Articles - The challenges of modelling and reporting in life insurance


Life modeling and reporting teams are struggling to keep up with their model development and reporting ‘day jobs.’ How do you drive the financial transformation needed to secure long-term success? Life modeling and reporting teams are facing unprecedented challenges, including uncontrolled costs and ever-tightening deadlines, as well as resistance to change and inconsistent reporting practices. Complicating this is the need for complex calculations, ever-evolving projects, heavy technology reliance and concerns with model optimization and maintenance.

 By Mark Brown, Global Proposition Lead, Life Financial Modeling, Insurance Consulting and Technology at WTW
  
 Has your actuarial team reached a place where change isn’t only desirable but urgent?
  
 In first of a series of five articles on life modeling and technology, we will explore the challenges facing life insurers. The articles will examine how life modeling and reporting teams can properly understand what is and what isn’t working well, the implications of that for the business and suggest ways to frame your situation to finance leaders to help you get the resources you need to deliver long-term improvements.
  
 The case for change
 Some of the common reporting challenges that you need to consider when developing your business case include:
  
 Your costs are out of control. Every year, your actuarial team works hard to complete the reporting in time and all the while, reporting demands deepen in their complexity. Errors start creeping in and the overtime bill is crippling your budget, right when you need to increase your spend on hardware to keep up with increasing reporting sophistication. If this is the case, the message to your CFO may be: We’re spending ever-more time and money just to stay still. We need to redeploy this spend smartly to make process and technology improvements that get us ahead of the growing complexity of the business’ modeling and reporting needs.
  
 You’re delivering reporting, but only just in time…just about. There’s so much to get done within the reporting cycle: preparation, calculations, review, rework, reporting and dealing with those last-minute 'what-if?' questions. It’s a stretch to get everything done each time, but your team does, just about. However, errors have started to creep in, and your team is having to redo some tasks. They’re at risk of burnout.
  
 While this ‘seat of the pants’ state of affairs accommodates the needs of your stakeholders, eventually, you’re going to start identifying errors too close to deadlines. Or auditors may ask last-minute questions and put the way actuarial reporting gets done under increasing scrutiny, creating additional workloads. The message to your CFO on this might be: Positive process changes, backed by the right resources, can shield our actuarial function from the people risks of burnout and the business from the risks of ‘just in time’ reporting errors.
  
 You’re fighting to keep pace with changing regulation and constantly deprioritizing value-generating projects. Every few years, there seems to be a new set of regulations, with refinements in between. And just as you’re barely keeping up with the compulsory changes, your management is looking to uncover more insights and greater value from your data assets. While your stakeholders may be asking simple questions, they don’t fully appreciate the scale of calculations to deliver the answers they seek, meaning it’s an uphill struggle to deliver even the most rudimentary responses. If this is your situation, your message to the CFO may be: The current status quo is pushing value-added work from the core to the margins. We want to deliver the insight business leaders need to generate more value, but we need resources to change our processes and the right technology solutions to make this happen.
  
 You’re wrestling reporting inconsistencies. As various reporting projects have evolved, with managers or external processes requesting more information, your reporting complexity has increased.
  
 Maybe you’re no longer even sure who still needs which reports or for what purposes, and why they’re not consistent across all projects. And maybe it’s not possible to bring the reports into a single consistent framework because other systems have evolved to depend on them as they are. Worse, maybe you have separate teams with different approaches, approximations and reports, all of which you have to consolidate. The message to the CFO in this type of scenario may be: Reporting inconsistencies have grown in response to business needs, but we need to simplify, automate and consolidate these if we want to prevent errors and actuarial resources being diverted to smoothing over the cracks, instead of adding real business value.
  
 So how did we get here — and what lessons need to be learnt?
 First, we need to acknowledge that these calculations are complex and business-critical. We are here because people have done their best — often with limited resources — to keep pace with changing needs. But in doing so, by being agile and reactive, problematic working patterns have crept in, which now need to be rooted out. Some of the most common of these are:
 
 Point Solutions
 Building a specific fix to a specific need, for example, a report or calculation. These localized components force the wider surrounding process to fit their needs and impose additional constraints. Where solutions aren’t flexible, they need to be reviewed.
 
 End user computing
 Challenges created by end user computing are similar to those found with point solutions. However, rather than locking the process into a particular approach, they often lock in the technology instead. For example, the use of Excel macros can force dependency on files and folders with specific naming conventions, text files and more Excel reports.
 
 Model investment
 Model development is often additive. Whether used or not, past features left in the code base can slow a model down, make it harder to maintain, sometimes generating spurious errors for new developments. Good models must be cleared out regularly to ensure they’re only representative of current needs.
 
 Model goals
 All too often, the goals of specific models are lost and forgotten. A good model will have a clear strategy around speed, precision and ease of maintenance. Both current models and future developments should bear these in mind. Often projects focus on simulation and precision as an easy target, which changes the philosophy of the model and hence its characteristics. This inadvertent refocusing can also result in a general deterioration of the model’s robustness, governance and auditability, its accessibility to new team members (as well as consultants and contractors) and the quality of documentation.
  
 The next steps in driving change
 The takeaway from this is that it’s important to take a critical view of what you’re working with. Instead of asking whether a model meets your current needs, you should ask whether this is what you would build if you were to start from scratch today.
  
 Success in the short term is to start a virtuous circle, where small investments result in larger savings, which in turn fund larger investments for even greater gains. By showing your willingness to think in these terms, you can better align with the concerns of finance leaders and work collaboratively to access the resources you need for more fundamental process change.
  
 Positive change may be highly desirable, but it isn’t inevitable. So, if you identify with any of the challenges in this insight, it may be time to disrupt the status quo. In the next of our articles in this series, we’ll explore a comprehensive strategy to enhance your life businesses, by focusing on long-term objectives and the right approach to model development and technology.

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