Three top banks employ Deep Labs’ platform to differentiate between transactions that are anomalies and those that are fraud.
Financial institutions are fighting the wrong war when it comes to credit card fraud, said Scott Edington, CEO of San Francisco-based Deep Labs.
Fraudulent transactions are expected to total $32 billion worldwide in 2019, according to Nilson. But banks should be paying more attention to false positive declines, Edington said.
False declines — payment-card transactions that are incorrectly flagged and canceled — led to losses of $331 billion globally in 2018, said Edington, citing a study by research and advisory firm Aite Group.
We’ve seen many new fraud and authentication techniques and point solution providers enter the market over the past several years, but have we really made any improvement against fraud, particularly in the financial institution space? Apparently not.
Account opening fraud
Account opening fraud is a rapidly increasing challenge for issuers due to the plethora of identity data available to fraudsters. The 2018 Identity Fraud Study by Javelin Strategy & Research shows that the number of identity fraud victims increased by eight percent in 2017, with the amount stolen totaling US$ 16.8 billion (£13.4 billion).
Account takeover fraud
Account takeover, where a fraudster gains access to a victim’s account, typically leads to unauthorised fraudulent transactions. Account takeover fraud (ATO) is still trending upward, especially in the financial services sector. According to Javelin, existing account takeover fraud tripled in 2018 to 1.5 percent of all US-based consumers.
Key gaps in the fraud ecosystem
Some of the top financial institutions employ specific and often expensive point solution providers for device risk, behavioural risk, mobile phone intelligence, social reputation, email reputation, call centre fraud defence, bot and malware detection. And each of these providers typically provides a risk score or a rules-based approach, and a potentially long list of data attributes.
But this approach creates an issue and an opportunity. It isn’t necessarily a bad investment to add new point solution or data providers as long as you are getting value out of these investments. However, that is often the hardest determination to make.
Learn how A.I., and more specifically true machine intelligence, can maximize the value of your existing data signals, reduce cost and minimize latency, while making more accurate risk and fraud decisions.
Written By Michael Lynch, Chief Strategy and Product Officer, Deep Labs
Service providers, consumers, and businesses are all impacted by telecom fraudsters. In fact, in 2017, the Communications Fraud Control Association (CFCA) estimated $29 billion is lost by carriers and organizations to global network fraud.
Telecom scammers and hackers are a constant threat to providers, whether it’s PBX hacking for revenue sharing fraud or call sharing fraud, or denial of service attacks, for example. They also target the consumers themselves, attempting to get access to their information for a variety of crimes. A popular scenario is when they pose as legitimate callers to banks to perform account takeovers, by leveraging techniques such as caller ID spoofing.
Whether it’s telecom, retail, or the financial verticals, fraudsters and hackers always seem to move much faster than those responsible for mitigating fraud. New, unforeseen threats need to be prevented rather than detected after the fact, which is the perfect use case for artificial intelligence, and more specifically true machine intelligence.
Organizations need new fraud prevention strategies based on artificial intelligence.
It will become more and more important to analyze data available from multiple channels, and only artificial intelligence will be able to provide the necessary key insights on behavior through billions of calculations, iterative insights, and process analytics.
EPSM, a European payment services industry group, has called for a minimum 18-month delay to the introduction of Strong Customer Authentication (SCA) rules under PSD2 – just eight weeks ahead of a looming deadline for implementation.
In a desperate plea to regulators for an extension, the 67-member organisation, whose members provide a range of payment services to merchants, warned of “significant market disruptions” and “a disaster for consumers and PSPs [payment service providers]” without a grace period for industry to get its house in order.
“EPSM recommends that additional timeframes of 18 months for standard applications and up to 36 months for challenging applications, (e.g. in the travel and hospitality sector) across all regions should be agreed in a harmonised migration approach” the lobby group said, warning of business disruption risks without flexibility.
According to Mobile Payments Today, as the mid-September deadline draws closer for a major transition of customer authentication rules for ecommerce transactions in Europe, a growing number of voices are seeking a pause to prevent what they fear could be a logistical nightmare for merchants, banks, payment processors and consumers.
The issue involves the transition to Secure Customer Authentication, a move by European regulators under what is called the second Payment Services Directive (PSD2) to lower the risk of fraud as more consumers make purchases through ecommerce channels.
Essentially future purchases will require all transactions to be authenticated using two of three authentication methods:
Something a customer knows, like a PIN code or password.
Something a customer has, like a smartphone or token.
Something that uniquely identifies the customer, like a fingerprint or facial recognition.
“The PSD2 directive has faced strong opposition in the market as the timeline to implement a solution with the complexity of the new Strong Customer Authentication rules for ecommerce transactions has always been seen as a challenge,” Scott Edington, CEO of Deep Labs told Mobile Payments Today via email. “The two-step verification process, with many requirements within that new process, requires a high degree of technical and security knowledge and time to build and put into production that new process.”
The San Francisco-based digital security firm has used artificial intelligence to develop solutions to meet the new PSD2 requirements. In March, for example, it launched “Deep Identity” to track transactional risk analysis, which leverages data signals and context aware machine-learning to help confirm risk levels.
In this contributing post to FinExtra, Deep Labs Chief Strategy Officer Michael Lynch discusses that within organizations, fraud professionals and those responsible for revenue growth have been working against each other for decades. You can stop fraud almost completely of course, by making it nearly impossible for your customers to transact by placing limits on the transaction or transfer amount, excessive manual reviews, and requesting additional authentication information that leads to abandonment.
Or you can maximize revenue by taking on more risk by minimizing the consumer security steps and security defenses.
Understanding and recognizing your consumer from a 360-degree view, both with respect to risk and fraud mitigation, to their propensity, motivation to buy, and predicting their next product need is now possible using machine learning and artificial intelligence.
In this article, Deep Labs Chief Strategy Officer Michael Lynch discusses how artificial intelligence is disrupting markets and providing a competitive advantage for early adopters for those investing in the technology now.
Many banks, payment companies and fintechs are attempting to gain a competitive edge in the marketplace by embracing artificial intelligence, via innovative partnerships, strategic investments, and attempting to develop their own cutting-edge technology.
Examples include automation of manual processes and repetitive tasks, predicting how to better serve customers with advice or predicting their next product need, fraud and risk management, chatbots and intelligent virtual assistants, and personalized user experiences.
SUNNYVALE, CA., March 14, 2019 — Plug and Play has selected 135 startups to participate in their Spring 2019 accelerator batches. Entrepreneurs from each startup will take part in one of the following programs: Brand & Retail, Cybersecurity, Energy & Sustainability, Fintech, Food & Beverage, New Materials & Packaging, and Supply Chain. Deep Labs has been selected to participate in the Fintech accelerator Batch 9 program.
“It is fantastic to see such a talented group of entrepreneurs accepted into our programs. We aim to give our startups the best chance for success and these next three months will give them the tools and connections they need to thrive,” said Saeed Amidi, Founder and CEO of Plug and Play. “I am excited to see what they can accomplish when integrated into our ecosystem.”
A record number of entries to the 2019 Digital DNA Awards has been whittled down to a high-calibre short list featuring the best technology businesses and people in Northern Ireland.
Finalists in the highly-coveted Company of the Year category – which will be voted for by the public – are: Allstate, Dawson Andrews, Kainos, Novosco, See Sense and Whitespace.
The winner of each category will be announced at the awards night on 28th March 2019 in St Anne’s Cathedral.
The full list of categories are: Business Personality of the Year, Developer of the Year, Entrepreneur of the Year, Young Person of the Year, App of the Year, Best Digital Marketing Campaign, Digital Project of the Year, e-Commerce Project of the Year, Best Tech for Good Innovation, Deal of the Year, Best Large Tech Company, Best Small Tech Company and Start-up of the Year.
Deep Labs was nominated for Start-up of the Year award and is looking forward to the upcoming Awards Ceremony in Belfast.