About QMetrics

• How to cluster your customer base to adapt your products/services and (E)–marketing in an optimal way?

• How to construct an optimal asset hedge portfolio to reduce the market- and insurance risk resulting from the liabilities towards the policy holders? (ALM)

• How can ‘big data’ consisting of customer and product data be used to recognize patterns in consumer behavior?

• What is the optimal price formula that a telephone company can use given the data about the call behavior of their customers?

How to use mathematic algorithms to optimize the profit on air plane tickets?

• How to predict what type of customers will buy what kind of products given data about your customers and products?

• How can the purchasing habits of your online customers be predicted using their online behavior?

• How to predict the probability of default by your customers to avoid default and fraud based on the payment history of your customers?

• How can regional car sales be predicted using data such as macro-economic variables, sales of competitors, seasonal effects, fiscal regime etc.?


These are all examples where data is key. Nowadays, enterprises are processing data in huge volumes. Data innovation and data science evolve at a very high speed. Tons of data are waiting to be revealed. It is QMetrics’ believe that data driven strategic decisions are getting more important for enterprises.
QMetrics is an econometric consultancy firm mainly operating in Belgium and the Netherlands. QMetrics aims to support organizations that are facing complex challenges by providing new context-relevant insights to guide decisions. These insights will be obtained from available data through the application of advanced and specialized econometric models. Overall, the goal is to provide information that can really make a difference in organizational outputs and achievements. QMetrics possesses the capacity required to answer all of the questions above. The above-mentioned complex cases are present in every industry. However, since each industry has its own dynamics and characteristics, QMetrics will provide solutions that are tailor-made. At QMetrics, we focus on a diverse set of fields. Some examples:

• Financial Risk Management
• Insurance Risk Management/Actuary (Solvency II)
• Credit Risk Management (Basel directives, IRB modelling)
• Customer Relationship Management (CRM)
• Asset Management – Portfolio Optimization
• Predictive Modelling
• Market Research
• Big Data analytics
• Etc.

QMetrics Process


Problem definitionProblem definition

QMetrics comes to understand the essence of the problem through interaction (e.g. Discussions and interviews) with the stakeholders of the company. In this joint venture, the client is the one with business know-how. He knows his products, the market and the accompanying dynamics best. QMetrics provides support using its modeling and quantitative expertise.
QMetrics believes that the models are just tools to approach the problem. It is at least as important to really gain insight into the business and their challenges.

requirementsSpecifying requirements

The problem will be broken down into greater detail. The following questions will be answered:

– What’s the final goal? What should the model be able to calculate?
– What are the (technical) requirements of the model?
– Who are the stakeholders, internal as well as external?
– What are the requirements of each stakeholder?
– What are the prior conditions regarding human resources, time, money and IT?
– Which software is required to execute the model?

dataData analytics

In this step the relevant data will be collected and analyzed. This can be internal data as well as external data. Using data mining techniques, QMetrics will examine patterns and evolutions in data then choose a suitable model. The challenge here is to distillate the relevant data from the raw data and translate this into useful information. The existing methods and processes will also be evaluated during this phase.


The problem will be translated into an econometric model which gives the best representation of reality. The complexity of this model depends on the nature of the problem and both linear and non-linear models will be considered.

In general, econometric models may be classified into forecasting- and optimization models:

Forecasting models/Predictive models predict a certain variable based on the historical relationships among several variables. This can be cross section or time series models (ARIMA) or a combination of both. E.g.: Prediction of salary within a region using gender, education, job categories, etc.

Optimization models are used to optimize for example profit, costs and risk. Examples of optimization models are segmentation (cluster), decision and hedge models.

Examples of optimization models are the following models:

Decision models. E.g. Profit on sales of plane tickets can be maximized by using decision rules on ticket tariffs. Using these rules, an airplane company can come up with algorithms to continuously adjust the ticket tariffs based on changing demand and supply.

Hedge models. E.g.: Insurance companies can reduce their market- and insurance risk resulting from their liabilities toward policy holders by constructing an asset hedge portfolio consisting of derivatives.

Segmentation models. E.g.: Segmentation of the customer base to personalize direct marketing to maximize profit and minimize marketing costs.

In this phase, the model will frequently be presented to the target group and will be fine-tuned when necessary. In particular, the model will be presented to the end users because it needs to be understandable and intuitive for them.


In this phase, the implementation will take place. As far as possible, the existing software of the company will be used.

QMetrics will also take care of the relevant documentation. This may include from technical specifications to an operation manual.


When the model is part of the operational process, one needs to test the quality of the performance of the model on a regular base. The model needs to be back tested on a frequently base to check whether the model still meets the predetermined performance criteria.

Depending on the performance of this backtest, the model will be recalibrated.


QMetrics is also interested in taking on the implementation phase as a separate service; the so-called implementation-only service. QMetrics has the expertise and experience to implement (complex) challenges with common software and/or open-source software like Excel, VBA, Access (SQL) and R Programming. The advantage of the use of software which are present in almost every company is that no fundamental and expensive ICT-interventions are necessary. The existing processes can be automated and made more efficient so companies can focus on their core business. This implementation-only service it aimed at mainly smaller companies.

  • Price offer tool
  • Tool to manage the supply of your products
  • Planning tool for working schemes and registration of leave hours
  • Tool for management of debtors
  • Customer relationship system; Tool in which the following can be managed:
    • Unpaid invoices (see tool for management of debtors)
    • Log file of customer contacts
    • Overview of purchased products
    • Status overviews (status of ordered products, etc.)
  • Financial dashboard which gives a clear insight into the key financial figures of your company

About us

QMetrics is founded in 2014 by Mienvu Dang. Mienvu Dang graduated in the studies ‘Econometrics: Quantitative Finance’ at the Erasmus University at Rotterdam. Following his studies, he worked in the following sectors:

– Insurance; Risk Management/Actuary department >> Pricing-, market price- and hedge models
– Bank; Credit Risk Management department >> Credit Risk Models (PD and LGD models)
– Energy; Asset Management department >> Pricing-, decision- and energy price models

The common factor in these experiences is the quantitative approach to complex challenges using mathematical, statistical and/or econometric models. Every sector has his own dynamics, products, consumer needs, legislation, history etc. In order to provide effective solutions, it is necessary to really understand the industry.

In 2016 Xuan Kim Trinh joined QMetrics. Xuan Kim Trinh graduated in the studies ‘Commercial Engineer’ at the University of Antwerp and ‘Controlling’ at Avans Plus in Breda. She has ten years of experience in the financial industry in different roles as a risk professional, business analyst/consultant and business controller. However, it were not the financial topics that were triggering her, but the complexity of the content. Searching for solutions to complex problems and questions through development of analytical and mathematical models (mainly in Excel/VBA) and translating it into understandable management reports/dashboards became her expertise and major interest.


For further information contact us at:

Phone: +32 468 164 254 (Mienvu Dang)

or + 32 475 797 430 (Kim Trinh)


E-mail: info@qmetrics.be