Insights

A federated data model can efficiently bring together disparate data across all delegated authorities, and unify the information from multiple risk, exposure and claims bordereaux into the ultimate, consistent data format.

The Solvency II Pillar 3 regulatory reporting requirements came into force on January 1, but many re/insurers are grappling with implementing the right system.

Against a backdrop of rapid technological change, record low fixed-income yields and perpetually softening insurance rates, it’s no wonder that many insurance businesses are considering a change in strategy. Barely a week goes by without some new report warning of threats to traditional insurance business models and competitive pressures on the established insurance market hubs.

With supply of re/insurance significantly outstripping demand in this extended soft market, many underwriters have become considerably more proactive about the ways they source business. Although no new distribution categories have displaced the traditional channels of direct sales, broker production and delegated authorities, the insurers have had to adopt more advanced methods to assess and rank each, to deduce their relative value. With this approach insurers hope to concentrate their efforts on the distribution channels, which promise profitable, and growth business. Garnering a quantitative understanding of the nature of the underlying risks is the key to delivering actionable insights, which guide the focus towards profitable business.

The confluence of soft market pricing, low investment returns, and new competition have made it more important than ever for underwriting operations to ensure each line of business written is carrying its weight. The challenge is heightened by the approaching exhaustion of surplus reserves. Releases have carried the market for several years, but it seems likely that soft-market underwriting and less-than-prudent reserving (for events such as Tianjin) will reverse the trend, leading to strengthening for some companies in some lines. Paid claims ratios have been moving in the wrong direction for some time. Given this backdrop, in theory everybody must be underwriting for profit, all of the time.

As brokers evolve beyond pure policy placement to provide wider risk consultancy, the necessity for detailed analytics becomes paramount. To achieve this leap up the value chain, brokers must integrate, analyse and communicate data, leading to actionable insights for their staff of clients.

1. Is data readily available to those who can use it and are they using it?
2. Is data-crunching creating a bottleneck?
3. Does the organisation contain information silos?
4. Is performance measurement transparent?

One of the most important jobs for line of business heads and business leaders is to react to market conditions in different phases of the cycle and to steer the portfolio accordingly.

The oscillations between reserve releases and strengthening can never be eliminated entirely due to the unpredictability of the emergence of budgeted catastrophic events or final payouts on long-tail liability claims. Nevertheless, data issues do contribute to the amplitude of the cycle.

Good Business Intelligence (BI) can help underwriters and pricing actuaries to rate business more accurately in day-to-day underwriting. It can also provide a timely indication that recent business written might not be performing according to original underwriting assumptions.