BIGGERWIDE FOR RISK MANAGERS

HOW CAN WE USE BIGGERWIDE AI?

Risk Managers can use BIGGERWIDE AI to enhance their risk mitigation strategies through advanced data analysis and real-time insights. By leveraging BIGGERWIDE AI's capabilities, Risk Managers can efficiently process vast amounts of unstructured data from diverse sources such as transaction records, financial statements, and market trends

This allows them to detect fraud, assess credit and market risks, andpredict potential threats with greater accuracy. The platform’s secure on-premises deployment ensures that sensitive financial data remainsprotected, addressing critical privacy and compliance concerns.Ultimately, BIGGERWIDE AI empowers Risk Managers to makeinformed decisions, safeguard the institution’s assets, and maintainregulatory compliance.

USE CASES FOR RISK MANAGERS IN THE BANKING AND FINANCE INDUSTRY USING BIGGERWIDE AI

The following use cases demonstrate how BIGGERWIDE AI can support Risk Managers in the banking and finance sector by improving fraud detection, credit risk assessment, and regulatory compliance, ultimately enhancing overall risk management capabilities

Fraud Detection and Prevention

Use Case

Risk Managers in banking and finance can leverage BIGGERWIDE AI to detect and prevent fraud by analysing large volumes of transactional data and identifying suspicious activities.

How It Works

Data Ingestion: BIGGERWIDE AI
ingests vast amounts of transactional data, customer profiles, and historical fraud cases.

Pattern Recognition: The AI model identifies unusual patterns and anomalies that may indicate fraudulent behaviour, such as rapid movements of funds, inconsistent transaction times, or deviations from normal spending patterns.

Real-Time Alerts: Risk Managers receive real-time alerts for potential fraud cases, allowing them to take immediate action to mitigate risks.

Benefits

Enhanced ability to identify and respond to fraudulent activities swiftly. Reduced financial losses due to early detection and intervention. Improved regulatory compliance by maintaining robust fraud detection mechanisms