How many customers do you actually have?
You might not know.

Name: Customer Intelligence
Brand: Percayso Inform

Your policy admin system says one number. Your CRM says another. Neither accounts for the same person holding motor and home with you under slightly different name spellings, or the household where three family members each have a policy but appear as three unrelated customers.

Without a true Single Customer View, every downstream decision is compromised. Marketing targets the wrong people. Retention campaigns miss duplicates. Pricing models work with incomplete histories. And every enrichment product you run returns less than it should - because it's matching against fragmented, unresolved data.

The Identity Problem

Your book contains thousands of records that represent the same person. John Smith at 14 Oak Lane. J. Smith at 14 Oak Ln. Jonathan Smith who moved from Oak Lane to Elm Street last year. Your systems treat these as three different customers.

This fragmentation cascades through everything. Bureau searches on a partial identity return less. Quote Intelligence matches fewer records. Policy Intelligence can't see the full picture. Your enrichment is only as good as the identity you're enriching against.

Most insurers know this. Few have solved it - because identity resolution at scale requires more than simple name-and-address matching.

What Customer Intelligence Delivers

Customer Intelligence takes your raw policyholder data and resolves it into a true Single Customer View using entity resolution and fuzzy matching across 40+ match signals.

For every person, you get:

One deduplicated identity record across all policies and lines of business
A RAG quality score across 34 data quality categories
Household and named-driver relationship mapping
200+ enriched attributes from behaviour, demographics, and risk data
7+ years of historical behaviour per resolved identity

Clean identity in. Better intelligence out. From every product.

Identity resolution that works at scale

Customer Intelligence uses a two-stage matching engine. Deterministic rules handle the clear matches. Probabilistic scoring resolves the rest - catching the variants, aliases, and address histories that simple matching misses.

94%+

of records resolved
to a PIL identity

<0.3%

false positive rate
on deterministic matches

3.2

average address variants
resolved per identity

200+

enriched attributes
per identity

How We Match

Stage one applies deterministic rules: exact name plus postcode, confirmed electoral roll match, VRM ownership link. These high-confidence matches form the backbone of your SCV.

Stage two applies probabilistic scoring across 40+ match signals - fuzzy name variants, address history, device fingerprints, behavioural patterns - to resolve records that don't satisfy deterministic thresholds but represent the same individual with high confidence.

78% of resolved identities are linked across two or more insurer data sources, giving you cross-market visibility that no single internal system can provide.

The Identity Graph

Resolved identities are stored in a graph structure that captures relationships between people - household members, named drivers, company officers - and entities like vehicles, addresses, and policies.

This graph enables downstream products to reason about household-level risk, corporate structure, and multi-product behaviour without your team needing to build complex data joins.

Customer identities are not static snapshots. CI continuously ingests new quote events, policy events, bureau data, and address changes - updating each identity's attributes in real time. You always query a live, current-state SCV rather than a monthly batch export.

Clean identity makes everything else work harder

Customer Intelligence isn't just a data quality product. It's the foundation that determines how well every other intelligence product performs against your book.

Without a Resolved SCV

Bureau searches run on incomplete keys and return partial results. Quote Intelligence matches fewer records because it's searching against fragmented identities. Policy Intelligence can't see the full history because the same person appears as multiple entries.

Your enrichment returns what it can find - but what it can find is limited by the quality of the identity you gave it. Every unresolved duplicate, every misspelled name, every outdated address is a missed match and a weaker signal.

You're paying for enrichment that's working at half capacity because the foundation isn't clean.

With Customer Intelligence

Every downstream product matches against clean, resolved identities. Bureau Intelligence searches with more keys and returns more data. Quote Intelligence finds more quote history because it's searching the right person, not a fragment.

The RAG quality scoring gives you a traffic-light view of every identity in your book - showing you exactly where data is strong and where gaps remain. This isn't a one-time clean; it's continuous, updating with every new event.

For the first time, you can see your true customer count, understand multi-policy relationships, and identify the highest-value customers in your book.

From fragmented records to resolved identity

Every customer record follows the same resolution path - whether submitted at point of quote, as a policy event, or as part of a batch SCV upload.

1 Customer record submitted from your system (quote, policy, or batch SCV)
2 Record normalised and parsed: name, address, date of birth, contact details
3 Deterministic matching: exact name + postcode + date of birth
4 Electoral roll lookup to confirm identity and resolve address aliases
5 Fuzzy matching across known name variants, aliases, and address history
6 Probabilistic scoring across 40+ signals for remaining unmatched records
7 Household and named-driver graph constructed, vehicle ownership appended
8 200+ attributes calculated, RAG quality score assigned, enriched SCV returned

The identity graph updates continuously with every new event. Your SCV is always live and current - not a quarterly batch that's outdated the day it's delivered.

"Customer Intelligence gave us something we'd been trying to build internally for years - a true Single Customer View that actually works across all our lines of business. The match rates and data quality scores have transformed how we approach retention and cross-sell."

Head of Data, Leading UK Insurer

How Customer Intelligence works for your business

Customer Intelligence is the foundation layer. By resolving your customer data first, every downstream product returns its highest possible accuracy - more matches, stronger signals, better decisions.

For Insurers

A fragmented or inaccurate SCV means lower match rates, missed fraud signals, and unreliable pricing. By cleaning and resolving your customer data first, you ensure that every downstream product returns its highest possible accuracy.

See your true customer count, understand multi-policy relationships, and identify your highest-value customers.

Solutions for Insurers

For Brokers

Brokers managing complex books with clients across multiple products and intermediaries often hold the same individual across many records. Customer Intelligence resolves these duplicates into a single, scored identity - giving your team a unified view of each client.

Solutions for Brokers

For MGAs

A high-quality SCV is particularly important for demonstrating data governance to capacity providers. Customer Intelligence provides measurable, auditable identity quality across your book - with RAG ratings and coverage metrics for capacity reviews and regulatory submissions.

Solutions for MGAs

For Comparison Sites

Comparison platforms accumulate identity data across millions of quote events, often with inconsistency across fields, aliases, and address formats. Customer Intelligence normalises this into a clean SCV, improving behavioural matching and the quality of signals available to pricing partners.

Solutions for Comparison Sites

How many of your customers are really the same person?

Start with an Evaluate. We'll resolve your book against the PIL identity graph and show you your true customer count, your duplicate rate, and how much more intelligence every product could return with a clean SCV underneath.

What's In Your Book? Schedule a Conversation

How many customers do you actually have?You might not know.