Choosing ALSPs /MSPs and Where They Fall Short  

Organizations often choose ALSPs or MSPs for incident response simply because they’ve retained them for related services and it’s more convenient to expand the existing relationships without additional approvals or procurement steps.  

Many law firms, ALSPs, and cybersecurity providers position IR as a natural extension to their other offerings and attempt to handle cases by repurposing existing processes and technology. However, this can no longer manage today’s cyber incidents effectively.  

These providers typically rely on three inefficient options:  

  1. Manual Review: The traditional method of hiring teams of people to analyze data one file at a time. This is slow, error prone, expensive, and unstainable as data complexity increases.  
  2. Partnering with Vendors: Some providers will turn to third-party tech solutions or tools, but without an in-house team to manage it, they struggle to use them effectively.  
  3. Leveraging In-House Technology: Providers often do not have the R&D or motivation to build the technology and hire the right people to do this successfully, leading this option to fall short of meeting client expectations and regulatory requirements.   

ALSPs and MSPs weren’t built for high-speed, high-accuracy breach investigations, and their limitations become clear when their methods fail to meet requirements or produce accurate results.  

The Hidden Costs of Traditional Incident Response  

Organizations often turn to ALSPs and MSPs because they appear to offer cost-effective solutions, but the hidden costs of these traditional approaches often come with hidden expenses that quickly add up.  

Manual review or vendor partnerships frequently lead to extended notification timelines, increasing the risk of noncompliance and regulatory penalties. Many providers outsource data review overseas to cut costs, but this introduction new security vulnerabilities, exposing already compromised data to additional risks. Inaccuracies in breach identification can result in lawsuits, fines, and reputational damage, while inefficiencies in manual workflows can escalate costs far beyond the original estimates.  

What may originally seem like the easier, less expensive solution often becomes a financial and operational burden. Organizations need a solution built for today’s data challenges that reduces risk, improves efficiency, and ensures compliance.  

The Case for Purpose-Built Data Mining Technology  

Data mining technology transforms incident response by automating the analysis of complex, compromised data ensuring accuracy and speed. Purpose-built solutions offer several key advantages:  

  • Speed: AI-driven data mining rapidly scans, processes, and analyzes massive datasets to identify compromised information. 
  • Accuracy: Machine learning algorithms identify impacted individuals and sensitive data with far greater precision than manual review.  
  • Scalability: Automated workflows can handle vast, complex data structures across hybrid environments.  
  • Cost-Effectiveness: By reducing reliance on slow, expensive manual reviews, engagements stay on budget and on schedule.  
  • Regulatory Compliance: Fast, accurate reporting ensures organizations meet breach notification deadlines.  

Unlike ALSPs and MSPs which rely on outdated or inefficient methods, purpose-built data mining technology delivers real results.  

The Future of Incident Response  

The cyber threat landscape isn’t slowing down, and neither are regulatory demands. Organizations need a solution that matches the complexity of today’s breaches, allowing them to respond faster, minimize compliance risks, and reduce costs while ensuring their response is accurate and defensible.