The Slope Blog

Slope Software, and the SLOPE platform, were born out of frustration with poor user experience. Along the way, founders Andy Smith and Taylor Perkins have learned much about innovation, leadership, and how to do great work. In this article, we’ll share some of those lessons and offer perspectives on how actuaries might apply them. Before […]

“No-code” and “Low-code” software applications are very much in vogue these days. For actuaries, there is a spectrum of options from do-it-yourself to everything-done-for-you. What are the positives and negatives of such options for actuarial software applications? We break them down in this article to give you helpful perspectives when you must choose. First, let’s […]

Deep Blue, Alpha Zero, HAL 9000, SkyNet, and… your reserve model? The idea that you’re facing off against a multi-billion dollar silicon-based mind capable of destroying humanity (or just winning every chess game ever) may be a little far-fetched. But a growing number of actuaries have, in the very recent past, run into artificial intelligence […]

It's easy for actuaries to get caught up with precision when they should be using system thinking.

Actuaries can improve their actuarial model management by applying product management principles.

In order to take advantage of new technologies, and adequately satisfy new requirements, actuaries will need to develop a "culture of innovation" rather than performing a "project of modernization". This article provides tips to make that happen.

Actuarial modelers need to ensure that all the components of their model are right before they depend on model outputs for business decisions. This article provides tips and strategies to help modelers uncover potential errors within and avoid problems in the future.

Actuarial development projects need non-actuarial perspectives to help achieve superior results. Enable and empower those teams with better tools and communications.

Actuarial modernization is underway at many insurance companies. Without proper planning, most of those projects will be unsuccessful. Actuaries must ask the right kind of questions when planning or evaluating future systems to get better results.

Actuaries working on lower-level tasks (such as manual data processing) aren't performing as well as they could. This article explains how to get more "top of qualification" tasks correctly assigned.

Actuarial specialisation can be a challenge to producing superior results. Bradley Shearer offers an international perspective on why actuarial teams need both close inspection and wide range visionaries. He also cautions against trusting experts too widely and encourages diversification in skill and career development.

With cloud technology, actuaries can efficiently scale up or down their use of computing resources to match their needs. See how with a clear example and a specific use case.

Slope professionals will be featured in a cloud computing webinar in February. Actuaries interested in understanding how cloud technology applies to their work should register and attend.

The investment world has had a busy week. We offer a lesson on perspective from the trading around GameStop stock. What's adverse for one may be beneficial for another.

Good actuaries need more than technical skills. This guest post by Rob Stone, FSA, MAAA, gives an experienced actuary's perspective on how to recognize when defensiveness may be holding you back.

The Actuarial Wasted Time Survey Results for 2020 are presented. Actuaries rank Data and Model Management tasks as more impactful than Hardware and Software Management tasks. Read more by downloading the full survey.

A quick wrap-up of some highlights of the year gone by, including company announcements, functionality enhancements, and saving clients loads of time.

Software development practices such as different environments, concurrent documentation, and expansive testing can help actuaries improve their work output.

We listened to actuaries. These are the challenges they said they deal with on a daily basis. Can you relate?

Actuaries of the future will work in agile teams across functions. How will we get there? What might actuarial deliverables look like under an agile mindset?

Agile and waterfall are two ends of the software development spectrum. This article explains the differences and illustrates how agile development at a software provider aligns well with the expected future of actuarial work.

Actuarial departments have traditionally been de-centralized. Recent years have seen a push to centralize modeling functions. This article compares pros and cons of centralized/de-centralized organization and offers an alternative model for consideration.

The actuarial profession continues to evolve. Reflecting on the SOA Annual Meeting, we give our perspective on where actuaries currently thrive and some thoughts on how to advance the profession.

Actuaries may need to decide whether to buy (hosted) or build (on-premises) the infrastructure to hold their various business software. This article explains the difference and gives questions to help the decision process.

SaaS providers have the ability to change underlying aspects of their offering for better experience. This case study shows how Slope upgraded database processes and users got their results faster.

Actuaries may wish to learn how to modify their practice from "Actuarial as a Product" to "Actuarial as a Service". This article highlights benefits of AaaS and encourages actuaries to adopt this forward-looking mindset.

Good actuaries have many characteristics in common. This guest post by Jeff Samu, FSA, MAAA, gives his perspective on what makes a good actuary.

Software as a Service applications have a lot to offer actuaries. Discover the benefits of applying SaaS to actuarial work with this comparison article.

Actuaries, their employers, and consumers benefit from actuarial software competition. So why isn't there more? Explore some consequences of thin offerings in this article.

Actuaries can learn a lot from software development principles. What they learn may influence their actuarial model development for better results.

Actuaries investigating model differences (either compared to actual results or other models) need to understand whether those differences are due to timing. This article explains why timing is important and gives reminders of how to structure changes.

Actuaries can improve the effectiveness of their models, much like humans pursue self-improvement. This framework gives actuaries a structure for prioritizing those improvements.

Initial results of our first Actuarial Wasted Time Survey are in. Check out a preview of some differences between actuarial levels and across different systems in use.

After converting an actuarial model to a new system, what happens afterwards? This article gives practical steps to show value of the project and leverage learnings for future success.

Ending a contract with an actuarial software vendor doesn't have to be so hard. Follow these 6 tips to keep focused on the good to come.

When it's time to compare outputs from a modern actuarial system to your prior version, hitting all 7 of these stages will ensure a smooth transition.

Actuaries end up wasting time on non-actuarial tasks. This post introduces a survey to help understand the extent of such wasted time.

Some reasons for choosing a modern actuarial system are good: they allow you to be a better actuary. Are there some bad reasons? Absolutely. Read this to avoid making a big mistake.

Actuaries evaluating modern actuarial systems will need to compare many dimensions. These will help actuaries understand differences between systems.

Actuaries making a case for a modern actuarial system will need structure to their argument. This article outlines a straightforward way to think about the necessary elements.

There are many signs an actuary may need to update their actuarial modeling system. Here are 4 more.

There are many signs an actuary may need to update an actuarial modeling system. Here are 4.

Actuarial model conversion is perceived as difficult. Ask any actuary who’s had to convert a model from one system to another, and they’ll tell you the same things: It was confusing, because it was hard to understand just where we were starting from. We didn’t really know what we were doing when we started, so […]

Let’s be honest, the next $100 million blockbuster isn’t going to be titled The Actuary, starring Liam Neeson as an experienced FSA looking to make sure that pricing, valuation, and forecasting are all on the same page with their best estimate mortality assumption. We’re not going to hear that famous Hollywood voice-over saying “The fate […]

It seems like “data storytelling” is all the rage these days. A quick Google search (in early 2020) returns over 100 million results. Even more popular, “effective data visualization” checks in at over 192 million possibilities. You’ve no doubt seen the numerous vendors, certifications, on-line communities, books, consultants, and trainings you can harness to improve […]

There is one dimension of your actuarial modeling system that’s often viewed as a point of contention. This is the range of options for allowing model changes. Here we’re going to call that the Flexibility vs. Control Spectrum (FVCS). The basic point is this: either your actuarial system can be totally locked-down (Controlled), or it […]

It seems like everyone is talking about work-remote and flexibility and telecommuting as the next big thing. Apparently, it’s been on the rise since 2005 (up 173%, according to Global Workplace Analytics), and the growth doesn’t show any signs of stopping. Employers like it for increased productivity and decreased savings. Plus, many professionals (like our […]

What’s 6 + 2? 8. It’s obvious. But the next question is not: How do you know that is true? There are a couple of different ways. One, you just remember. You learned some kind of fact long ago (similar to “The American Revolution began in 1776” or “Cats have five claws on front paws […]

We promised a series of articles discussing actuarial model trade-offs, and dang it, we’re going to keep our word. Our first trade-off article was about Modeling Efficiency versus Detail, and you can read that one here. Today we’re discussing another trade-off that many actuaries contend with on a daily basis: how precise do you need […]

(We’re not going to say “best”, because, frankly, that’s a bit more arrogant than we wish to be.) One of our colleagues had a practice of typing his thoughts out as he was having them. Literally. He would document his thoughts in real-time, as he was having them. Not the I can’t believe it’s not […]

As any actuary who’s been in modeling for any time knows, there are multiple trade-offs in creating your model. We’ll be presenting some of those tradeoffs over a series of articles. This is the first, discussing the inevitable compromise between model detail and run efficiency. AN UNLIKELY CASE STUDY There once was an insurance company […]

What Is A Model? “All models are wrong, but some are useful.” —George E. P. Box This quote is very familiar to modelers, not just in the actuarial world but in statistics, biology, economics, and even politics. The essence of the quote comes from the need to simplify the “real world” in order to understand […]

Change is hard. At least, that’s what we’ve been told. But sometimes change is easy; Way too easy! This is part 2 of our discussion on Model Governance.  If you missed the first one, check it out here. Model Change Management can be a tough topic for many people. Model change management programs exist across […]

Despite the meteoric rise of cloud computing, actuarial software (and the financial services industry in general) seems to be lagging behind.  Numerous articles written over the years point to the benefits cloud computing can provide, but most software available today still requires too much manual intervention.  Be it installation and maintenance of desktop software, or […]

Model Governance? Sounds boring. Why do I need that? Well, in short, it’s about managing risk. Specifically model risk – the risk of adverse consequences resulting from reliance on a model that does not adequately represent that which is being modeled or that is misused or misinterpreted. That covers a fair amount of ground.  If […]