RiskButler is for all organisations that have financial exposure from any source (product type).
RiskButler is data-driven and extremely advanced: machine learning and AI is used and there are a long range innovative system features.
It is a cloud (or in-house) service for financial portfolio optimization in terms of current and future portfolio composition, construction, valuation, performance, risk and compliance.
Contact UsThe sometimes wild nature of financial markets provides a well-known challenge to understand and describe.
Many still stick to mostly human driven financial analytics but that is a waste of talent and money.
Our computer-based models can do amazing things that humans cannot.
However, it is still best to have a skilled person to control and pick the best possible computer result to base important decisions upon.
RiskButler.com uses different models to describe and immitate the nature of financial products and markets.
A "classical" model in RiskButler is at its core described by so-called stochastic processes, a method and approach that is (still) required by e.g. financial regulators in regulation of the financial industry.
We now also offer models using artificial intelligence (AI) which are based on another machine learning process than the one used for for stochastic processes.
With AI it is the computer algorithm that finds and describes the movements of the financial market while with stochastic processes it is basically an advanced mathematical & statistical regression analysis that is in play.
AI models can keep improving with more data (in many dimensions) while the classical methods do not after a certain point.
Two extremes of information about the future are (1) near full certainty i.e. everything is nearly known, and (2) complete uncertainty i.e. everything is random.
Reality is normally somewhere between these two states depending on the context, concrete time and situation.
Knowledge about the future enables businesses to make better decisions for increased prosperity for the business and for society.
There are many use cases for financial market forecasting.
RiskButler is about forecasting and more.
Understand how future movements in financial markets can affect your financial portfolio or company’s bottom line ("portfolio"), both positively and negatively.
Make informed risk exposure hedging decisions to avoid unwanted future losses in earnings and cash flows.
Ensure transparent risk analysis of the entire portfolio for both internal and external stakeholders.
Focus on core competencies while having control of the financial risks and potentials (upsides).
Ensure that the portfolio's risk exposure is kept within the economic capacity and objectively stated risk appetite of your entity.
SignupIf your organisation has financial exposure then we can help you manage the financial exposure better.
All kinds of industries and organisation types can strongly benefit from RiskButler services.
If customization is required this will be done.
All product types are (or can be) supported and these can be assets or liabilities.
Examples of products are cash, foreign currency, deposits, loans, bonds, swaps, equity (shares), forwards, futures, options, derivatives, structured products.
You can use the online web-application and/or your organisation can utilize our server-to-server APIs.
The web-application user interface is designed for most ease-of-use while retaining the high level of advancedness: however all complicated matters are managed under the hood to the highest degree.
Data communication and activities are logged for optional audit & compliance. Documents (files) are generally not deleted but versioned.
The system is built on the basis of ISO currency, country, and language standards; consitent field definitions and names; international web standards (www.w3.org), programming language standards (www.ecma-international.org), well-established AI frameworks (tensorflow.org), among other.
Once the portfolios have been defined, the system can automatically make the required calculations either on a periodical & automated basis, or in inter-active mode by user through web-browser.
The system automatically calculates and includes all the complete analytics & diagrams in the user-interface or reports.
Automated email alerts can be sent in connection with periodical tasks & services.
We provide interfaces to a selection of third party market data providers. Data can also be intraday data.
You can use your preferred market data providers: this data can be fully integrated into RiskButler through APIs and uploads.
Wanted and required data transformations can be defined through Javascript functions and stored, the system will then use these transformation rules automatically.
You can define new price indexes for further analysis, valuation, risk assessment etc. or for use in portfolios as effectively new product types.
With lines & limits control each part in the trading process gets concrete financial risk limits that they must stay within, else this is immediately reported upwards in the organisation and the entities must act to bring down their excess risk taking.
The term "Line" refers to the actual type of metric that is being measured, this could for example be a simple trading volume line for at specific product, or it could be a specific risk line, or another kind of line. The "Limit" term refers to decided boundaries placed on the lines, typically a simple maximum limit amount.
Market risk, counterparty credit risk and other risk calculations can be made for legal purposes.
This can e.g. be investment product companies such as UCITS for required reporting (see also: Riskdocuments), or for banks' capital adequacy risk reports.
We use world class third party cloud centers (google cloud) and you can have a choice of the preferred cloud locations city-wise.
Optionally, you can run riskbutler in-house (on-premises).
Our cloud APIs are generally auto-scalable, so we can handle any load you need.
We provide full access to all your own data and this data can be downloaded.
The system is a fully dynamic and near real-time system, meaning that all system settings and data available at any given time is used to generate fully up-to-date analytics and reports.
The system time is internally programmed in milliseconds, so the system can theoretically deal with time series down to a time interval of one millisecond, although normal practice is still around 24 hours as the time interval.