The Challenge of Consistent Company Analysis.

In the complex world of private market investing, accurately assessing and comparing companies is crucial. However, two significant challenges often undermine this process: the lack of standardization in how companies present their financial data and the inconsistent approaches to company analysis among analysts within the same fund.

First, the lack of standardization in how companies present financial data creates a critical hurdle. Companies often report their financial information in different formats and structures, making it difficult to create a consistent basis for comparison. Without a standardized approach to this data, comparing a company’s performance against its peers or the broader market becomes nearly impossible. This lack of uniformity hinders investors' ability to determine whether a company is truly excelling or underperforming within its industry.
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Second, the inconsistency in how company analyses are conducted within the same fund further complicates matters. When different analysts use varied methods or metrics, the comparisons drawn can be fundamentally flawed, leading to unreliable conclusions.

Moreover, standardization serves a purpose beyond just enabling fair comparisons between companies; it also facilitates the aggregation of data. By aggregating standardized metrics and financial data—where the source data is consistent and calculated uniformly—investors can identify broader trends and build deeper knowledge about specific sectors, leading to more comprehensive market insights.

How Intrinsiq Addresses Standardization Challenges.

Standardizing Financial Data with Intrinsiq’s Comprehensive Financial Library

One of the core challenges in private market investing is the standardization of raw, unstructured financial data from diverse sources such as P&L statements, balance sheets, and cash flow statements. To address this, Intrinsiq has developed an in-house financial library that automatically maps these varied financial data points to standardized categories.

This process links raw line items from diverse financial statements to standardized categories in our financial library, which is composed exclusively of standardized categories. This approach enforces consistency and standardization, making it possible to compare and benchmark data across different companies and sectors with precision.

Despite the automation, Intrinsiq ensures user control over data, allowing users to review, adjust, and confirm how financial data is categorized, ensuring both accuracy and relevance. This balance between automation and user oversight ensures that the data stored within Intrinsiq is standardized and reliable, providing a solid foundation for further analysis and benchmarking.

Automatic Metric Standardization from Source Files

Intrinsiq also excels in automating the calculation of key performance indicators (KPIs) directly from source files. For example, when dealing with customer cubes in tech and SaaS companies, our platform automatically calculates metrics like Lifetime Value (LTV) and Customer Acquisition Cost (CAC) Payback in a consistent manner.

By ensuring that metrics like LTV and CAC Payback are always calculated the same way, Intrinsiq eliminates discrepancies that arise from varied calculation methods, providing a reliable basis for comparison across analyses. This standardization at the point of data entry ensures that all subsequent analyses are built on a foundation of accurate, consistent, and comparable data.

How Intrinsiq Helped a SaaS and Fintech Fund Tailor Its Investment Strategy

To illustrate the power of standardization and data-driven insights, Intrinsiq helped a fund focused on SaaS and Fintech companies significantly enhance its ability to identify key market trends and tailor its investment strategy accordingly.

Intrinsiq’s platform also enabled the fund to aggregate revenue growth metrics across its SaaS and Fintech investments. By standardizing how revenue data was categorized and calculated, Intrinsiq provided a clear, aggregated view of growth trends across the portfolio. This aggregated data revealed an emerging trend: SaaS companies offering cloud-based financial management tools were experiencing a surge in revenue, driven by increased demand from SMEs seeking digital solutions during economic uncertainty. Recognizing this trend early, the fund was able to shift its focus towards these cloud-based SaaS providers, capturing a significant market opportunity ahead of its competitors.

Another area where Intrinsiq made a significant impact was in the benchmarking of Lifetime Value (LTV) across the fund’s Fintech portfolio. Prior to adopting Intrinsiq, the fund struggled to compare LTV across companies due to differences in how each company calculated this metric. Intrinsiq’s automated metric standardization ensured that LTV was consistently calculated for all portfolio companies, using a uniform methodology directly from the raw customer data cubes.
With standardized LTV data, the fund was able to benchmark its Fintech companies against each other and the broader market. This analysis revealed that startups focusing on micro-lending had significantly higher LTVs compared to those in payment processing. Armed with this insight, the fund strategically increased its investments in the micro-lending sector, where customer retention and value were demonstrably higher.