPS dispatch supervisor Matthew Frost to learn about some of the Fortune 500 company’s driving tips. Matthew said, “A lot of the managers here and supervisors here, they train their kids when they get of driving age and they train them the same way that we train our drivers here to keep ‘em safe.

Because these are proven methods that work.” After 6 years behind the wheel of a brown truck, Matthew now helps plan out the drivers’ routes. “When we design routes, as we put them together, we want to try to design it where the drivers are taking a right-hand turn as many as possible.” The company has found that right-hand turns are not only safer, but they’re also more efficient. It’s a tip that AAA agrees with. By using routing technology and avoiding idling at lights for left-hand turns, UPS was able to avoid 98 million minutes of idle time in a year; an estimated fuel savings of about $980,000 per year.

Other tips by the delivery giant include leaving at least one car length between you and the car stopped ahead of you to allow for reaction time. They advise using your eyes to scan the road and your mirrors. The dispatch supervisor said, “We train our drivers to check a mirror every five to eight seconds. Then check back to the front, then check another mirror, back to the front.” In addition to all of that, the drivers are given training drills to keep their minds sharp.

Matthew told WAGA that UPS has, "110,000 drivers. We log 3 billion miles a year and we average less than one accident per 1 million miles." That safe driving record is enforced with drivers undergoing 1 week of the company’s training after which they are allowed to get behind the wheel of a truck.

UPS is proud of their Circle of Honor club with 6,400 drivers who all have 25 years or more of safe driving.

How Nissan Will Roll Out Self-Driving Cars: Fricking Lasers

As reported by ReadWrite: It was an improbably futuristic scene: A man standing on a sunbaked tarmac in Irvine, Calif., next to a Nissan Leaf electric car, pushed a button on the hatchback’s key fob. The Leaf, unassisted by human intervention or preprogrammed maps, crawled at about five miles per hour through rows of parked vehicles, detected an SUV pulling out of a space, paused, and allowed the SUV to pull away. Then it moved past the now-vacated parking spot, slowed into position, glided back into the space, and powered down.

A moment later, the man pushed the button again, and the Leaf fetched itself, reversing its previous steps, and returned to the man’s side.

This isn't science fiction. I watched this all myself, dumbfounded, just a little over a week ago.

Was this self-parking demonstration a bit of razzle-dazzle that will never make it into the vehicles in dealer lots? Maybe not.

To witness this scene, I drove 45 miles in a 2014 Infiniti Q50 sedan from LAX to the decommissioned El Toro Marine Corps Air Station. (That's where Nissan held its month-long Nissan 360 technology showcase.) The Q50 was equipped with the luxury car’s $3,200 tech package , which pushes the nicely appointed vehicle’s price over $50,000.

The relevant features of the teched-up Q50 are Intelligent Cruise Control and Active Lane Control. The technology allowed me to travel at highway speeds along short, straight stretches of the 405 and the 5, with my foot off the pedals and my hands at my side.

Take that, Google! The search engine is investing an unknown amount in self-driving cars, and those prototypes have driven millions of miles. Google promises to offer the technology to consumers by 2018, but the Q50 is on sale today.

Proto-Automation

The Q50’s camera located in front of the rearview mirror, along with its image-processing system, can read lines and dashes on the roadway.  When the vehicle gets close to the white paint separating lanes, the car gently nudges the steering wheel in the direction of safety.  But here’s a problem that I experienced: When the car approached the white line to the left, it overcorrected, sending me across the lane to the right-side boundary, where the camera and computer nudged me back again across the lane to the left line.  With my hands off the steering wheel, the Q50 became a careening, 3,500-pound ping-pong ball. 

In fairness, the visual guidance technology in the Q50 is not meant to fully automate driving.  It’s intended to play an assist role, which according to Infiniti—Nissan’s upscale division—reduces driver fatigue and otherwise enhances the vehicle’s luxury feel. It worked as intended.

Similarly, the Q50’s Forward Assist technology was effective.  Set the cruise control to, say, 65 miles per hour, and lift your foot off the accelerator.  That’s plain ol’ cruise control, right?  But thanks to a radar system behind the front bumper, the car can detect the speed of cars ahead in the same lane, and automatically slow down the Q50 to match their pace—all the way down to a complete stop, only to resume acceleration when the car ahead gets going. This is an increasingly common automotive feature, usually called adaptive cruise control.  A related safety feature rapidly and automatically applies brakes when the vehicle in front comes to a screeching halt.

Driving Back to the Future

These early manifestations of autonomous driving technologies already seem unremarkable.  But what’s surprising is that the fully automated Leaf on display in Irvine uses the same exact camera, image-processing technology, and radar found in the Q50.

“To find objects that are approaching from far away very fast, radar is the best technology,” explained Tetsuya Iijima, general manager of intelligent transportation systems engineering at Nissan. “But unlike the driver-assisting features on the Q50, fully automated technology can’t make any excuses to the customer.”
So Iijima and his team of engineers employ more serious automagical mojo: six laser scanners that surround the car.  And not just the fixed broad-beam or one-dimensional lasers already used in auto-safety systems from Continental and other suppliers. These are three-dimensional ones that scan left, right, up, and down, to make a full spatial rendering of all road objects on the fly.  Three radars are still used, one in front and two in back, as well as five cameras that can read speed-limit signs (to modulate speed according to the highway rules) and the color of traffic signals (to know when to stop and go at an intersection). 

Add 12 sonars, and you now have a Leaf electric car that can travel autonomously and safely on highways—and do that cool robotic-parking trick as well.  Iijima demonstrated those two feats in two separate vehicles—each equipped with precisely the same hardware, but programmed for either highway travel or automated parking.  Nissan executives said that these automated features will go on sale in 2020—and will become available a few years later in a wide range of models.

The Secret Sauce: Fricking Laser Scanners

Several carmakers already offer features similar to the ones available in the Infiniti Q50, and are making claims about fully automated driving coming in the not-too-distant future—although most do not give timetables.

The reason Nissan thinks it can set a date is that it has committed to laser technology.
“We believe that we are leading this technology," said Iijima. "Other companies still have not decided to use a laser scanner. We have come to the conclusion that laser scanners are required. The image is a regular three-dimensional picture. Each point has depth information.”

The Google car uses a relatively large roof-mounted LIDAR system, using 64 lasers in a spinning 360-degree turret to create a high-resolution map accurate to about 11 centimeters, according to Popular Science.   The autonomous Leaf embeds six fixed laser scanners—around the car in corner body panels and into rear-passenger doors—each one providing resolution to 1 centimeter, according to Nissan.

Iijima declined to identify the companies that Nissan is considering to supply the three-dimensional laser hardware or what it might cost. Nissan is developing its own software that filters all the various inputs, and integrates the data into steering-wheel position, acceleration levels, and braking. It’s Big Data on wheels. The intricate integration of hardware and software will take an alliance of companies, according to Iijima.

But Nissan has ruled out one type of technology, at least for the next few years—intelligent GPS-based geographical mapping, in the vein of Google Maps or Nokia’s Here. The info gathered from those mapping services is not detailed enough, according to Iijima. Also forget vehicle-to-vehicle or vehicle-to-infrastructure communications that will take decades to penetrate across enough cars and roadways to become useful.

The cool self-parking car, unlike similar systems unveiled from Audi and Volvo, does not require GPS or any sensors or transmitters applied to the pavement.  Instead, as Iijima believes, vehicle automation should work with on-board sensors.  (Nonetheless, Nissan is working on a parallel development using precise maps that will enable cars to run autonomously in more challenging city environments.)  For now, Nissan is only talking about tackling the simpler challenge of highway driving and automated parking.

The Beginning Of The End Of Driving

Iijima outlined some limitations to the system: a max speed of 80 miles per hour and difficulty in extreme weather conditions, like a snowstorm.  He said that his work now focused on increasing processing power, reducing cost, and shrinking the size of the hardware that currently occupies the entire hatch space—down to about the size of a shoebox that could fit into the engine compartment.

The software, which Nissan developed in-house with unnamed partners, is not unusual.

“It’s C++,” Iijima said with a chuckle.  And ironically, the most important required infrastructure is … white paint.  “The white line defines the road,” he said.  “It’s minimal infrastructure.”

What’s at stake with this program?  Big stuff. The promise of zero fatalities.  The ability for elderly and disabled people to gain mobility.  More efficient use of fuel and roadways.  And nothing less than a complete transformation of the relationship between car and driver.

“When the driver is no longer necessary, there is no need for cars to be owned by individuals,” he said. He envisions a world of shared autonomous mobility robots roaming global roadways by 2030.  Yet, there’s no single finish line set to be crossed in the distant future, but rather a slow and steady supplanting of human drivers by onboard computers, cameras, radar, sonar and lasers.

80% of Location Data in Top Mobile Ad Exchanges is Inaccurate

As reported by GPS Business News: Location-powered ad exchange Verve has published last week a new report where it brings together key findings of its location-based advertising campaigns.

According to them 80 percent of lat/long ad requests found today in major ad exchanges are rubbish and made out of lesser quality data such as Geo-IP or ZIP code in an attempt by publishers to make bigger revenue out of their - poor quality - 'inventory'.

In a comparative test campaign Verve experienced a Clock-Through-Rate of 1.04% with verified location data versus 0.23% with unverified location data.

Other key findings from the report include:

- Retail is the number one category utilizing location powered advertising. The top three types of retailers using location powered advertising are big box, consumer electronics, and department stores.

 - Geo-fencing, which includes geo-conquesting, is the number one most utilized location targeting strategy deployed by retailers. 

- Driving foot traffic to stores is the number one objective for retailers leveraging location-based mobile advertising. 

- For retailers, proximity impacts mobile ad performance, the sweet spot for ads served being between 1 and 6 miles.

FDA to Focus on Apps That Turn Smartphones Into Medical Devices

A MIM Software app that allows doctors to view X-rays
and MRIs on smartphones and tablets was one of
the first to win FDA approval. (MIM Software photo / September 23, 2013)

As reported by Reuters: The Food and Drug Administration said Monday that it will focus on mobile medical apps that have the potential to harm consumers if they do not function properly.

The FDA, which issued final rules on the apps Monday, has cleared about 100 over the past decade, including products that can diagnose abnormal heart rhythms or help patients monitor their blood sugar. About 40 were cleared within the past two years.

The agency said it will not regulate the sale or general consumer use of smartphones or tablets or mobile app distributors such as the iTunes store or Google Play store.

It will, however, focus enforcement on products that transform smartphones into devices the agency currently regulates, such as electrocardiography machines that can determine whether a patient is having a heart attack.

The FDA will also focus on apps that would be used as an accessory to a regulated device, such as one that displays images used by physicians to make specific diagnoses. 

Google Adds Remote Lock and Password Reset Features to Android Device Manager

As reported by the Verge: Android users can now remotely lock down a misplaced or stolen device from the web. Google has rolled this critical feature into Android Device Manager, which launched last month with location tracking and remote wipe functionality. Now the web tool lets you lock any Android smartphone running version 2.2 of the operating system and above.

To do so, you'll simply need to set a new password to be entered once the device is recovered. This can be different from your regular lock screen PIN, so even if that password is compromised, you can override it with a new one.

Google is actively discouraging users from re-using their main Google credentials, however.

A lock request will immediately secure any device connected to Wi-Fi or a cellular network — even if it's actively being used. 

If a thief has turned off a phone or enabled Airplane Mode, the lock will take effect as soon as a data connection is reestablished. And should your beloved smartphone prove unretrievable, there's always the last-ditch measure of wiping its memory entirely.