Enterprise Fraud Management (EFM) is a centralized framework for risk management, providing comprehensive risk analysis and application of controls for identifying internal and external frauds across all users, accounts, and channels in the organizations by transaction monitoring and customer profiling. Furthermore, it helps in identifying malicious behaviour and corruption in real-time thereby combating risks, minimizing losses, ensuring regulatory compliance, and optimizing operational efficiencies across the organization and entities.
EFM platform gives higher visibility in identifying threats and mitigating these threats. EFM solutions also offer a unified dashboard, enabling real-time monitoring of transactions and raising alerts for anomalies if required.

Some Noteworthy Features of EFMs are –

  • Centralized Data Repository – Businesses are developing centralized data repositories for clients’ accounts and transactions data for various products and services across multiple channels. EFM solutions process large quantities of data in real-time to create detailed profiles of clients and employees using high-performance computing technology based on machine learning, which can be used to detect and investigate money laundering and fraud.
  • Fraud Risk Assessment – A fraud risk assessment is a vigorous and continuously improving process. Organizations do thorough fraud risk assessments to identify individual fraud schemes and risks, assess their probability and magnitude, check existing fraud control actions. They introduce new rules and regulations to improve fraud detection. EFM solutions use risk scores to assess fraud based on guidelines provided by enterprise firm and analysed historical information. The new cloud-based EFM solutions are flexible enough to adapt these new rules and risk assessment tasks.
  • Real-Time Detection using Analytics – Since fraudsters are becoming more advanced, EFMs must evolve at a faster rate. EFM solutions allow for in-depth analysis of internal and external data collected from all resources for real-time fraud detection. In addition to rule-based fraud detection, sophisticated predictive fraud models fuelled by analytics on massive quantities of data are being developed. Risk is assessed in real-time for each transaction using a combination of parameters, algorithms, and cumulative statistics by comparing the characteristics of each customer’s or employee’s conduct with the fraud models and recorded patterns of behaviour. Techniques like graph visualization are used to identify underlying patterns and irregularities in data. EFM’s have forensic tools for e-fraud investigation. The aim is to use all available data to detect illegal activity before it happens and to avoid it before a customer’s account is compromised.
  • Scalability and Performance – EFM solutions are cloud-based, so there are no data storage and processing limitations. Financial institutions like banks with millions of customers and billions of transactions can be monitored with EFMs while retaining the fast detection needed in real-time environments. These organizations can leverage EFM’s cross-channel fraud management, user-centric fraud detection based on advanced AI. EFM solutions can easily correlate fraud events across the organization.
  • Enterprise Case Management – Enterprise Case Management uncovers hidden relationships in financial transactions. It is created primarily for financial fraud detection and investigations in the EFM solutions, it is built on previous fraud cases. These prebuilt and streamlined cases include key areas of fraud, which ease the process of fraud detection.

In the digital era, with evolving technologies, fraud attacks are also increasing at an alarming rate, indicating organizations to include Enterprise Fraud Management solutions to mitigate threats and frauds in the risk landscape.