In a previous article, we outlined some changes that the financial services industry needed to make to improve persistency rates.
First, products must be more obviously linked to the needs of end-customers, second, the relationship between providers and distributors must change and finally, the industry must begin defining success in terms of measures that reflect genuine value creation.
But there is little sign that progress is being made in solving the retention riddle despite the consensus among providers that the current situation is unsustainable and regulatory endorsement of change.
Why has there been so little ground gained and how can providers and others in the value chain work to create the kind of healthy and dynamic industry that best serves the needs of shareholders, partners and customers?
We must first understand what stands in the way of the industry taking action today. The critical issue is that it is incredibly difficult to assess the potential impact of changes to insurance business processes or activities.
The high complexity of the market and the numerous dependencies and variables involved at every step, make it hard to be confident that a change designed to improve persistency will not have significant adverse consequences. For example, modifying adviser remuneration may negatively affect volumes, with uncertain implications. The result is that the industry – which is already risk-averse – shies away from taking action.
The key question becomes – how can a provider in today’s environment build a case for change that balances an acceptable likelihood of success with an acceptable degree of risk?
We believe the answer lies in a three-stage solution. The first stage is to develop a simulated market model to identify the impact that actions will have across all relevant variables. This can then be used to inform the design and implementation of a series of controlled, rolling experiments to provide evidence to refine the model and increase confidence in its results.
Finally, as these experiments progress and the evidence mounts, the entire org-anisation must be prepared to make fundamental changes to the way it does business to achieve the ultimate objective of value creation.
A key component of the solution is the use of system thinking and system dynamics methodologies to build a market model.
These allow problems to be assessed from a range of perspectives, incorporating the interplay and effects of multiple actions. Just as important, they provide a mechanism for building consistent, organisation-wide understanding of the issues and opportunities that arise. Such models work best when developed by a wide group of stakeholders. Breadth of input ensures that they take a balanced view and capture interactions in a realistic manner. They also provide a very powerful way of ensuring that all participants share an understanding of what is really happening in the market and this commonality affords much higher levels of confidence in making decisions about the next steps to be taken.
Once a prototype model has been built, it can be used to support much better decisions about the actions that the insurers should test in the market in their efforts to address retention issues.
For example, an organisation can react in a number of different ways to early warning indicators that a policy is about to lapse. Among other things, it could communicate proactively with the customer, route client requests to specially trained case managers or identify and recommend alternative products.
Detailed analysis of the results of a carefully designed experiment can identify the combination of responses that is most likely to result in retention, and any negative effects in areas that are known to be linked thanks to the market model.
To minimise the risk of significant business detriment, these tests should be conducted as a series of linked experiments using controlled groups of policies.
Accuracy can be ensured by using statistical techniques to ensure representative samples and meaningful results. The experiments must also be carefully designed to identify the behaviour of each relevant variable, which can be difficult to isolate, given that most changes affect a combination of variables.
For example, understanding the behaviour of three variables in a sample group and a control group requires eight separate tests to properly understand their optimal relationship. Four variables would require 15, and so on.
As results are received, data should be used to test and update the model, increasing the certainty of benefit and the appreciation of risk.
In our experience, the first actions to improve overall results will be identified at an early stage and benefits will start to accrue as these are implemented across the organisation.
Achieving competitive advantage
It is our belief that simply improving responses to customer behaviour will not be enough to reverse the current deterioration of customer persistency.
More fundamental actions will prove necessary to deliver the necessary step-change in the market – the ultimate objective of the modelling activity.
Such actions might include a change in the number and type of distributors with which a provider works and partnering with like-minded organisations to test and develop end-toend solutions.
This could be supported by remuneration models that more accurately reflect the value created by individual distributor relationships.
Another outcome might be a complete rethink of the cost-cutting culture that exists in many customer service divisions. Rather than aiming for a barebones service, providers could focus on serving and communicating with customers effectively, thereby enhancing loyalty and strengthening the relationship.
These techniques will also allow product providers to begin designing new propositions which better suit the needs of all customers, removing the complexity and artificial barriers that often cause suspicion and mistrust.
Much of the new business being written today will destroy value on providers’ balance sheets. This cannot be sustained, it will ultimately result in the industry shrinking. The negative impact can be reduced through carefully controlled actions, perhaps of the reactive type outlined above.
However, this will only slow the decline, and we believe a truly healthy and vibrant market can only be achieved by a more fundamental shift in attitudes and behaviour.
The process outlined in this article provides a mechanism for achieving this transition. The rewards for those with the bravery to carry it out will be substantial.