Following up the previously published Now Tech report, I’m excited to announce that The Forrester Wave™: Enterprise Fraud Management In Asia Pacific, Q4 2021 is now live.
Forrester defines enterprise fraud management (EFM) as “a solution that integrates data from multiple payment and non-payment transaction processing systems, online portals, and threat information sources and provides transaction monitoring, risk scoring, case management, and reporting for online and offline and payment and non-payment transactions.” In our 34-criterion evaluation of EFM providers in Asia Pacific (APAC), we identified the seven most significant ones — Alibaba Cloud, Baidu, Bangsun Technology, Dingxiang Technologies, Mininglamp Technology, NEXT DATA, and Tencent Cloud — and researched, analyzed, and scored them on current offering, strategy, and market presence.
As new digital commerce and payment methods have proliferated and digital finance has become the norm in recent years in Asia Pacific, transaction fraud has become significantly more frequent and sophisticated. New types of user-authorized fraud, such as promotion fraud and telecom fraud, and the increasing correlation between fraud and money laundering require more sophisticated fraud management models and strategies that respond in real time, detect fraud prior to a transaction, and are driven by data insights. As a result of these trends, enterprise fraud management customers in Asia Pacific should look for vendors that provide:
- Sophisticated AI- and ML-based fraud models to respond to new fraud patterns quickly. Models based on machine learning (ML) and employing a variety of algorithms can effectively identify new fraud patterns and prevent different types of fraud. For instance, models based on supervised learning are suitable for transaction monitoring, where regulations require high explainability. Models based on knowledge graphs reveal complex relationships to battle group fraud. Customers expect vendors to provide multiple algorithm-based ML models and model-building features out of the box.
- Privacy tech to allow financial institutions to use more data insights to fight fraud. The rapid growth of digital financial services and lifestyle offerings requires financial institutions to manage risks in a variety of channels and business scenarios — so it’s very valuable for them to get data insights from a variety of sources. But stringent regulations in many countries forbid these institutions from exchanging data with external entities, including vendors. This makes it difficult to leverage data insights, such as risk scores, from vendors in a software-as-a-service deployment model. To tackle this challenge, innovative vendors are developing privacy technologies like homomorphic encryption and federated learning to enable financial institutions to share encrypted data while complying with regulations so they can get richer data insights from multiple channels and scenarios to identify fraudulent transactions more effectively.
- A flexible, customizable workflow for citizen data scientists to build models. The low-code and no-code trends are increasing customers’ expectations of vendors to provide easy-to-use visual model-building features so citizen data scientists and business users can build, train, and manage out-of-the-box and custom-built models and model ensembles. Vendors should provide capabilities for end users to build models based on rules, AI, and ML in an integrated, unified platform to improve data scientists’ efficiency and augment business and non-technical users’ capabilities.
To see how the evaluated vendors stack up, Forrester clients can find the full report here — but keep in mind that the written report just scratches the surface of the full evaluation. Download the interactive scorecard tool and use it to customize the Forrester Wave model for your organization’s objectives.
If you are interested in digging deeper into the findings of the evaluation or want to discuss EFM in APAC more broadly, please schedule an inquiry.