Industry · Insurance AI Platform

Policy Recommendations

Personalised policies that fit each customer — recommend the right coverage and offers to improve conversion, retention and adequate protection.

+0%Conversion uplift
+0%Cross-sell rate
+0%Renewal retention
Overview

What is Policy Recommendations?

Policy Recommendations at MindCraft Solution helps insurers match customers with the coverage that genuinely fits them. We build recommendation and next-best-action models that suggest the right products, coverage levels and cross-sell / upsell offers — improving conversion and retention while ensuring customers are neither under- nor over-insured.

Generic offers convert poorly and can leave customers wrongly covered. We use customer, policy and behavioural data to personalise recommendations at quote, renewal and service moments, balancing relevance and value with suitability and compliance — so recommendations help the customer, not just the sale.

Integrated with your quote, CRM and service channels, the result is higher conversion and cross-sell, better retention at renewal, and customers who feel understood and properly protected.

What's included

What Policy Recommendations includes

Everything you need to take policy Recommendations from idea to a dependable, owned capability.

Coverage recommendations

Suggest the right products and coverage levels per customer.

Cross-sell & upsell

Relevant next-best-action offers that fit the customer.

Renewal & retention offers

Personalised offers that improve renewal rates.

Suitability & compliance

Recommendations that respect suitability rules.

Channel integration

Delivered at quote, renewal and service moments.

Measurement & optimisation

A/B testing and uplift measurement.

The impact

Outcomes we target

Typical results from MindCraft insurance AI Platform engagements.

+0%
Conversion uplift
+0%
Cross-sell rate
+0%
Renewal retention
0%
Coverage suitability
How we work

Our delivery model

A clear, low-risk path from first call to a running, optimized solution.

  1. 1

    Understand customers

    We analyse customer, policy and behavioural data.

  2. 2

    Build recommendations

    We build personalised recommendation and next-best-action models.

  3. 3

    Integrate

    We deliver recommendations across quote, CRM and service.

  4. 4

    Test & optimise

    We measure conversion and retention uplift and refine.

Challenges we solve

From problem to outcome

The pressures we see in insurance — and how we fix them.

  • Challenge

    Slow claims settlement

    How we solve it

    Touchless claims automation that settles faster.

  • Challenge

    Inconsistent underwriting

    How we solve it

    Data-driven, explainable underwriting AI.

  • Challenge

    Claims fraud leakage

    How we solve it

    Advanced fraud analytics before payout.

Tools & technology

The stack we use

PythonRecommendation modelsSnowflakeCRM integrationREST APIA/B testing
Deliverables

What you get

Concrete, owned artifacts — not just advice.

  • Recommendation & NBA models
  • Quote / renewal integration
  • Suitability controls
  • CRM / channel integration
  • Uplift dashboards
FAQ

Questions, answered

No — suitability and compliance are built in. Recommendations balance relevance and value with what's genuinely appropriate for the customer, which also builds trust and retention.

At the moments that matter — quote, renewal and service interactions — across your digital and assisted channels, integrated with CRM.

Yes — personalised renewal and service offers improve retention, and right-fitting coverage reduces churn driven by dissatisfaction or claims surprises.

Through A/B testing and uplift measurement on conversion, cross-sell and retention, so the impact is evidenced rather than assumed.

Ready to talk about Policy Recommendations?

Tell us where you are and what success looks like. We'll bring the right people, stack and plan — and reply within one business day.