Homeland = Your Average Life Insurance Company?

Or in other words: Did the agency model kill data quality?  When you watch the TV series “Homeland”, you quickly realize the interdependence between field operatives and the command center.  This is a classic agency model.  One arm gathers, filters and synthesizes information and prepares a plan but the guys on the ground use this intel to guide their sometimes ad hoc next moves.

Data QualityThe last few months I worked a lot – and I mean A LOT – with a variety of mid-sized life insurers (<$1B annual revenue) around fixing their legacy-inherited data quality problems.  Their IT departments, functioning like Operations Command Centers (intel acquisition, filter and synthesize), were inundated with requests to fix up and serve a coherent, true, enriched central view of a participant (the target) and all his policies and related entities from and to all relevant business lines (planning) to achieve their respective missions (service, retain, upsell, mitigate risk): employee benefits, broker/dealer, retirement services, etc.

The captive and often independent agents (execution); however, often run with little useful data into an operation (sales cycle) as the Ops Center is short on timely and complete information.  Imagine Carrie directing her strike team to just wing it based on their experience and dated intel from a raid a few months ago without real-time drone video feeds.  Would she be saying, “Guys, it’s always been your neck, you’ll figure it out.”  I think not.

Homeland = Your Average Life Insurance Company?
Homeland = Your Average Life Insurance Company?

This becomes apparent when talking to the actuaries, claims operations, marketing, sales, agency operations, audit, finance, strategic planning, underwriting and customer service, common denominators appeared quickly:

  • Every insurer saw the need to become customer instead of policy centric. That’s the good news.
  • Every insurer knew their data was majorly sub-standard in terms of quality and richness.
  • Every insurer agreed that they are not using existing data capture tools (web portals for agents and policy holders, CRM applications, policy and claims mgmt systems) to their true potential.
  • New books-of-business were generally managed as separate entities from a commercial as well as IT systems perspective, even if they were not net-new products, like trust products.  Cross-selling as such, even if desired, becomes a major infrastructure hurdle.
  • As in every industry, the knee-jerk reaction was to throw the IT folks at data quality problems and making it a back-office function.  Pyrrhic victory.
  • Upsell scenarios, if at all strategically targeted, are squarely in the hands of the independent agents.  The insurer will, at most, support customer insights around lapse avoidance or 401k roll-off indicators for retiring or terminated plan participants.  This may be derived from a plan sponsor (employer) census file, which may have incorrect address information.
  • Prospect and participant e-mail addresses are either not captured (process enforcement or system capability) or not validated (domain, e-mail verification), so the vast majority of customer correspondence, like scenarios, statements, privacy notices and policy changes,  travels via snail mail (and this typically per policy). Overall, only 15-50% of contacts have an “unverified” e-mail address today and of these less than a third subscribed to exclusive electronic statement delivery.
  • Postal address information is still not 99% correct, complete or current, resulting in high returned mail ($120,000-$750,000 every quarter), priority mail upgrades, statement reprints, manual change capture and shredding cost as well as the occasional USPS fine.
  • Data quality, as unbelievable as it sounds, took a back-burner to implementing a new customer data warehouse, a new claims system, a new risk data mart, etc.  They all just get filled with the same old, bad data as business users were – and I quote –“used to the quality problem already”.
  • Premium underpricing runs at 2-4% annually, foregoing millions in additional revenue, due to lack of a full risk profile.
  • Customer cost –of-acquisition (CAC) is unknown or incorrect as there is no direct, realistic tracking of agency campaign/education dollars spent against new policies written.
  • Agency historic production and projections are unclear as a dynamic enforcement of hierarchies is not available, resulting in orphaned policies generating excess tax burdens.  Often this is the case when agents move to states where they are not licensed, they passed or retired.

What does a cutting-edge insurer look like instead?  Ask Carrie Mathison and Saul Bernstein.  They already have a risk and customer EDW as well as a modern (cloud based?) CRM and claims mgmt system.  They have considered, as part of their original implementation or upgrade, capabilities required to fix the initial seed data into their analytics platforms.  Now, they are looking into pushing them back into operational systems like CRM and avoiding bad source system entries from the get-go.

They are also beyond just using data to avoid throwing more bodies in every department at “flavor-of-the-month” clean-up projects, e.g. yet another state unclaimed property matching exercise, total annual premium revenue written in state X for tax review purposes by the state tax authority.

So what causes this drastic segmentation of leading versus laggard life insurers?  In my humble opinion, it is the lack of a strategic refocusing of what the insurer can do for an agent by touching the prospects and customers directly.  Direct interaction (even limited) improves branding, shortens the sales cycle and rates based on improved insights through better data quality.

Agents (and insurers) need to understand that the wealth of data (demographic, interactions, transactions) corporate possesses already via native and inherited (via M&A) can be a powerful competitive differentiator.  Imagine if they start tapping into external sources beyond the standard credit bureaus and consumer databases; dare I say social media?

Competing based on immediate instead of long term needs (in insurance: life time earnings potential replacement), price (fees) and commission cannot be the sole answer.

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