What data & insights capabilities can transform personal lines quote conversion rates?

What data & insights capabilities can transform personal lines quote conversion rates?

While it seems like a singular ask, the fact is that there are several factors that influence quote conversion, and not all of them are fully controlled by the carrier, anymore.

In Capgemini's World Insurance Report 2020, executives in Personal Lines had identified quote conversion rates as one of the focus areas for growth. And it is true that for sustained profitable growth, this is a key outcome for all carriers. In recent times, as carriers are planning for recovery from pandemic, there is an explicit need for growth and quote conversion rates are quite an important factor. Chief Data Officers and Heads of Sales & Distribution, at our clients, have asked us in recent times, as to what are the proven methods to influence quote conversion rates.

One of the key findings from World Insurance Report 2020, was that prospects use different methods to research and buy insurance.

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What this means is that while comparative raters are quite important for sourcing business in personal lines, the carriers' (or their agents') own digital capabilities are equally important in improving conversion rates.

Having said that, for both of these channels to yield better conversion rates, there are a number of factors that influence it. Here are the top three:

  • Pricing sophistication: the quoted price is one of the most important factors for carriers make the cut, and in order to win on price, the pricing models need to be sophisticated, granular and they ought to work in unison with other forward-looking high fidelity AI/Machine Learning models such as bind propensity, early cancellation, claim frequency/severity models, etc. Several of the carriers are restricted by archaic pricing engines (even more true in commercial lines), which do not allow granular pricing. For instance, Capgemini supports pricing analytics tools in 500 m x 500 m grids along with a strong partner ecosystem to help with pricing sophistication.
  • Matching exposures with risk appetite: given the shifting nature of underlying risks and perils across geographical regions, there are opportunities to shift focus to writing the right risk profiles, to the allowed levels and shift capital to regions where profitable business can be sought more actively. For instance, over the years the shifting wind directions have changed the exposure maps for wildfire-related (or other) risks. Using the right third party data sets, it is possible for insurance carriers to manage their books more frequently, at much deeper levels, to identify opportunities to grow, while sustaining long term profitability.
  • Customer experience transformation: in a soft market, market share growth is a function of how carriers build their reputation as a trusted service provider. Some of the carriers have taken this up several notches to become "advisors" who focus on claim prevention through early intervention, use of real-time IOT & analytics, etc. However, in today's world, those who are shopping for insurance, have a lot of information on individual carriers, their service levels, reviews from existing customers, etc. These sources and key opinion leaders influence the quote conversion rates (as well as lapse rates, non-renewals, upsell/cross-sell, referrals, etc.). If you are constrained by budgets or time, this should be the first one to focus on. And as the survey results indicate not everyone buys online and if you were to dedicate your contact centers to pursue conversion, that would certainly help.

Now that it is a reasonably complex issue to solve, what should companies begin, if they want to improve the quote conversion rates?

Here are some ideas to think about:

  • Conducting a review of quote leakage and identify potential reasons
  • Assimilate information from customer and prospect reviews to identify issues that mar conversion
  • Review your existing pricing engines to see they are able to support the sophistication your line of business needs. It would also help to review your current data estate modernization roadmap to see pricing analytics capabilities are gaps are being addressed
  • Invest in digital marketing and social media management tools to improve your branding and digital presence
  • Let your agents fire from your shoulders by giving them actionable insights

For additional details and more information, please do not hesitate to contact me. There are similar approaches that work for Commercial Lines too.

Happy New Year!

Prabananth Mounasamy

Product Management | Management Consulting | Open Banking | P&C Insurance | FinTech

3 年

Good one Ajish. When it comes to the Indian Carriers, I think that most carriers can still improve their response quality. An abandoned quote, IMO, must be considered as one of the most important leads. In India, irrespective of whether I use an aggregator/ 3P comparision quote provider OR carrier portals/apps, the time taken to receive a follow up call is relatively higher and often times, the CSR isn't very knowledgeable. I feel that there is a lot of scope in using Third Part Data (Vaahan, Credit Score, Claims History and etc.,), Social Media Data, Location / Other Demographic Data and etc., to score and prioritize each lead. Based on the priority score, they can determine the best CSR/ local office or agent to handle the lead and also decide how fast they need to respond I would expect new age Companies like Acko or Digit to respond back to a high priority abandoned quote within about 5 mins of the potential customer leaving the website/app.

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