The Simility Blog
Going Mobile: How Businesses Can Meet Customer Demands While Keeping Fraud At Bay

Jayan Tharayil
December 03, 2019The mobile economy is surging. In the US alone, retail sales via mobile devices are predicted to soar from just over a third of all e-commerce sales (34.5%) in 2017 to reach over half (53.9%) by 2021, according to Statista.1 Yet as customers increasingly demand more seamless omnichannel experiences allowing them to jump between multiple devices, fraudsters are also exploiting new opportunities. For businesses keen to drive customer loyalty and profits, there’s too often a trade-off between lower fraud losses and more customer friction – or vice versa.
In reality, both losses and user friction can be minimized with the right approach, centered around smart, data-centric platforms capable of adapting to changing fraud patterns and spotting scams no matter what channel is used for attacks.
A Portal For Our Digital Lives
We are spending more and more of our waking lives online, and it’s the mobile device that is the gatekeeper to this digital world. It’s the last thing we check before turning the lights out at night and the first thing we look at in the morning. There are an estimated 265 million smartphone users in the US – over 80% of the current population – and the figure is set to rise further to reach 285 million by 2023, according to Statista.2
We use our mobiles to message friends, share photos and stories, post status updates, shop and research goods, do online banking, and even consult our local clinician. We’re also using multiple devices to do so – flicking effortlessly from our smartphones to tablets, laptops and home PCs. Mobiles are increasingly being used to open credit card (21%) and checking accounts (26%), according to Javelin Strategy & Research.3 In the world of mCommerce, soaring rates of mobile usage have given rise to a new era of omnichannel retail, where stores offer seamless shopping experiences across bricks and mortar and online channels – including buy online, pick-up in-store (BOPIS).
A New Target, A New Solution
Yet, as the door to our digital lives, mobile devices have inevitably become a popular target for online fraudsters. They have worked out that, by compromising a user’s mobile phone account, they could intercept the one-time passcode messages sent out by a range of online providers to offer secure access to accounts.
In 2018, 17% of account takeover victims had their mobile phone account hijacked, compared with 10% in 2017, with the number of victims nearly doubling each year since 2015, according to Javelin.4 Mobile wallet fraud rose from 10% to 14% from 2017-2018, while new account fraud via mobile channels also increased, by around 60% from 2017 to 2018.
Organizations must improve their authentication security to more robust measures than passwords, security questions, and SMS one-time passwords. But for more holistic protection against mobile-related fraud, they need to empower teams with improved decisioning tools.
Simility’s Adaptive Decisioning Platform is one such offering. Fraudsters are adept at masking the true characteristics of their mobile devices in order to impersonate legitimate customers. But Simility’s Device Recon feature sees through these attempts, analyzing hundreds of mobile and desktop device characteristics and behaviors to fingerprint devices. We then apply machine learning models for risk scoring and similarity clustering for extra insight.
It’s all part of our unique approach, which takes in a large volume and variety of data, allows risk teams to quickly write and test manual rules in plain English, and applies machine learning to those rules to help spot suspicious patterns of behavior. Not only does this enable organizations to adapt to changing fraud patterns, but it also helps protect businesses across channels.
To learn more about how Simility’s Adaptive Decisioning Platform can help protect businesses across channels, schedule a demo now.
1. Statista, https://www.statista.com/statistics/249863/us-mobile-retail-commerce-sales-as-percentage-of-e-commerce-sales/
2. Statista, https://www.statista.com/statistics/201182/forecast-of-smartphone-users-in-the-us/
3. Javelin, 2019 IDENTITY FRAUD STUDY: Fraudsters seek new targets and victims bear the brunt, https://www.javelinstrategy.com/coverage-area/2019-identity-fraud-study-fraudsters-seek-new-targets-and-victims-bear-brunt
4. Javelin, 2019 IDENTITY FRAUD STUDY: Fraudsters seek new targets and victims bear the brunt, https://www.javelinstrategy.com/coverage-area/2019-identity-fraud-study-fraudsters-seek-new-targets-and-victims-bear-brunt