Written by Thomas Mutsimba, an author, a Risk Management Professional. Thomas is an author with special interests in advanced actuarial analysis and advanced forensic analysis
Actuarial data modelling has been covered a great deal in the series of articles I published on this platform. I have started off with a very high level overview. Actuarial data modelling is regarded as complicated, requiring very highly skilled people to carry out the nudging task of solving problems in the markets.Now, here on this article I focus on demystifying Actuarial data modelling to proffer a view to the enterprise risk management audience and the audience at large. Demystification of actuarial data modelling will be done at a unique level.
What is Actuarial data modelling from an Actuarial analyst view? Actuarial data modelling from an Actuarial analyst view is modelling that focuses on examination of modes of degeneration of model input fundamentals in business optimization architectures.Why is business optimization crucial in the quest of an analyst? The main purpose is to test and prove that the optimization imperatives are working best to achieve goals encapsulated in the strategic imperatives of the organisation.
Now this definition has one missing synonym. The synonym being referred to is the quantum risk universe that interacts with the business optimization initiatives aimed at ameliorating the effects of opportunity cost forgone as a result of certain decisions made by the organization. The Actuarial analyst concerned has to be wary and be ready to recommend quantum risk defined bases that strike at least strategic imperative-input fundamentals balance. The account of the role of the Actuarial analyst of the future must be backed by quantum driven and tested methodologies that stand the impending risk universes.
The analyst must never forget that actuarial data does not perspire on its own or independently. The vernacular tab of data perspiration possibilities gives impetus to demystification of binary data algorithms. Why are we referring to binary data algorithms? Binary data algorithms are methodic meaning algorithms which are transformative in two sets of characteristics. The characteristics are:
- Algorithm determination quantum base
- Formulative datum base perspired in high income entities
Algorithm determination quantum base
This refers to deep seated programming language that documents advanced algorithms meant to drive the technology powered evolution of actuarial data modelling. How does it work? It works based on the evolution of data to minute advanced components. The minute advanced components are basically the degeneration of actuarial models to where the business decision challenge is. The Actuarial analyst role has been compacted and blanketed under a narrow view of business science. Business today is in need of highly astute and cognitive thinking driven analysts. Organisations today are optimally lacking because of deficient business optimization models. Entities are outpaced by other entities because of the astuteness of blossoming entities in this area. The algorithm quantum base forms three phases and they are as follows:
1.Quantum base genesis
The genesis of a quantum base will be defined from the velocity driven motion censorship population from business intelligence statistics. Velocity driven motion censorship is a tool that improves and creates opportunities for a product or a service model development at an accelerated pace. Enterprise risk management reports must be able to articulate actuarially determined data driven input fundamentals as reportable indicators that are powerful. Boards and governance structures must be educated on the impacts and volume-powered data population in the business optimization mixes.
2.Quantum bases genesis is the future
As opposed to just indexing input imperatives for determining the evolutionized results without equipping governance structures within boards with education. This is the only way business can improve coupled with initiatives to improve corporate governance structures.
3.Quantum bases genesis is advanced
Those interested in Actuarial science and how it powers the generic architecture of data models. No man can move alone; let alone be an island and aspire to grow without interaction with the universe. Quantum bases genesis will be explained further in the the future issues of articles with a focus on Quantum risk management.
Formulative datum base perspired in high income entities
A formulative datum base perspired in high income driven entities is a censorship algorithm characteristic that degenerates through the populative architecture of data perspiring through a business model optimization input fundamental . The input fundamental perspires based on motion censored decision when quantum risk analytics informs the data model optimization directional strategy.
Generally formulated data algorithm policies will posture this motion sensorship inspired strategic imperative. Characteristically the status quo in today’s actuarial data modelling algorithms written in languages such as python do not have these advanced sense of algorithms.
For so stated, every Actuarial analyst through training and development instituted by Institutes and Faculties of actuaries must change their focus. Analysts and actuaries will become irrelevant if they are not equipped in this manner. This is even the same scenario with other professions whose tenets are driven by actuarially determined data.
The focus under this section has been targeted on high income entities. Is it because small to medium income entities do not fall under this formulative datum base? They do fall under this base but high income entities whose investments in algorithm developments for data modelling are the most hit by deficiencies in business optimization models.
Product or service optimization models driven by actuarially determined will face these developments alluded to. The notion of technological velocity is a dangerous risk investment scenario. What does this mean? It means technology is a trigger functionary coordinating factor in scenarios among the motion censorship tenet. Generally it is a done deal, data centers hosting business data will need massive integration capabilities.
Capabilities phased approaching data modelling is the generational transformative nature. Nullifying the current status quo of the actuarial analyst job will be the evolutionary nature of data coming from legacy systems.
The Actuarial analyst roles and responsibilities
The Actuarial analyst is responsible for the following:
- data architecture formulation triggering actuarial reporting and quantum based risk analytics;
- deceleration of input fundamentals in approved actuarial models to strategically position the entity for profitability and sustainability;
- formulation of supportive actuarial architectures informed by motion censorship data development algorithms.
- product and service model optimization fundamentals alignment to injected actuarial modelling scenarios meant to give stress asymmetry tenacity.
Disclaimer: All views expressed in this article are my own and do not represent the opinion of an entity whatsoever, with which I have been, am now, or will be affiliated with.
informationsecactuarialyardanalysis 