3 Ways CEOs Can Close the Enterprise Risk Management Capability Gap

The cloud also is elastic, enabling companies to scale storage capacity and processing power, allowing companies to mine and analyze large and variable datasets without investing in massive on-premise IT infrastructure or compromising security.

Big Change #2: Dynamic Data from IoT & Social Media
Risk managers have traditionally collected and analyzed historical data to predict future risk exposure. But, time lags from data collection to aggregation and analysis have hampered decision-making. With the proliferation of sensor-equipped devices, like infrastructure sensors monitoring property integrity, risk operations are now empowered to monitor in real time the status of property, equipment and events that affect risk. IoT provides risk operations unprecedented agility to anticipate and respond to perilous events.

“Time lags from data collection to aggregation and analysis have hampered decision-making.”

Social media is also an important tool for monitoring potential reputational, location-based, and safety risks. Integrating social media alerts about global, adverse events into a risk management system provides risk managers with another data source for providing the C-Suite with real-time perspectives on potential risk exposures.

The challenge for the C-suite now becomes data overload. The key is analyzing all this unstructured data, filtering out the “noise,” and converting impactful data into actionable insight.

Big Change #3: Big Data & Predictive Analytics
Today, companies monitor multiple data sources in real time (dynamic data), enabling faster, more informed decisions. To effectively unlock and use big data, companies must have predictive analytics. Predictive analytics applications that support risk management efforts include: