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Case Study
KPMG

“Creating a forensics report for our customer used to take days to load and a month to produce. With Loom, we’re able to produce a better final report in less time than it previously took to load the data. And, we’re detecting things we didn’t even know to look for in the past.”


Naveed Islam
, Manager – Cybersecurity, Advisory at KPMG Canada

KPMG is a global network of independent member firms offering audit, tax and advisory services. The firms work closely with clients, helping them to mitigate risks and grasp opportunities.

Member firms' clients include business corporations, government and public-sector agencies and not-for-profit organizations. They address KPMG for a consistent standard of service based on high order professional capabilities, industry insights and local knowledge. KPMG member firms cater to 152 countries. Collectively they employ more than 189,000 people across an array of disciplines.


KPMG’s cyber and forensics divisions serve many
customers in many industries who struggle to put
process in place around cyber and forensics issues.
They depend on KPMG to provide analysis and
guidance on security breaches and effective remedies
to protect them from future attacks.


Business Challenge: KPMG’s workflow with customers would be to receive logs from a compromised machine, often IIS web server logs, windows and event logs. The files could be 10-15 TB of structured or unstructured data, and KPMG has a limited understanding of the customer’s environment. The cyber security and forensics division would then analyze the logs and report back to the customer using manual tools to research the logs.

The Company | KPMG
Location | Canada
Service | Management Consulting
Challenge | KPMG needed to provide detailed reports on security breaches from vast quantities of data and minimal prior knowledge of complex environments in which the breach occurred.
Solution | Loom’s automatic data processing and structuring as well as AI-driven detection of problems helped KPMG provide better analysis of cyber security breaches to its customers in a fraction of the time it took previously.


The first challenge with such work methodology was time: due to a large log quantity, such a process often takes several days up to a week to process the data. A further analysis of the logs would take a full month to produce a report which includes meaningful conclusions for the customer. Furthermore, due to the limited knowledge of the customer’s environment, detection of issues was highly manual and led by human intuition, rather than automatic and scientific.


How did Loom help? To rectify these issues, KPMG harnessed Loom Systems' AI-based technology to process the data and apply structure based on pattern recognition and lexical detection. Loom Systems’ AI engine, Sophie, automatically analyzed the data to detect abnormal behaviors, without any prior directive.

 

End Result: KPMG could now receive large amounts of logs, process them, and provide a comprehensive report to its clients within days after log reception instead of a month which the process would previously require. Beyond just a faster response time, KPMG found the analysis of the logs was highly significant due to Loom’s ability to correlate abnormalities across several layers of stack, providing a complete view of the breach’s origin.

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