.

**Overview**

There are huge numbers of variants of deep architectures as it’s a fast developing field and so it helps to mention other leading algorithms. The list is intended to be comprehensive but not exhaustive since so many algorithms are being developed [1] [2][1],[2].

- Deep High-order Neural Network with Structured Output (HNNSO).
- Deep convex network.
- Spectral networks
- noBackTrack algorithm to solve the…

Added by Syed Danish Ali on July 26, 2016 at 5:00am — 2 Comments

While Deep Learning has shown itself to be very powerful in applications, the underlying theory and mathematics behind it remains obscure and vague. Deep Learning works, but theoretically we do not understand much why it works. Some leading machine learning theorists like Vladimir Vapnik criticise Deep Learning for its ad-hoc approach that gives a strong flavour of brute force rather than technical sophistication. Deep Learning is not theory intensive; it is empirical based more (hence…

ContinueAdded by Syed Danish Ali on July 20, 2016 at 5:00am — 3 Comments

This post highlights a number of important applications found for deep learning so far. It is well known that 80% of data is unstructured. Unstructured data is the messy stuff every quantitative analyst tries to traditionally stay away from. It can include images of accidents, text notes of loss adjusters, social media comments, claim documents and review of medical doctors etc. Unstructured data has massive potential but has never been traditionally considered as a source of insight before.…

ContinueAdded by Syed Danish Ali on June 26, 2016 at 5:00am — No Comments

**Overview**

*“The only function of economic forecasting is to make astrology look respectable***”** John Kenneth Galbraith

Predictive modeling and traditional ratemaking is an exercise of forecasting the future, whether directly or indirectly (indirectly as generalizing historical lessons to the future). But is such forecasting so hopeless as being same as seeing into a crystal ball?

The advantage of data scientist and actuaries is their close in contact with…

ContinueAdded by Syed Danish Ali on June 20, 2016 at 2:30am — No Comments

**Shakespeare and Fuzzy Logic [1]**

*There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy. - Hamlet (1.5.167-8), Hamlet to Horatio[2]*

Shakespeare teaches us in this Hamlet quote that reality is much more complex than our mental projections and understanding. Reality is fuzzier than we would care to think. Although introducing subjectivities to modeling seems to harm the…

ContinueAdded by Syed Danish Ali on June 20, 2016 at 2:24am — 1 Comment

We should attempt to creatively synthesize the many pluralistic approaches as well as focus more on synergistic interpretation of findings of these pluralistic researches.

We can recognize that though we cannot precisely predict black swans but forecasting emerging liabilities and their ratemaking can be a professional-character building experience in itself where we train to be better evolvers rather than better predictors alone.[1]

We can…

ContinueAdded by Syed Danish Ali on June 20, 2016 at 1:44am — No Comments

This post highlights the various value-additions that machine learning can provide to actuaries in their analytical work for insurance companies. As such, a key problem of swapping specific risk for systematic risk in general insurance ratemaking is highlighted along with key solutions and applications of machine learning algorithms to various insurance analytical problems.

*‘In pricing, are we swapping specific risk for systematic risk?’ [1]*

The…

ContinueAdded by Syed Danish Ali on June 20, 2016 at 1:30am — No Comments

Up till recent past, the artificial intelligence portion of data science was looked upon cautiously due to its history of booms and flops.[1] In the latest stream of events, major improvements have taken place in this field and now deep learning, the new leading front for Artificial Intelligence, presents promising prospect for overcoming problems of big data. Deep learning is a method of machine learning that undertakes calculations in a layered fashion starting from high…

ContinueAdded by Syed Danish Ali on June 20, 2016 at 1:15am — No Comments

__Review__

The challenges of big data can be captured succinctly as follows[1]^{,[2]}:

- Volume; ever increasing volume which breaks down traditional data-holding capacity
- Variety; more and more heterogeneous data from many formats and types are bombarding the data environment
- Velocity; more and more data is time sensitive now; frequent updates are taking place instead of relying on historical old data and…

Added by Syed Danish Ali on June 20, 2016 at 1:03am — 1 Comment

**Underwriting Cycles [1]**

In this case study for Complexity Science, we aim to show its value addition through agent based modeling of an important insurance problem, i. e, underwriting cycle. Underwriting in Property-Casualty/General Insurance is where insurance underwriting follows and mimics the Economy and its cycles of boom and busts. These soft and hard market swings are a key source of challenge and volatility to insurers. The main value addition of…

ContinueAdded by Syed Danish Ali on June 20, 2016 at 12:41am — 2 Comments

**Complexity Science**

It is quite difficult at first to precisely define ‘Complexity Science’. It is a new perspective of methodology and modeling approaches that are based more on reality than assumptions. Quite simply put, Complexity Science is a new way to grasp and manage reality. It does not study systems in isolation like gambling dice or planetary motion only. It studies the complex, holistic, inter-connected reality in which we actually live such as financial stock…

ContinueAdded by Syed Danish Ali on June 20, 2016 at 12:31am — 5 Comments

Topology is the mathematical study of the properties that are preserved through deformations, twistings, and stretchings of objects. Tearing, however, is not allowed[1]. Topology can be used to abstract the inherent connectivity of objects while ignoring their detailed form. Put simply, Topology is a mathematical discipline that studies shape and assumes that shape has meaning[2]. This post discusses topology’s applications in finance and insurance. While…

ContinueAdded by Syed Danish Ali on June 20, 2016 at 12:30am — 3 Comments

- On-going Developments and Outlook for Deep Learning
- Limitations of Deep Learning and strategic observations
- Applications of Deep Learning
- Inspiring Imagination In Data Science: Qualitative Profiling
- Shakespeare and Fuzzy Logic
- Modeling Meditations
- Machine Learning: An Analytical Invitation to Actuaries

- Sweet and Short Introduction to Complexity Science
- Limitations of Deep Learning and strategic observations
- Guide to Deep Learning
- Key tools of Big Data for Transformation: Review & Case Study
- Applications of Deep Learning
- Machine Learning: An Analytical Invitation to Actuaries
- A Different Breed of Mathematics: Topology

- A History and Timeline of Big Data
- AI voice technology has benefits and limitations
- Strong data governance frameworks are fuel for analytics
- Top 12 most commonly used IoT protocols and standards
- What is the status of quantum computing for business?
- How parallelization works in streaming systems
- An Eggplant automation tool tutorial for Functional, DAI
- Circular economy model enables sustainability and resilience

Posted 29 March 2021

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