FEATURE STORY - PAGE 6 How U.S. Bank Is Using Machine Learning To Tackle Fraud NEWS & TRENDS DEEP DIVE M&T Bank releases mobile money Protecting customers from management09 tool to boost users’ account opening14 and other financial health fraud in the mobile channel SEPTEMBER 2019 © 2019 PYMNTS.com All Rights Reserved 1 DIGITAL BANKINGTRACKER TABLE OF CONTENTS What’s Inside 03 A look at worldwide digital banking news, including how FIs and FinTechs are using AI and ML to respond to fraud in channels like voice banking Feature Story Dominic Venturo, executive vice president and chief innovation officer at U.S. Bank, on 06 how ML can help prevent synthetic identity theft and account opening fraud News and Trends Headlines on the latest digital banking trends, including why FIs like the Royal Bank of 09 Canada are launching student mobile apps Deep Dive A closer look at how banks can use AI and ML to reduce fraud in mobile channels, 14 including how these technologies may replace passwords Top 10 Rankings 18 The highest-ranking B2B and B2C digital banking providers Scorecard See this month’s top scorers and a directory featuring more than 250 digital banking players, 19 including three additions About 158 Information on PYMNTS.com and Feedzai ACKNOWLEDGMENT The Digital Banking Tracker was done in collaboration with Feedzai, and PYMNTS is grateful for the company’s support and insight. PYMNTS.com retains full editorial control over the following findings, methodology and data analysis. © 2019 PYMNTS.com All Rights Reserved 2 What's Inside Fraud protection and data security innovations are struggling to protect against a rising number of cy- musts in digital banking, especially since bad ac- berattacks and hacking attempts. FIs and finance tors seem to consistently find new ways around such apps in these areas are now taking steps to ward measures. Financial institutions (FIs) may be experi- off app hijacking, automated bot attacks and other menting with features and new technologies to serve forms of technology-driven fraud that put their cus- and protect their customers, but cybercriminals are tomers' data at risk. working just as hard to match that pace. Southeast Asia may be one of the regions most prone The rise of mobile banking means an increasing risk to fraud, but banks around the globe are searching for of related fraud, and FIs and fraudsters are both de- ways to combat the fraudsters dispensing their cus- ploying technologies like artificial intelligence (AI) tomers’ data to other nefarious parties. Australian and machine learning (ML) to keep control of cus- FIs are responding to the aftermath of a data breach tomers' data. It’s perhaps not surprising that losses that originated from the country’s New Payments emanating from fraud in mobile and web channels Platform (NPP) faster payment system, exposing have been steadily rising, with three-fourths of U.S. the PayID names and account numbers of an undis- banks alone reporting growing losses in these areas. closed number of banking customers. The FIs are One study claims 49 percent of all risky transactions urging users to remain vigilant for scammers who worldwide originated from mobile devices and that may use the uncovered data to target their accounts. 61 percent of banking transactions now originate Card networks like Visa are meanwhile developing from mobile, highlighting why fraudsters have turned new AI-focused tools to help banks better protect their attentions there. themselves and their customers against fraud. It Account takeover (ATO) fraud remains one of the recently announced a new set of security features most frequently used methods by bad actors to gain designed to protect merchants’ and retail bank- access to users’ banking data. Such attempts are ing users’ data, including the Visa Account Attack popular with cybercriminals because they can orig- Intelligence tool to monitor card-not-present (CNP) inate from a single customer data point — such as fraud through deep learning. The tool could prove an ill-gotten email address, date of birth or full name helpful in tracking transactions and protecting — and most fraudsters rely on technology to do the against the hackers who want to scoop up card num- work for them from there. About 40 percent of all bers or security codes. ATO attacks now count as high-risk, meaning banks For more on these stories and other digital banking of all shapes and sizes must reexamine how they headlines, read the Tracker’s News and Trends sec- think about data protection, security and the tools tion (p. 9). they use to guard against emerging threats. How U.S. Bank uses ML to fight account Around the digital banking world opening, synthetic identity fraud Some regions are dealing with more fraud problems Fraudsters are more frequently relying on schemes than others. Southeast Asia is particularly vulnera- that use stolen credentials to imitate legitimate cus- ble, with banks in Indonesia, Singapore and Vietnam ACKNOWLEDGMENT tomers, methods that can be tricky for banks to The Digital Banking Tracker was done in collaboration with Feedzai, and PYMNTS is grateful for the company’s support and insight. PYMNTS.com retains full editorial control over the following findings, methodology and data analysis. © 2019 PYMNTS.com All Rights Reserved 3 WHAT'S INSIDE detect with traditional fraud protection tools. FIs also need to ensure they are not adding additional layers EXECUTIVE INSIGHT of friction to the customer experience as they create stricter authentication measures. AI and ML technol- ogies help lessen the impacts of ATO and other fraud What are some of the challenges attempts without the friction, said Dominic Venturo, banks are facing when protecting against bot attacks, ATOs, spoofing executive vice president and chief innovation officer attempts and other automated for U.S. Bank. In this month’s Feature Story (p. 6), he forms of fraud? discusses how FIs can tap into both technologies. How banks are using AI technology to better fight fraud "Fraudsters have undergone their own digital transformation, going far beyond person-to-per- A reported 3,813 data breaches in the first half of son fraud. They have become sophisticated 2019 exposed a collective 4.1 billion customer re- enough that they are also using tools like machine cords. ATO fraud is becoming a common method learning and are even automating their fraud simply because of the wealth of data that is available techniques. That’s essentially what a bot does to fraudsters, enabling them to imitate legitimate — breach a vast [number] of internet-connected customers with ease. Banks may be able to guard devices and coordinate them to launch an attack. against such schemes by employing AI and ML to We’ve seen them attempt to wreak havoc on our greater effect, however. To learn more about how FIs clients and their customers. How do you combat are currently using such technologies in this area, that? You automate fraud detection as well, and and how they can better protect customers, read the build more advanced tools to always stay ahead Tracker’s Deep Dive (p. 14). of the newest trends in financial crime. To be truly effective, you have to be able to score transac- September Digital Banking Tracker updates tions in real time, you have to be able to handle the enormity of data from many sources and you have This edition of the Digital Banking Tracker includes to use advanced tools like automated machine profiles of more than 250 financial players, including learning workflows and AI-powered visualiza- three additions: Apiture, Mobills and Olivia. tion engines." SAURABH BAJAJ chief product officer at Feedzai © 2019 PYMNTS.com All Rights Reserved 4 WHAT'S INSIDE 5Five Fast Facts 70% 73% 49% Share of Portion of Portion of risky customers born customers transactions after 1980 who who feel they globally that have are willing to use should be able originated from digital banks 77% to accomplish all 38% mobile devices in financial tasks on the past year mobile phones Segment of banks Fraction of that have currently consumers who deployed some have not visited form of AI bank branches in the past six months © 2019 PYMNTS.com All Rights Reserved 5 How U.S. Bank Is Using Machine Learning To Tackle Fraud © 2019 PYMNTS.com All Rights Reserved 6 Mobile and online banking providers have been up- can run through large reams of data, adding addi- ping their fraud protection measures over the last tional fraud protection layers to online banking and decade, making it more difficult for bad actors to speeding up the review process for FIs that are on rely on some of the schemes that previously worked the hunt for fraudulent transactions. in such channels. The prevalence of CNP fraud, “Improving our efficiency is great for us, but, from once the bread and butter of the enterprising cy- a customer perspective, what that means is ‘less bercriminal, has steadily crept downward each year hassle, faster answers,’” Venturo said in a recent in- alongside other forms that game customers’ credit terview with PYMNTS. “If all you’re trying to do [as a card numbers. customer] is log in … then we’re using different tools Cybercriminals are still masters of a thriving trade, to make sure you are you when you’re doing that — though. Banks are dealing with rapid rises in fraud without trying to get a blood sample along the way to schemes such as ATOs, synthetic identity fraud and prove it before you can see your balance.” account opening fraud. Creating new credit or mo- ML and AI can provide layered protection for new bile device accounts is a popular application of this and existing customers, he added, a necessity in a type, which uses legitimate customers’ stolen infor- banking world that sees synthetic identity theft and mation to defraud both them and their FIs.