What is portfolio management?
‘Active portfolio management’, as we prefer to call it, is about how a business pro-actively manages its portfolios to deliver against its business plan. There are three essential building blocks:
- Identifying the portfolios: Identify meaningful dynamic/fluid groupings of risks that can be analysed in depth so that drivers of performance and be identified.
- Informed and agile management: Management actions (strategy, pricing, underwriting, etc.) must be informed by good quality (insightful, relevant, timely, well governed) data and analysis. Effective management also requires speed or agility, that is, how quickly can the organisation identify and respond to issues in the portfolio.
- Making it active: A framework for proactively looking for opportunities as well as issues (which requires intelligence, be that human, market or artificial), cascading a strategy into a detailed action plan, and then executing against it quickly.
An organisation with effective portfolio management will have a plan for each of the portfolios. This will have been subject to scenario testing, sophisticated analytical and stochastic modelling techniques, and will align to the business plan. All this will be backed up with appropriate monitoring.
The way that portfolio management is deployed not only brings together all the functions to ensure an integrated strategy, but ensures that any deviations from plan are identified and understood quickly, so that fast management action can be taken. The accountability for managing the portfolio should be vested with the right individual in the organisation, who has the skills and authority to bring everyone together. This includes the ability to recognise and communicate the potential implications for capital management. All this is underpinned by high quality data and analysis.
The five key steps of portfolio management
1. Develop strategy
How to achieve business objectives in terms of underwriting, pricing, claims, reserving, data (etc) strategies
2. Create detailed plan
Aligns with top-down objectives and strategies. Data quality is combined with experience and judgement. Granular segmentation, wide engagement and scenario/impact testing.
Communications to underwriting, pricing and claims, and with IT and data supporting rapid deployment and cycle times. Issues are identified quickly through AvE monitoring.
4. Performance management
Data strategy is critical, and there is regular, automated MI production. There is a self-service data exploration dashboard environment, and strong governance forums.
5. Portfolio steering
Reviewing results while looking for opportunities and issues. Mix dialled up and down through levers or rate, retention and new business. Influence over underwriting and pricing (direct), and reserving and claims.