Financial fraud poses a major challenge for the financial services industry. Not only does it come in many different forms, but it’s often difficult to detect due to the complexity of the relationships between entities and hidden patterns. And, once detected, financial institutions must notify customers of fraudulent activity in real time and take immediate action to stop it—for example, by blocking the customer’s credit card.
The financial services industry is also regulated and must report anti–money laundering (AML) activities and complete due diligence on their customers using Know Your Customer (or KYC) processes. This often requires analyzing data across products, markets, and geographies to identify relationships and patterns for AML.
Conceptually, money laundering is simple: Dirty money is passed around, blended with legitimate funds, and then turned into hard assets. In reality, it’s far more complicated, relying on a long, complex series of valid transfers between accounts created using synthetic (often stolen) identities and often using similar information, such as email and street addresses. In short, it involves a vast amount of data, which is why a unified data platform that supports advanced analytic techniques, such as graph analysis, is essential for AML programs.
The financial services industry continues to be highly monitored and regulated, and few areas have seen a greater increase in regulatory focus than anti–money laundering and counter-terrorist financing activities. Driven by vast criminal networks, financial fraud is a sophisticated and growing challenge requiring anti–money laundering solutions that provide insight across the enterprise and the entire globe.
The following architecture demonstrates how Oracle components and capabilities, including advanced analytics and machine learning, can be combined to create a data platform that covers the entire data analytics lifecycle and delivers the insights AML teams need to identify the anomalous patterns in behavior that can be indicative of fraudulent activity.
There are three main ways to inject data into an architecture to enable financial services organizations to identify potentially fraudulent activity.
Data persistence and processing is built on three (optionally four) components.
The ability to analyze, predict, and act is built on three technology approaches.
Oracle Data Platform can help your organization detect money laundering more effectively, boost the accuracy and efficiency of financial crime investigations, and streamline reporting processes to keep compliance costs down.
Oracle 所提供的 Free Tier 包含無時間限制使用 20 多項服務 (如 Autonomous Database、Arm Compute 和 Storage) 以及 300 美元的免費額度，可試用其他雲端服務。取得詳細資料，並立即註冊您的免費帳戶。
透過教學課程和實作實驗室來體驗廣泛的 OCI 服務。無論您是開發人員、管理員還是分析人員，我們都可以協助您瞭解 OCI 的運作方式。許多實驗室是在 Oracle Cloud 免費層或 Oracle 提供的免費實驗室環境上執行。
此研討會中的實驗室涵蓋 Oracle Cloud Infrastructure (OCI) 核心服務介紹，包括虛擬雲端網路 (VCN) 以及運算和儲存服務。立即開始 OCI 核心服務實驗
在此研討會中，您將會瞭解使用 Oracle Autonomous Database 的步驟。立即開始 Autonomous Database 快速入門實驗
本實驗將引導您將試算表上傳到 Oracle Database 表中，然後根據此新表格建立應用模組。立即開始此實驗
在本實驗中，您將會在 Oracle Cloud Infrastructure (OCI) 中的兩個運算執行處理上部署 Web 伺服器，並使用負載平衡器以高可用性模式 (High Availability) 進行設定。立即開始 HA 應用程式實驗
瞭解架構師與其他客戶如何部署各種工作負載，從企業應用程式至 HPC，以及從微服務到資料湖。透過「Built & Deployed」影片系列，瞭解最佳實務，聽聽其他客戶架構師的分享，甚至使用我們的「按一下即可部署」功能來建置許多工作負載，或者從我們的 GitHub 儲存區域自行完成。
Oracle Cloud 的定價簡單明瞭，在全球各地保持一致的實惠價格，而且支援廣泛的使用案例。若要預估您的費率，請查看費用預估工具，並依照您的需要設定服務。