The Fraud Team And The Tool
We have met with many cases where analysts not only doubt themselves in their decision but also discouraged to take information into account that may not be considered as useful – not to mention the rise of Machine Learning in fraud prevention. Is our work that we do manually truly outdated?
Through examples we will re-explore the tools that we have at our expense and discuss how we can effectively use them in relation, from articulating sentences, to defining use cases and relying on AI.
- To find or regain the interest in the beauty of fighting fraud – making decisions that would be the key to stop the malicious activity yet keeping the mind open to changes.
- Utilising every aspect of the tool that are available and considering ways that we may have disregarded before and still could be useful, ultimately a boost for the year 2022 and to remain on the top of defense against harmful users.
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Manual Review remains a cornerstone of modern fraud prevention; offering enhanced precision in fraud screening, fairness in dispute management and labels for machine learning. However, as a business grows, so to must a Manual Review team. This introduces operational challenges to manage headcount, quality and return on investment.
In this session, we will cover Booking’s story of launching and rapidly scaling Manual Review Operations as a Service in Fraud Prevention. Hear how we empower a small team of 4 to manage Manual Fraud Operations on a global scale across Booking’s suite of products and associated risks.
As the need to reduce the cost of manual fraud prevention increases, we will show the benefits of leveraging multiple fraud prevention solutions such as outsourcing, automation and ML, demonstrating how the function interacts with various ML models to optimise workload and achieve a balanced defense against fraud.
Conventional fraud detection has historically been centered around linear relationships between user indicators. Machine learning techniques in this domain also focus on learning and adapting to patterns arising from single depth connections of datapoints. The weak point of this setup is that we miss out on transitive relationships, which becomes an increasingly interesting factor when fraudsters reuse few overlapping indicators in new fraud attempts.
At Booking.com, we solved this problem by using graph technology to power our payment fraud controls. In this presentation we will show how we developed an in-house technological ecosystem that stores payments transactions in graph format and leveraged state of the art algorithms to compute innovative graph features that enriches our existing fraud controls (ML models and static rules). We will have a look at the different parts of the system: a latency sensitive real time feature computing service, a visualization tool for analysis of networks and a historical feature reconstruction mechanism. Finally, we will have a look at the impact we saw on our fraud controls after incorporating the new features.
We would conclude by explaining the plans to scale this technology in other fraud domains like marketing & rewards, account takeover etc. and exploring Network Representation Learning (a type of deep learning on graph data) to tackle them.
Business leaders at global marketplace Wish knew the secret to the enterprise's continued growth was increased international expansion.
As one of the world’s largest e-commerce marketplaces, Wish now operates in more than 60 countries, processing approximately 900,000 transactions a day, across about 250,000 merchants, and has more than 20 million monthly active users. While that scale provides a wealth of transaction intelligence, Wish also needed to put a very local lens on the data it was processing.
Wish found its answer in machine learning — in particular a machine learning fraud protection model that scales rapidly while leveraging the fraud and risk expertise of the internal team at Wish. Smart machines surfaced the localized data the Wish team needed to react to the diversity of geo-specific fraud attacks and abuse schemes.
In this session, Signifyd senior vice president of operations and corporate development J. Bennett and Wish Director of Risk Operations Tara Mitchell dive into the considerations around deploying a machine learning solution and explore the steps Wish took to marry the strengths of humans and machines to reduce their exposure to fraud and increase order approval and conversion rates.
Machine learning continues to be an important tool for fraud mitigation specialists, but fraudsters are learning how to adapt.
The current landscape is now a battle against both automated and human-driven attacks. This presentation from Adyen and Microsoft explores the latest techniques in AI and ML to ensure the best customer experience and provide additional context for fraud decisions.
Join LiMeng Lee, Chief Strategy Officer at Razer and MRC APAC Advisory Board Member, and Gene Yu, CEO of Blackpanda (a cyber crisis management firm that offers top-tier cyber-attack containment and investigative services in the event of a data breach) as they demonstrate the importance of having a cybercrime crisis management or incident response plan in place before the incident or event occurs.
LiMeng and Gene will highlight the necessary steps which should be undertaken to set up your incident response strategy, they will also highlight the immediate activities which should take place in the wake of an incident occurring.
The viewer, upon listening to the webinar, will have a basic understanding of the importance of implementing the prevention plans outlined, and were recruiting a third-party consulting company to assist in setting these plans up can help.
Tracy Kobeda Brown is an experienced start-up and corporate executive with expertise in technology strategy, product design, engagement, video gaming, and information security. In her current role as the Vice President of Programs and Technology for the Merchant Risk Council, she is overseeing the programs and technology team tasked with delivering content, education, and tools to help the world’s best fraud and payment professionals battle fraud for their companies. Prior to her role at the Merchant Risk Council, she held various C-level roles at corporate and start-up companies. She was the Head of Product for Fragomen, Lockerz, and the CEO and founder of Evil Genius Designs. Prior to that, she led the team that created American Eagle Outfitters website, ae.com, where she started her career in fraud and payments, eventually becoming the Head of Information Security (CISO).
She earned her Master’s degree from Carnegie Mellon in Entertainment Technology and her BS in Economics from The Wharton School at the University of Pennsylvania in Decision Sciences and Risk Management. She has served on the board of the National Cyber-Forensics and Training Alliance (NCFTA), Co-Chairperson of the Merchant Risk Council at its inception, and as an Executive/Entrepreneur in Residence for various universities and accelerators.
Merchants are always after the best solution for their fraud prevention needs, but it’s hard to know whether a new solution will actually be right in practical, ongoing terms. Enter POCs. A real-life try-out of the solution can give a clear indication of its performance. Right? Not always.
Our webinar will discuss 3 specific use cases that will help merchants understand the right way to conduct a POC for a fraud prevention platform.
In this webinar, we will address the following scenarios and how to best counter their negative impact on a POC:
- The challenge of trusting the accuracy of the POC's end result when another system (i.e., your existing one) is in place and affects the results dramatically.
- An existing fraud prevention system that guarantees transactions and is liable for them. The solution which is being vetted through the POC is not.
- For a limited point in time, you can have professionals conducting the POC side by side with your system. While this approach will significantly improve overall performance, in reality, it will be impossible to replicate.
During the 2022 Annual Member Meeting held on May 17, CEO Julie Fergerson and three other MRC leaders provided an overview of the current membership composition and the organization's financial health. The Meeting also included highlights of ongoing advocacy work, in-person and virtual events planned for the remainder of the calendar year, details of the MRC's expansion into the LATAM region, and a summary of upcoming innovations.
In this edition of the interview series My Path in Payments, Checkout.com spoke with Rakhi Seth-Forrest, VP of Global Fraud & Payment Operations at Warner Bros. Discovery. Rakhi spoke to us about how she and her team tackle payment fraud, her passion for creating a thriving team culture, and her drive to enable innovation in her industry.
In this edition of My Path in Payments, Checkout.com talks to Colleen Graneto about her work at Airbnb, her passion for building products that help money move, and her experience with payments as a small business owner. My Path in Payments is Checkout.com's interview series documenting the candid insights and diverse perspectives of modern payments leaders.