Impact of AI Realtime alerting for risk mitigation use cases
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Introduction
As AI technology develops, businesses discover additional processes and use cases that need to be optimised. Making sure you select the ideal solution for your needs is essential to successfully implementing AI in your organisation. There are many platforms that use AI characteristics to address business concerns. You encounter it every day, for example, when you begin to write on Gmail, it anticipates what you will write next.
One of the biggest challenges you see out there now in the digital and physical world is the amount of noise that is generated. All this leads to is too much time spent on monitoring, identifying and investigating vulnerabilities on your business and can result in being behind the curve when it comes to acting on those vulnerabilities. AI’s ability to analyse large amounts of information substantially improves the identification of data relevant risk management, risk assessment, and ensuring the correct follow up action.
Engines for machine learning are capable of analysing vast volumes of data from many sources. Some of the market-available solutions will source information from more than 400 thousand data sources worldwide, including feeds, global social media, code repositories, news media, the deep and black web, IoT sensors, video, etc. Real-time prediction models are created using this data, enabling security teams and risk managers to promptly address concerns. This is essential for creating early warning threat management systems that guarantee the organisation’s continuous functioning and the safety of its stakeholders.
How will this fit to your business?
As an organisation, you must determine whether you have a full understanding of the risks that are affecting you in real time, are able to recognise them, and are capable of responding to alarms.
Prior to doing anything else, the first step is to determine the regulatory, reputational, and stakeholder risks that the organisation faces. You then need to know how to handle information once a risk is discovered and understand what you lose if you do not identify what these risks are.
This will then serve as the foundation for your organisation’s risk management structure. You can then decide what information you need to gather and how you want to handle it. You must be able to view this from both a macro and a micro perspective within your organisation.
After defining it, you’d need to incorporate enterprise risk technology into your business’s operations integrating it into either an incident management system or building it into your own systems.
Any AI adoption strategy needs to be in alignment with the overall risk appetite from the beginning in order to build effective risk management processes and controls.
Choosing the right solution
As mentioned in the introduction it is key to choose the right solution that fits your business. Whatever you choose, it must:
- Minimise business disruption and keep people and assets safe
- Reduce or avoid reputational risk
- Reduce duplicative or unnecessary efforts
- Not impact security labour costs
- Discover and contextualise risk information
- Enable proactive and coordinated responses and alerts
- Be easy to deploy and scale
- Increase ROI by allowing security teams to contextualise and accelerate responses to high impact events, threats, and emerging risks.
- Must be available as a platform that is truly multilanguage
A pioneer in this field is Dataminr, whose real-time AI engine, Pulse, finds the early signs of developing dangers and high-impact events in openly accessible data.
In order to better protect your employees, your brand, and your physical and digital assets, Dataminr Pulse provides you with the first warnings of high-impact events, as well as rich visual context and tools that help you cooperate and respond more quickly.
Numerous hyperlocal public data sources offer extensive coverage, while translations into more than 100 languages offer the most complete picture of the world’s risk environment.
You are able to customise your alert streams based on the information that is most pertinent to your assets thanks to extensive, particular topic lists. Your team can visualise hurricane paths, active alert zones, and storm impact areas thanks to Dataminr Pulse’s open-source data layers from providers like the National Weather Service and proprietary data providers like IBM Weather. This allows you to respond promptly to significant weather events and maintain an accurate line of sight as they unfold.
The right choice will invariably help you reduce average incident response time, including:
- Mean time to detect
- Mean time to acknowledge
- Mean time to resolution
- Total number of incidents, including:
- Volume and frequency of alerts that turn into incidents
- Volume of unactionable alerts
- Escalation ratio, including:
- Percentage of alerts escalated for action
- Percentage of incidents resolved in a defined timeframe
- And, you can measure cost reductions realised by saving time and manpower and streamlining or fully automating processes.
With the convergence of cyber and physical risks, risks will continue to rise, so your SOC should have access to critical real-time data that provides a holistic view of the risk landscape.
Impact of the right Risk Management Solution on your Business Risks
Some of the initial alarms on the use of a serious vulnerability in Apache Log4j were surfaced by Dataminr Pulse. Pulse for Cyber Risk equips threat analysts to understand their attack surface, proactively mitigate risk, and defend their enterprises by cross-correlating data from many sources.
Businesses are increasingly reliant on digital infrastructure and tools. Customers need to be able to proactively minimise risk (financial, reputational, and operational) in the whole context in which it emerges.
Which Personas need to consider this solution?
- Corporate Security: CEO
- Reputation Risk Lead: CMO, CCO
- Cyber Risk Leads: CISO
- Business Intelligence: COO, CFO, GC, CRO
Which industries are already benefiting from this technology?
- Financial Services
- Retail/Consumer
- Goods/Manufacturing
- Real Estate
- Healthcare/Life Sciences/Pharmaceutical
- Technology
- Transportation/Logistics
- Energy – Oil & Gas Shell, BHP
- Energy – Power & Utilities
ROI
Forrester Consulting was hired by Dataminr to carry out Total Economic Impact research in order to investigate the measurable advantages businesses are gaining from using Dataminr Pulse. According to the study, firms’ return on investment (ROI) could reach 421% with a payback period of just six months.
Conclusion
As you can see from the blog, selecting the proper enterprise risk solution is essential in today’s complex and challenging world, where incidents that endanger employees and physical assets, disrupt business operations, lower employee productivity, and alter customer and employee perceptions are on the rise.
AI platforms for real-time alerting are swiftly changing the game. Dataminr Pulse is one we have talked about and you can see how organisations see the benefit from Day 1.