Jan 1, 2017

Happy Risk New Year 2017

Happy New Year to all Actuary-Info readers.

The year 2017 will be the another year that'll empower us to develop new insights on risk management. Driven by economic turbulence and desperate rule-based regulation we will probably keep trying to capture, control and even eliminate risk, instead of trying to understand and anticipate risk.

Dutch Insurance Merger
At the end of 2016, two large Dutch insurers - Nationale Nederlanden (NN) and Delta Lloyd (DL) - decided to go ahead with their merger. Formally it's called a take over of DL by NN.

Driven by a declining DL-Solvency-II rate and supported by the concerned Dutch regulator (DNB), DL now finds shelter within NN. Besides the take over price of € 2.5 billion, NN Group faces a decline in solvency ratio from around 250% (pre-merger; Q2 2016) to 185 percent 
(post-merger, Q3 2016).

A strong merger (background) driver is
DL's expectation: "Delta Lloyd's 4Q16 Solvency II ratio is to be adversely affected by the LAC-DT review by DNB, the possible removal of the risk margin benefit of the longevity hedge and adverse longevity developments."

However, keep in mind that 'all' life insurance companies with 'long tails' have a serious (business case) problem. A problem that's not only solvable with money (capital), but necessitates the formulation of a new strategy that goes beyond just "cost control".

As low interest rates will continue and Solvency-II requirements will only increase, more mergers of life companies (with long tail risks) are to be expected.

When is a merger the right solution?
Although a merger often looks like a perfect solution for 'the problem', it not always is.....

Several studies estimate the failure rate of mergers and acquisitions somewhere between 70% and 90% (at least more than 50%).

The most common general merger fallacies and attention points are addressed in a McKinsey presentation:

When a merger or take over is considered, first check the next key-points from a risk perspective :

1. Strategy: Bigger is not always better
It's surprising how inherently correct analyzes always lead to 'bigger' is 'better', while we know that "bigger" contributes to 'too big to fail ',' decreasing cost efficiency ',' less flexibility (less agile) and 'less innovative capacity ' (like Fintech applications).

For successful mergers or take-overs, 
just applying traditional capital management (and Solvency II rules) just isn't enough. In all cases a well defined checked and supported 'new strategy' (plan) including a strong 'business case', are a first requirement.  

Always investigate these (adverse) merger effects and concept new strategy in the due diligence phase of a merger.

2. Increasing complexity effects
Is the change in complexity (IT, communication, products, distribution channels, etc.) measured and addressed in the merger/'take-over? If the complexity increases beyond certain  levels, targeted cost reductions may not be met. Often these costs are underestimated.

Always try to measure and address complexity
 in the due diligence phase of a merger.

3. Consistency 
Always check upon the consistency of (financial) analyses. If certain (actuarial) analyses, audits or valuation methods are only applied (one-sided) for the to be acquired company and not  for the acquiring company, consistency clearly fails and merger conclusions are probably biased.

Whether it's a "takeover" or 'merger', or how the power in the board is managed, doesn't really matter. Both companies should be compared on the same basis.
Always check on consistency in the due diligence phase of a merger.

Success with risk is on your merger-table in 2017 !! 

- Bigger is better wine glass
The Big Idea: The New M&A Playbook
Mergers and Acquisitions failure rates and perspectives on why they fail
NN Group and Delta Lloyd agree on recommended transaction
DNB esearch; Bikker; Is there an optimal pension fund size?
DNB examination into complex IT environments
70% of Transformation Programs Fail - McKinsey
McKinsey: Where mergers go wrong

Oct 2, 2016

Leadership and Actuaries

It's more than a year now, since I've posted a blog at Actuary-Info. During this year I fully focused on the market launch of the Fintech startup Symetrics. Now, with more time in pocket I'll pick up 'actuarial blogging' again.

Last summer Reinier Roosen, Managing director of FTE in the Netherlands, asked me to give a presentation about Leadership and Actuaries at the yearly seminar of 'Actuarieel Podium' (translated: 'Actuarial Stage') on september 27, 2016 in Zeist, the Netherlands.

Incomplete data
One of the key slides of this presentation discusses the power of actuaries to cope with incomplete data (missing information) in big data sets. here it is, take good look!

Do you think something's missing in the above slide?

Think again please....

Altough a presentation is in no way ever represented by the corresponding slides (slides are always just supportive), I would like to give you an impression of my presentation in PowerPoint style.

In the coming blogs I'll discuss the main topics that are mentioned in this presentation, more in depth.

Main Messages
Summarized my main messages in this presentation are:

  1. Take more responsibility: Socially, Personally
    • Widen the area of influence
    • Grow and spend more time on your personal and professional network
    • Intensify cooperation with other disciplines
  2. Strengthen ‘Soft Skills’
    • Communication skills, power to convince, master principles, self-reflection
    • Empathy power: understanding social dynamics, stakeholders & clients
  3. Innovation
    • Build up new client-central products with new adequate regulation principles
    • Innovation can be stimulated by making implicit conditions, explicit
  4. Adjust professional methods and education
    • Develop new ‘board decision models’
    • From ‘Believes’ to ‘What If, Given Conditions x|y|x’
    • From ‘Long term uncertain estimates’ to ‘Short term recipes’
    • Including systemic, parameter and model risk
    • Anticipating on economic and behavioral effects and scenarios
    • Based on early warning indicators instead of trigger points

Final Presentation
Enjoy the presentation and give me feedback at jos.berkemeijer@gmail.com.

The presentation is best (better) viewed:
- on the Powerpoint app at: https://goo.gl/IgmGh5  
- at Slideshare at https://goo.gl/ZT4wWM
- as a movie on Youtube: https://www.youtube.com/watch?v=B4StprG3YaI

Jul 9, 2015

Optimal Pension Fund Investment Returns

How to manage a pension fund investment portfolio in economic uncertain times and shifting financial markets? Let's try to answer this question from a more practical point of view instead of a pure scientific approach......

Historical Performance
Let's take a look at the performance of two large and leading Dutch pension funds

First of all we take a look at the historical (1993-2014) yearly returns of both pension funds and try to figure what n-year moving averages results in a stable and mostly non-negative yearly performance.

Smoothing Returns
If our goal is to 'smooth' returns to pension fund members and to prevent negative returns as much as possible, a '3-year moving average return approach' as basis for sharing returns to pension fund members, could be a practical start. 

In this approach, a single maximum cut of around 3.3% is largely compensated by the returns in other years as the next chart of  '3 Year Backward moving Average Yearly Return' shows:

Of course if we want to protect pension members also against systemic risk and crises, an additional investment reserve of around 15%-20% would be necessary.

The  next slide gives an impression of the effects of a 10 year moving average approach. I'll leave the conclusions up to the readers. of this blog.

Main conclusion is that the analysed pension funds ABP and PFZW are able to generate a relative stable overall portfolio return over time. They manage to do so, despite the fact that their liabilities yearly fluctuate as a result of the fact that they have to be discounted by a risk-free rate. 

A risk free rate that itself isn't risk free at all and - on top of - is continuously 'shaped'(manipulated ) by the central banks to artificially low interest levels.

Managing Volatility instead of Confidence Levels
A strategy based on managing the funding ratio of a pension fund given a certain confidence level and given the actual method of risk-free discounting of liabilities, is doomed to fail in a low interest environment. Discussions about confidence levels are also a waste of time, as long time confidence - at any confidence level - eventually will turn out to be an illusion.

As long as pension funds are able to demonstrate that that they are able to manage and control the volatility of their assets within chosen limits (risk attitude 1; e.g. 10%) and within a chosen time horizon 
(risk attitude 2; e.g. 20 years) , they will be able to fulfill their pension obligations, or to timely adapt their chosen risk-return strategy to structural market changes.

How to curb volatility?
Managing the volatility of an pension fund investment portfolio within a certain risk attitude is one of the greatest challenges of a pension fund board.

In short, the traditional instruments to curb volatility are:

  1. Diversification
    With the help of diversification the asset mix of a  pension fund can be tuned to optimize long term risk-return in relatively 'normal' market circumstances.
  2. Capital Requirements & Management
    By defining and maintaining a well quantitative risk-based capital and investment reserve policy, a relatively smooth yearly return available for pension fund members can be achieved in a systematical risk environment.
  3. Economic Scenarios
    By studying portfolio outcomes under different economic scenarios, a short term 'best fitting' near future volatility asset strategy can be developed.
  4. Trigger points
    By defining asset portfolio actions that will 'fire' once particular trigger points of specific asset classes are met, all measures based on 'damage control' are in place.
Unfortunately the above measures all fall short in case of systemic market events.

In case of crises, like the current Greece crisis, agent based models, also called behavioral models, can help to manage systematic volatility.

Behavioral Asset Management
A way to minimize systemic volatility in an investment portfolio is to apply new 'Behavioral Economic Stress Test' models. These kind of tools, as provided y a FinTech50 2015 company called Symetrics, enable pension boards and investment managers to model and to anticipate crises.

More is explained in the next short presentation "The value of economic scenarios from a risk perspective" by Jos Berkemeijer, one of the four managing partners of Symetrics.

Used Links
- Agent based Models
- Behavioral Models by Symetrics
- Spreadsheet wit data used in this blog
- Presentation: The value of economic scenarios from a risk perspective