Real Results from Real Insurers

The Challenge

Apex ran three specialty programs through a network of 180+ appointed producers. Their distribution strategy was simple: more producers meant more submissions meant more premium. But their hit ratio — the percentage of submissions that actually bound — had been declining for two years, from 22% to 15%. Nobody could explain why.

The VP of Distribution assumed their top-volume producers were their best producers. Monthly commission statements showed who generated the most submissions, but there was no way to see conversion rates, loss performance, or cycle time by producer. When the carrier partner asked Apex to explain why their loss ratio was climbing despite premium growth, the answer was a shrug and a promise to "look into it."

The other invisible problem was cycle time. Producers were complaining that quotes took too long, and Apex was losing deals to faster competitors. But without data on where submissions stalled — clearance, underwriting, rating, or quoting — there was no way to pinpoint the bottleneck.

The Solution

The Producer Scorecard was the first dashboard that changed Apex's distribution strategy. For each of their 180 producers, they could now see submissions received, hit ratio, bound premium, average premium size, and loss ratio — all on one screen with YoY comparison. The data told a story nobody expected.

Their #1 producer by volume — an agency generating 400+ submissions per year — had a 9% hit ratio. For every 100 submissions they sent, Apex bound 9. Meanwhile, a mid-tier agency sending 80 submissions per year had a 52% hit ratio and zero claims. Apex had been investing marketing dollars and co-op funds in the wrong producers for years.

The Cycle Time dashboard revealed that 30% of all submissions were expiring before a quote was issued. The bottleneck wasn't underwriting — it was clearance. Submissions piled up on Tuesdays because three of their largest producers did weekly bulk uploads on Monday evening. The fix was simple: Apex worked with those producers to stagger uploads across the week and added a second clearance team member on Tuesdays.

The AI chat feature became a daily tool for the distribution team. During calls with producers, they could instantly answer questions like "What's our hit ratio on BOP in Florida?" or "How many of your submissions are still in queue?" Responses that used to require a day of pulling reports now happened live on the call.

After 6 months, Apex terminated appointments with 15 consistently underperforming producers (high volume, low conversion, adverse loss experience) and redirected their field marketing efforts toward the 40 producers with the best conversion-to-loss profiles.

Dashboards & Features Used

Results

The Challenge

Commonwealth operated with a familiar disconnect: the underwriting team and the claims team lived in separate worlds. Underwriters priced risks based on class codes, loss history, and rate filings. Claims adjusters managed open files based on reserves, litigation status, and settlement authority. Neither team had visibility into the other's work.

The consequences showed up in subtle ways. Underwriters continued writing a specific class of Florida commercial auto risks that the claims team knew had a 92% loss ratio — but that information lived in the claims system and never made it into the underwriting guidelines. The claims VP had flagged the issue verbally in a meeting six months earlier, but without data to quantify the impact, it was filed under "things to look into eventually."

Commonwealth also had 12 claims handlers across two offices. The Atlanta office handled Workers Comp and GL; the Charlotte office handled Auto and Property. Management believed the workloads were balanced, but there was no objective measurement. Quarterly claim reviews were based on each handler presenting their own files — a subjective process that took two full days and told leadership almost nothing about relative performance.

The CEO's frustration boiled over when the annual actuarial review showed a $4.2M reserve deficiency concentrated in the Florida commercial auto book. "How did we not see this earlier?" became the question that led to the Insulytics engagement.

The Solution

Insulytics was deployed with a specific mandate: connect the dots between underwriting decisions and claims outcomes. The first step was loading both the policy and claims data into a single platform so that every claim could be traced back to its originating policy, producer, underwriter, and line of business.

The Claims Trends dashboard, configured for Accident Year view, immediately quantified the Florida commercial auto problem. Loss ratio for that segment was 94% over the trailing 3 years — not a recent spike, but a sustained bleed that had been masked by the profitability of their Georgia Workers Comp book. When filtered by underwriter, the data showed that two of their eight underwriters were responsible for 70% of the Florida auto writings, and their combined loss ratio was 108%. The issue wasn't the market — it was concentration risk in a specific underwriter-territory-LOB combination.

The UW Scorecard gave management a view they'd never had: each underwriter's full lifecycle performance from submission received through claim closure. One underwriter had the fastest cycle time (great) but the highest loss ratio (not great) — she was binding quickly but not spending enough time on risk selection. Another had excellent loss performance but a 12% hit ratio — he was being too selective and leaving profitable business on the table. These weren't performance problems that a single metric could surface; they required the multi-dimensional view that the scorecard provided.

The Handler Scorecard ended the two-day quarterly review process. Management could now see each handler's open file count, average reserve, closure rate, litigation percentage, and average days to close — updated continuously, not once a quarter. The data revealed that one handler in the Atlanta office had 145 open files (the next highest was 87). She'd been quietly absorbing reassigned files from a colleague who left 8 months earlier, and nobody had rebalanced the book.

The Litigation dashboard showed that 22% of Commonwealth's open GL claims were in litigation — well above their target of 15%. When filtered by state, Florida accounted for 60% of all litigated claims. When filtered by attorney involvement timing, they discovered that claims where an attorney appeared within 30 days had 3.2x the average incurred cost. This led to a new early-intervention protocol for Florida GL claims.

Commonwealth's CEO now starts each Monday with an AI-generated summary: "What changed in our book this week? Any new alerts?" The AI flags reserve movements over $50K, new litigation filings, and any LOB where loss ratio moved more than 5 points from the prior month.

Dashboards & Features Used

Results