All posts in “Europe”

Health insurance startup Alan covers meditation app subscription

French startup Alan wants to be a bit better than your good old health insurance. That’s why the company is trying something new and now covers part of your Petit Bambou subscription.

Petit Bambou is a popular meditation app. It’s a sort of Headspace, but with French content. You download an app, put your earphones, close your eyes and follow the instructions. Meditating ten or twenty minutes every day should help you feel better after a while.

The basic course is free and you need to pay a subscription to access more content. It costs €7 per month or €60 per year.

In France, health insurance companies usually cover your bills when the national healthcare system already pays for part of the bill.

For instance, if you get X-Rays for your arm, the national healthcare system will pay for part of the bill, and your health insurance will cover the rest. Usually, if something is not covered by the national healthcare system, your insurance company won’t cover it either.

But Alan wants to differentiate its offering and add more stuff. The Petit Bambou offering is just a test for now. You can get €25 back if you subscribe for six months or a year. It only works once. But Alan is thinking about turning it into a recurring offer if people like the feature.

N26 faces criticism regarding its identification processes

Fintech startup N26 is growing quite rapidly. Building a startup is hard, but building a startup that manages your bank account is even harder given the increased scrutiny. German weekly magazine Wirtschaftswoche published an article that questioned N26’s identification processes. According to Wirtschaftswoche, it’s quite easy to create an account with a fake ID document.

“One or two people got through with a fake ID document. And we detected that afterward. Unfortunately, we didn’t detect it in real time,” co-founder and CEO Valentin Stalf told me. “Unfortunately, it can happen.”

But Stalf also insisted that it’s not a widespread problem and that all banks face the same issue. According to him, N26 complies with all regulations when it comes to onboarding.

Currently, N26 has three different procedures depending on the country and works with a third-party company called SafeNed for some of the verification procedures.

In many countries, you can initiate a video call with someone so that they can check your ID and compare it with your face. In Germany, you can also print a document, go to the post office with an ID document and make a post employee check that you are actually you.

In some countries, you can open an N26 account by uploading a photo of your ID document and a selfie. Other banks also take advantage of this procedure. For instance, it’s a common process in the U.K.

More generally, other banks also have to deal with fake ID documents. But security is never perfect. That’s why you can’t simply eradicate the issue. You can try to keep the fake ID rate as low as possible.

“Security is our top priority at N26, which is why secure identification processes and constant review of our security and monitoring mechanisms to prevent identity theft are of great importance to the company,” the company told me in a statement.

In other words, N26 monitors this fake ID rate. And N26 also has ongoing transaction monitoring for those who have already opened a bank account. The company tries to detect fraudulent activity as quickly as possible.

You might think that uploading a photo of your ID document leads to more fraudulent activity. But N26 has noticed that there’s a higher fraud rate for customers who go to the post office to check their ID document.

So fraud is nothing new in the banking industry. Nobody has eradicated fraud, and nobody will. In fact, many startups (such as DreamQuark) are working on improving fraud detection using machine learning and more sophisticated processes. But even artificial intelligence won’t solve this problem altogether.

All eyes are on N26 because it’s the hot new thing. But if you look at what’s happening, it’s a pretty boring story. “In one of the articles they said we used weaker method to grow faster. This is complete bullshit,” Stalf told me.

This story is a great example that it can be tough to manage your startup’s reputation. Building trust takes a long time. But it can go away much more quickly. That might be why N26 debunked the issue so intensely.

Here’s N26’s full statement:

Security is our top priority at N26, which is why secure identification processes and constant review of our security and monitoring mechanisms to prevent identity theft are of great importance to the company.

After the customer’s identity is verified, we carry out ongoing transaction monitoring along with numerous other security measures, in a bid to prevent criminal activity such as money laundering and terrorist financing.

We therefore take the findings put forward by Wirtschaftswoche very seriously, will analyse the facts and take appropriate measures if necessary.

Contrary to the statement in Wirtschaftswoche, the use of photo verification by N26 is legally compliant. N26 works with a regulated payment service provider, SafeNed, in this regard. SafeNed is a UK business which is authorised and regulated by the UK Financial Conduct Authority (FCA) with regards to the prevention of money laundering and terrorist financing. SafeNed verifies its customers using the Photo Ident process, which is compliant with UK law.

According to the German Money Laundering Act, N26 is allowed to use a third party regulated in the EU, in this case a payment service provider in the UK, for the verification of customers (Section 17 (1) GwG). The respective verification procedure is then determined by the law applicable to the third party (in the above example, therefore, by UK law). This understanding is also confirmed by BaFin in its interpretation and application notes on the German Money Laundering Act (p. 67 et seq.) for customers not resident in Germany.

Crypto Quantique unveils its ‘quantum driven secure chip’ for IoT devices

With Gartner estimating that there will be 150 billion connected devices by 2030 — many of them mission critical, such as powering major national infrastructure — the risk and realisation that these devices aren’t secured properly is leading some cyber security experts to predict that there is a large-scale disaster waiting to happen. And the problem is only getting worse. By some estimates, on average there are 127 new devices connected to the internet every second.

Enter: Crypto Quantique, a startup out of company builder Entrepreneur First that has been patiently toiling away for the last couple of years trying to solve the IoT security problem. Specifically, the company has developed what it claims is “the world’s first quantum driven secure chip (QDSC)” on silicon, which, when combined with cryptographic APIs, it says is capable of providing any connected device with a scalable and easy to implement “end-to-end” security solution.

Moreover, by employing advanced techniques in cryptography and quantum physics, its makers say the Crypto Quantique QDSC is unique to every device and entirely unclonable, which makes it almost impossible to hack. That’s quite a claim.

“There are security complexities in IoT, many stakeholders, including OEMs, manufacturers, integrators and designers are involved in developing and implementing the IoT,” Shahram Mossayebi, co-founder of Crypto Quantique, told me over email. “Each stakeholder is faced with different threat vectors and thus has different security requirements and produces devices based on very different architectures. Currently there is no clear approach to securing the IoT, which is also impacted by the lack of basic security tools that would allow stakeholders to build their own security solutions”.

To that end, he explained that security must start from the device, then travel through the network and finally reach the IoT device’s backend services. In other words, proper end-to-end security is required to protect IoT devices and infrastructure.

At the heart of this is “root of trust” — the ability for a device to authenticate itself and be a trusted member of a network — which, conversely, is also the weakest link. Data traveling throughout the network also needs strong encryption, of course. Finally, with IoT devices being in the billions, there’s an issue of cost: any secure solution can’t be prohibitively expensive to implement on a per device basis or be fragmented across multiple third-party providers.

“We have created a root-of-trust by harnessing quantum processes in semiconductors to generate unique, unclonable and tamper evident cryptographic keys,” says Mossayebi. “We call it quantum driven secure chip (QDSC) and it is the first ever of its kind in the world. Because of the uniqueness and way in which the keys are generated there is no requirement to store the keys on the device because the keys can be retrieved on demand. This eliminates secure storage requirements and leakage of sensitive information.

“In addition to building the QDSC, we also provide the cryptographic APIs and manage the end to end security to remove the multiple parties involved in the security chain and provide an all-in-one solution. This means there are no ‘open windows’ in connectivity when it comes to security. Once a QDSC is placed in a device it links directly to the owner system (i.e. public or private cloud) through CQ’s cryptographic APIs, where it is managed automatically and remotely while the device is in the field. This is the most advanced security product for the IoT, enabling new industrial revolutions such as Industry 4.0”.

As I said, big (and very interesting) claims, indeed.

On that note, Mossayebi says Crypto Quantique is aimed at any connected device that needs to stay secure, from traffic lights to a SCADA machine used in critical infrastructure. “Currently, we are working with leaders in different fields such as defence, aerospace, energy, industrial IoT manufacturers and enterprise hardware appliance manufacturers. The applications vary from securing satellites and drones to securing energy grids, sensors in critical infrastructure and data centres,” he says.

Azimo launches business money transfer service

Hot on the heels of raising $20 million in Series C funding led by Japan’s Rakuten Capital, London-based money transfer service Azimo is launching a new service aimed at small and medium-sized businesses.

Dubbed “Azimo Business,” it lets SMEs across the U.K. and Europe send payments to an impressive 189 countries — including many emerging markets, which is Azimo’s traditional focus — and at a price the company claims undercuts banks by 50 percent or more.

The idea isn’t just to beat the banks on fees (which is often not hard to do) but also through better technology, delivering faster transfers and a smoother UX via the Azimo mobile apps and web versions.

In a brief call, Azimo co-founder and CEO Michael Kent told me that a fully fledged business version of Azimo was something that many of the company’s existing customers had been asking for as they wanted to expand their use of the money transfer service to the small businesses they operate, not just for sending money to family and friends in their original home country.

He also (rightly) noted that immigrants are much more likely to start their own business compared to native nationals, and that these micro and small businesses are often international in nature, such as importing or exporting specialist goods. This requires a significant amount of money transfer and exchange for things like paying suppliers and paying local salaries.

To that end, even though Azimo Business runs on the same rails as Azimo’s existing consumer service, Kent explained that there are additional regulatory requirements around anti-money laundering. This sees business users having to pass KYC and KYB checks, with Azimo ultimately needing to satisfy the regulator that it knows the beneficial owner of a business sending money.

However, the Azimo founder says that required building technology and processes to scale those checks but in a way that doesn’t expose Azimo to regulatory risk or creates too many false positives that would decline customers unnecessarily.

Meanwhile (and proof that there was pent-up demand), while running in beta, Azimo Business customers on average sent six times more money than Azimo’s consumer customers. The most popular sending countries were the U.K., Germany, the Netherlands, Spain and France. The most popular receiving countries were Poland, China, Singapore, Pakistan, Hong-Kong, and South Africa

Applied gets $2M to make hiring fairer — using algorithms, not AI

London-based startup Applied has bagged £1.5M (~$2M) in seed funding for a fresh, diversity-sensitive approach to recruitment that deconstructs and reworks the traditional CV-bound process, drawing on behavioural science to level the playing field and help employers fill vacancies with skilled candidates they might otherwise have overlooked.

Fairer hiring is the pitch. “If you’re hiring for a product lead, for example, it’s true that loads and loads of product leads are straight, white men with beards. How do we get people to see well what is it actually that this job entails?” founder and CEO Kate Glazebrook tells us. “It might actually be the case that if I don’t know any of the demographic background I discover somebody who I would have otherwise overlooked.”

Applied launched its software as a service recruitment platform in 2016, and Glazebrook says so far it’s been used by more than 55 employers to recruit candidates for more than 2,000 jobs. While more than 50,000 candidates have applied via Applied to date.

The employers themselves are also a diverse bunch, not just the usual suspects from the charitable sector, with both public and private sector organizations, small and large, and from a range of industries, from book publishing to construction, signed up to Applied’s approach. “We’ve been pleased to see it’s not just the sort of thing that the kind of employers you would expect to care about care about,” says Glazebrook.

Applied’s own investor Blackbird Ventures, which is leading the seed round, is another customer — and ended up turning one investment associate vacancy, advertised via the platform, into two roles — hiring both an ethnic minority woman and a man with a startup background as a result of “not focusing on did they have the traditional profile we were expecting”, says Glazebrook.

“They discovered these people were fantastic and had the skills — just a really different set of background characteristics than they were expecting,” she adds.

Other investors in the seed include Skip Capital, Angel Academe, Giant Leap and Impact Generation Partners, plus some unnamed angels. Prior investors include the entity Applied was originally spun out of (Behavioural Insights Team, a “social purpose company” jointly owned by the UK government, innovation charity Nesta, and its own employees), as well as gender advocate and businesswoman Carol Schwartz, and Wharton Professor Adam Grant.

Applied’s approach to recruitment employs plenty of algorithms — including for scoring candidates (its process involves chunking up applications and also getting candidates to answer questions that reflect “what a day in the job actually looks like”), and also anonymizing applications to further strip away bias risks, presenting the numbered candidates in a random order too.

But it does not involve any AI-based matching. If you want to make hiring fairer, AI doesn’t look like a great fit. Last week, for example, Reuters reported how in 2014 ecommerce giant Amazon built and then later scrapped a machine learning based recruitment tool, after it failed to rate candidates in a gender-neutral way — apparently reflecting wider industry biases.

“We’re really clear that we don’t do AI,” says Glazebrook. “We don’t fall into the traps that [companies like] Amazon did. Because it’s not that we’re parsing existing data-sets and saying ‘this is what you hired for last time so we’ll match candidates to that’. That’s exactly where you get this problem of replication of bias. So what we’ve done instead is say ‘actually what we should do is change what you see and how you see it so that you’re only focusing on the things that really matter’.

“So that levels the playing field for all candidates. All candidates are assessed on the basis of their skill, not whether or not they fit the historic profile of people you’ve previously hired. We avoid a lot of those pitfalls because we’re not doing AI-based or algorithmic hiring — we’re doing algorithms that reshape the information you see, not the prediction that you have to arrive at.”

In practice this means Applied must and does take over the entire recruitment process, including writing the job spec itself — to remove things like gendered language which could introduce bias into the process — and slicing and dicing the application process to be able to score and compare candidates and fill in any missing bits of data via role-specific skills tests.

Its approach can be thought of as entirely deconstructing the CV — to not just remove extraneous details and bits of information which can bias the process (such as names, education institutions attended, hobbies etc) but also to actively harvest data on the skills being sought, with employers using the platform to set tests to measure capacities and capabilities they’re after.

“We manage the hiring process right from the design of an inclusive job description, right through to the point of making a hiring decision and all of the selection that happens beneath that,” says Glazebrook. “So we use over 30 behavioural science nudges throughout the process to try and improve conversion and inclusivity — so that includes everything from removal of gendered language in jobs descriptions to anonymization of applications to testing candidates on job preview based assessments, rather than based on their CVs.”

“We also help people to run more evidence-based structured interviews and then make the hiring decision,” she adds. “From a behavioral science standpoint I guess our USP is we’ve redesigned the shortlisting process.”

The platform also provides jobseekers with greater visibility into the assessment process by providing them with feedback — “so candidates get to see where their strengths and weaknesses were” — so it’s not simply creating a new recruitment blackbox process that keeps people in the dark about the assessments being made about them. Which is important from an algorithmic accountability point of view, even without any AI involved because vanilla algorithms can still sum up to dumb decisions.

From the outside looking in, Applied’s approach might sound highly manual and high maintenance, given how necessarily involved the platform is in each and every hire, but Glazebrook says in fact it’s “all been baked into the tech” — so the platform takes the strain of the restructuring by automating the hand-holding involved in debiasing job ads and judgements, letting employers self-serve to step them through a reconstructed recruitment process.

“From the job description design, for example, there are eight different characteristics that are automatically picked out, so it’s all self-serve stuff,” explains Glazebrook, noting that the platform will do things like automatically flag words to watch out for in job descriptions or the length of the job ad itself.

“All with that totally automated. And client self-serve as well, so they use a library of questions — saying I’m looking for this particular skill-set and we can say well if you look through the library we’ll find you some questions which have worked well for testing that skill set before.”

“They do all of the assessment themselves, through the platform, so it’s basically like saying rather than having your recruiting team sifting through paper forms of CVs, we have them online scoring candidates through this redesigned process,” she adds.

Employers themselves need to commit to a new way of doing things, of course. Though Applied’s claim is that ultimately a fairer approach also saves time, as well as delivering great hires.

“In many ways, one of the things that we’ve discovered through many customers is that it’s actually saved them loads of time because the shortlisting process is devised in a way that it previously hasn’t been and more importantly they have data and reporting that they’ve never previously had,” she says. “So they now know, through the platform, which of the seven places that they placed the job actually found them the highest quality candidates and also found people who were from more diverse backgrounds because we could automatically pull the data.”

Applied ran its own comparative study of its reshaped process vs a traditional sifting of CVs and Glazebrook says it discovered “statistically significant differences” in the resulting candidate choices — claiming that over half of the pool of 700+ candidates “wouldn’t have got the job if we’d been looking at their CVs”.

They also looked at the differences between the choices made in the study and also found statistically significant differences “particularly in educational and economic background” — “so we were diversifying the people we were hiring by those metrics”.

“We also saw directional evidence around improvements in diversity on disability status and ethnicity,” she adds. “And some interesting stuff around gender as well.”

Applied wants to go further on the proof front, and Glazebrook says it is now automatically collecting performance data while candidates are on the job — “so that we can do an even better job of proving here is a person that you hired and you did a really good job of identifying the skill-sets that they are proving they have when they’re on the job”.

She says it will be feeding this intel back into the platform — “to build a better feedback loop the next time you’re looking to hire that particular role”.

“At the moment, what is astonishing, is that most HR departments 1) have terrible data anyway to answer these important questions, and 2) to the extent they have them they don’t pair those data sets in a way that allows them to prove — so they don’t know ‘did we hire them because of X or Y’ and ‘did that help us to actually replicate what was working well and jettison what wasn’t’,” she adds.

The seed funding will go on further developing these sorts of data science predictions, and also on updates to Applied’s gendered language tool and inclusive job description tool — as well as on sales and marketing to generally grow the business.

Commenting on the funding in a statement, Nick Crocker, general partner at Blackbird Ventures said: “Our mission is to find the most ambitious founders, and support them through every stage of their company journey. Kate and the team blew us away with the depth of their insight, the thoughtfulness of their product, and a mission that we’re obsessed with.”

In another supporting statement, Owain Service, CEO of BI Ventures, added: “Applied uses the latest behavioural science research to help companies find the best talent. We ourselves have recruited over 130 people through the platform. This investment represents an exciting next step to supporting more organisations to remove bias from their recruitment processes, in exactly the same way that we do.”