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Business area digitalisation analysis

Digitalisation of insurance companies and intermediaries

How to connect quotation, risk assessment, policy, claim, partners and customer service into a single insurance process

Digital maturity

Typical digital maturity

Shows the level of technological and process digitalisation at which companies in the sector or business area typically operate today.

A typical market situation is assessed, not the most advanced companies.

The assessment consists of five equally weighted dimensions:

Core system usage
Whether ERP, CRM, WMS, MES, customer portals or other operationally important systems are widespread in companies.
Process digitalisation
How many core processes run in systems and how many are still managed manually.
Systems integration
Whether core systems exchange data between themselves or whether employees transfer information manually.
Data quality and readiness
Whether core data is structured, up-to-date, consistent and suitable for automation and analytics.
Advanced data use
Whether real-time analytics, forecasting, automated alerts, optimisation models or AI are used.

The final score is the average of the five dimensions.

1–5 scale

  • 1 very low maturity
  • 2 low maturity
  • 3 medium maturity
  • 4 high maturity
  • 5 very high maturity

A low maturity score does not necessarily indicate low potential. On the contrary, low maturity and a high level of manual work may indicate significant untapped digitalisation value.

medium
Skaitmenizacijos potencialas

Digitalisation potential

Shows how much significant business value a typical sector or business area company can create by systematically digitalising core processes.

The rating is calculated on a 100-point scale across five dimensions:

Process frequency and scale 20 %
An assessment of how frequently the digitalised processes recur and what proportion of operations they represent.
Manual work intensity 20 %
An assessment of the extent to which processes depend on email, telephone, Excel, paper documents and repeated data entry.
Impact on revenue and costs 25 %
An assessment of the potential effect on sales, margin, customer retention, administrative costs, errors, downtime or inventory.
Growth and scale potential 20 %
An assessment of whether digitalisation would enable operational capacity to be increased without expanding headcount and costs at the same rate.
Impact on decisions and risk 15 %
An assessment of the potential effect on data reliability, decision-making speed, customer experience, and the reduction of errors and operational risk.

The final score is calculated according to the assessments and weights of all dimensions.

100-point scale

  • 0–20 very low potential
  • 21–40 low potential
  • 41–60 moderate potential
  • 61–80 high potential
  • 81–100 very high potential

A high score does not mean the solution will be easy to implement. It indicates the size of the potential value, not the implementation complexity.

84/100
Biggest challenge
Client and policy view is fragmented
Biggest opportunity
End-to-end policy, risk and claims lifecycle

A business area with high potential and high implementation complexity, where digitalisation must simultaneously improve client experience, claims economics and decision control.

Operating model of insurance companies and intermediaries

Insurance operations combine risk assessment, contractual coverage, periodic payments, an extensive network of intermediaries and service partners, and the claims settlement process.

Abundance of products and exclusions

Insurance coverages, tariffs and decision rules differ according to product, object, client and channel.

Long contract period

Client and object circumstances change, so policy data must remain current until renewal or claim.

Partner dependency

The claims process is often carried out by repair partners, experts, medical institutions or other external participants.

Explainability of decisions

Pricing, underwriting and claims decisions must be substantiated and traceable.

Market and technology context

The insurance technology direction is shaped by digital claims administration, image and document analysis, partner data exchanges, connected asset data and stricter model governance.

  • Digital claim processThe customer expects to report a claim remotely, see its status and receive a clear explanation of the decision.
  • Data-driven risk preventionTelematics, property and behavioural data enable not only more accurate pricing, but also reduction of claim probability.
  • Broker and partner integrationsStandardised data exchanges reduce re-entry, commission discrepancies and claim delays.
  • AI and actuarial model governanceModel versions, data, correctness, explanations and actual outcomes must be managed in one system.

Typical operating process

01

Need and risk data collection

Information is gathered about the client, the insured object, desired coverage and previous history.

02

Risk assessment and offer

Applied product rules, tariffs, models, exceptions and expert approvals.

03

Policy creation and administration

The contract is signed, premiums, documents, object and coverage changes are managed.

04

Claims notification

The client submits incident information, documents, images and preferred communication channel.

05

Claims assessment and decision

Coverage, claim circumstances, partner reports, fraud signals and indemnity amount are verified.

06

Indemnity, closure and renewal

Indemnity is processed, the claim is closed, risk data is updated and the next offer is prepared.

Digital maturity model for the business area

0

Separate customer, policy and claim records

Customer, insured object, policy, document, partner and claim information is managed separately, with important statuses communicated via email or files.

1

Separate sales, policy and claim processes

Customer, object, policy and claim information is fragmented, with broker and partner data often transferred via files.

2

Digital channels for selected services

The customer can purchase some products or report a claim online, but staff and partners continue to manage many manual exceptions.

3

Integrated policy and claims process Typical current situation

Client, object, coverage, documents, payments and claims status are unified across core products.

4

Data-driven risk and claims prevention Siektina

Pricing, fraud, partner and claims data are utilised throughout the process, whilst proactive actions are provided to the client.

5

Adaptive insurance platform

Products, partners, models and claims processes are managed in a modular fashion, whilst solutions are continuously validated against actual risk and customer outcomes.

Key finding

The greatest digitalisation value in insurance arises from connecting the entire policy lifecycle – from need and risk assessment to claims, settlement and renewal.

The most practical initial project is typically a process for one frequently occurring claim type, as it clearly demonstrates costs, duration, partner actions and client experience.

Product and data platforms are a strategic foundation, but they are worth expanding based on specific, already functioning client and claims scenarios.

Related digitalisation topics

Digital insurance claims administrationInsurance customer self-serviceInsurance partner integrationsAI and actuarial model management
Next step

An assessment of insurance process digitalisation opportunities

A selected quotation, policy or claims scenario can be analysed, including its data, partners, decision rules, and a measurable first version can be defined.

Getting acquainted