METHOD
METHOD
How we work.
We have collected and structured cash flow management experience from a decade and derived mathematical algorithms from it. Our mathematical and statistical methods show that potential savings can be predicted with a high degree of probability from transaction data.
Based on this, we have developed an analysis method that includes qualitative and quantitative methods. This allows us to see within a very short time the size and areas in which your potential lies.
In the analysis, our method guarantees us record-breaking throughput times in the 6 cash flow-relevant areas: accounts receivable, accounts payable, organization, financing, investment, and the interfaces to the banks.
CASHFINDER METHOD: Assessable utility. Exact calculation. Structured implementation.
60 - 95 reports show us possible potential...
From the thematic work area "Cashflow" we create around 60 - 95 reports with over 400 mathematical algorithms. This process is only possible by systematically evaluating a large amount of data. We work intensively with the methods of stochastics, which combine probability theories and statistics. Our reports are about finding out whether the probability of the event happening is close to 1 (probable) or close to 0 (unlikely). We present the results of our scientifically based method, which has been made usable in practice, in just one working day.
In the history of mathematics, statistics was initially referred to as "collective research" and developed methods to systematically analyze empirically collected data. This includes checking the data with regard to their relevance as well as examining the relationships between certain pieces of information and information from the environment that needs to be supplemented. It is precisely in this field of tension that we are still moving today. When it comes to probabilities and statistical evaluation, however, one mathematical law is of particular importance.
The law of large numbers
Francis Galton, one of the oldest statisticians, called it "the supreme law of unreason" and wrote more than 200 years ago: "As soon as one sizes a large mass of random elements of a set, it is found that there is an unexpected and most harmonious regularity in was hidden from them.” In summary, the law of large numbers justifies the statement that the mean of any number of measurements is more reliable than any individual measurement. Jacob Bernoulli went on to formulate a special case of the law and argued that the relative frequency can be used to estimate unknown probabilities.
In the course of the rapid development of data processing, this long-known mathematical law unfolded unimagined dimensions. At the same time, the availability of more and more extensive computing capacities and the associated development of adequate algorithms mean that the statistical models used for data analysis are becoming more and more complex.
Big Data
Derived from the term large data in English, "Big Data" is now a synonym for dealing with gigantic, complex, rapidly changing amounts of data. For companies, everything that is summarized under the keyword Big Data promises quick knowledge gain and thus tangible competitive advantages. Increasingly powerful computers and corresponding algorithms now make it possible to collect, store, systematize and statistically evaluate huge amounts of data. An example of the evaluation of a multitude of available data are the ratings of analysts.
Based on a comprehensive, systematic analysis of large amounts of data, listed companies are evaluated, from which buy or sell recommendations for the corresponding shares and securities are derived. Both internal company data, such as the structure of the company, assets, investment income, liquidity, etc., and external surveys, such as the behavior of other market participants or changes in the legal framework, are used for this purpose.
As already noted, however, the large amounts of data available alone are no guarantee for generating reliable information. Rather, the quality of the statements and forecasts made will always depend on whether the data has been collected statistically cleanly and systematic errors have thus been avoided, whether the data used has been wisely selected and adjusted or reduced in accordance with the question at hand, and whether the results have been correctly evaluated and interpreted become.
By systematically analyzing existing databases using statistical methods, CASHFiNDER is able to uncover hidden connections and patterns and thus quickly identify potential for cost optimization. These assumptions are checked in phase 2 by the presence of the project manager on site and formed into a statement.
White-, Black- und Greyboxmodelle
Mathematical models enable an accurate representation of reality by precisely identifying the factors that are crucial to the processes under study, while abstracting from all non-relevant factors.
So-called white box models are used when the internal structure of a system is known, but is largely hidden for the analysis. If only the interactions of a system can be recorded without knowing its internal structure, black box models are used. Most of the time, some information about the system is available and some is not; certain interactions can be recorded, others not. In all of these cases, a gray box model is formed, which is usually completely sufficient to depict the essential data. Processes are described by algorithms in such a way that they can be reproduced by the computer. Algorithms are therefore a perfect tool for discovering previously unknown relationships within large amounts of data. Clusters (groups) can be identified quickly, outliers (deviating data sets) are identified accurately. In this way, we are able to reduce the amount of data, which simplifies the evaluation without distorting it.
Savings in the average double-digit percentage range...
With the CASHFiNDER method, we can regularly achieve savings in the double-digit percentage range for our customers. This method will also lead to top results in your company. We guarantee that.
You decide to what extent you continue to benefit from our results after our analysis, because only a calculable benefit is a calculable advantage. The measurable success of our national and international customers is therefore the focus of our actions.
Because we only get our fee if you are successful. To do this, your monetary performance must be optimized in an objectively measurable area. Then we CASHFiNDER will live up to our name. And then, and only then, will we share in the success that has been achieved.
COMPLIANCE
CASHFiNDER have a strong focus on compliance. That's why we only work with certified applications.
