With our pricing engine, asset managers and investors can determine market-driven prices for all traditional asset classes with just one click. The underlying mathematical models are based on over 6,000 data points measured monthly and Patric A. Huber's 20 years of experience – including his roles as Global Head of Pricing at UBS Asset Management.
Calculate precise prices for institutional asset management mandates – simply in seconds!
Pricing Engine
“Pricing in institutional asset management is often opaque, inefficient, and based more on gut feeling than on facts.
Our pricing engine calculates market-driven prices in seconds – transparent, risk-adjusted, and scientifically sound – for investors and asset managers alike."
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Over 20 years of international management experience including at UBS Asset Management, as Global Head of Pricing and Global Head of Product Strategy & Shelf Evolution
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Building global pricing and revenue management frameworks for multi-billion dollar institutional mandates
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Strategic responsibility for proprietary capital strategies with direct impact on growth and profitability
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Doctorate in Management from the University of St. Gallen; Swiss Certified Public Accountant
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Lecturer at the Financial Services Zug Competence centre and former member of industry working groups for the further development of fund economics and institutional pricing
Patric A. Huber, Ph.D.
This is how pricing works according to the method
of pricing expert Patric A. Huber
This is how it works:
Prices are determined based on historical median values – often from aggregated data by (sub-)asset class and mandate size. Differences in risk profile or strategy are not taken into account.
Typical for this method:
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Average values from data pools (e.g. 65 strategies in a median)
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Rough bucketing by assets under management (AuM)
What this means:
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Little significance for concrete mandates
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Lack of transparency of the value drivers of a strategy
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No reliable basis for sound price negotiations
Traditional pricing
This is how it works:
Our engine uses mathematical models to calculate a market-based price for any traditional investment strategy - based on a few, but meaningful, inputs such as AuM, target alpha, and complexity.
Typical for this method:
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Scientifically based computational logic
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Individual pricing for every risk and complexity configuration
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Continuous curve instead of rigid buckets
What this means:
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Clear, risk-appropriate price points instead of inaccurate averages
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Greater negotiating power through better understanding of the underlying value drivers
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Transparency for both sides: Investors do not overpay – asset managers do not give away margins
Pricing with the 1 ProValue Pricing Engine
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Transparency creates trust
FAQ
Here you can find our FAQs - hover your mouse over the question to find the answer.
We already work with consultants – do we really need that?
Our tool complements existing consulting – it provides precise, data-driven decision-making bases and relieves your advisors of the burden of detailed analysis. This gives you greater depth, speed, and independence in assessing offers.
Doesn’t more transparency lead to more difficult business relationships?
On the contrary – transparency builds trust. When prices and services are transparent, it strengthens relationships with providers, customers, and policyholders.
What is your pricing model?
We offer a fixed-price model based on the number of users. Alternatively, you can choose a lower fixed price and pay based on usage.
Can you prove the financial benefit?
Yes. Even small optimizations—for example, five basis points on a billion-dollar volume—mean 500,000 per year. That translates to 2.5 million in potential savings over five years.
Yes. Thanks to the REST API, our pricing engine can be flexibly integrated into your infrastructure. For example, use 1 pro Value as the core of a revenue management framework that ensures consistency in pricing and discount decisions.
Is there an API?
Partners:
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Book a demo appointment
I am pleased to present our Pricing Engine
to demonstrate personally
Patric A. Huber, Ph.D.
