Insurance AI
M

Milliman

Milliman is a global actuarial and consulting firm that also ships a portfolio of named, separately licensed analytics products to insurers, and is judged here on those products rather than on the consulting practice. Milliman IntelliScript serves life and health carriers with data driven risk assessment: Irix medical and prescription histories, the Curv suite of predictive models for identifying unknown risk in groups, and underwriting insight drawn from pharmacy and medical claims records.

Milliman Nodal applies machine learning and natural language processing to structured and unstructured claim data, including adjuster notes, medical notes and police reports, to triage property and casualty claims, predict litigation likelihood, flag excessive medical cost and benchmark spend across workers compensation, auto liability and general liability. Nodal is delivered as a fully managed service with models tailored to each client's own claim and text data on top of a shared reference database, and companies deploying it report average cost savings between five and fifteen percent.

Other products include AccuRate Fleet, a usage based score for pricing fleet exposure and driving behaviour, Datalytics Defense for detecting patterns in attorney billing, an explainable platform for detecting and quantifying fraud, waste and abuse, Market Baskets for property and flood pricing, and the actuarial platforms Arius, Integrate and the Economic Scenario Generator. IntelliScript operates as a consumer reporting agency under the United States Fair Credit Reporting Act and appears on the Consumer Financial Protection Bureau list of consumer reporting companies, so an individual can obtain their own report free of charge and dispute its contents directly. Nodal was named the 2025 InsuranceERM Americas award winner in its category, chosen by an independent panel of industry experts.

Last VerifiedAugust 20, 2026
Compare Milliman with other vendors
Founded
1947
Headquarters
Seattle, Washington, United States
Categories
insurance-ai, fraud-and-transaction-risk
Assessment

Capability Axes

Capability grades

15 of 15 axes rated · 9 graded A or B

AI Capability
AI Centrality
BB on AI CentralityThe models are the engine of a core capability, layered on a product that would still function without them as a rules or workflow system.
Vendor Published

Judged on the products under the services hybrid rule, and the portfolio splits cleanly. Nodal is a pure model product: strip the machine learning and the natural language processing off it and nothing remains, since its entire function is extracting signal from adjuster notes and claim text to predict litigation, severity and excessive cost. The Curv predictive models, the fleet score, the attorney billing algorithms and the fraud detection platform are the same shape.

Against that, the firm also licenses actuarial computation platforms that carry no inference at all, and the largest business by far is consulting. B is the honest middle: several products where the model is the whole thing, inside a firm that is not an AI company.

Autonomy and Oversight Model
BB on Autonomy and Oversight ModelA written commitment that the models work alongside human judgment, with real review surfaces, short of the full control structure: commonly the threshold at which the system stops or what happens after it is wrong.
Vendor Published

Output is scores, alerts and high, medium and low bands presented to a claims department, with the firm's own actuaries, data scientists and claims professionals placed alongside implementation and continuing after it. That is the oxane shape, people staffed next to the model rather than positioned after it as an adjudication layer, which is why this is B rather than A. The specific gap: the product also offers to automate low risk claims so skilled staff can concentrate on complex ones, and nothing published states the threshold for that automation, what review the automated path receives, or what happens when a claim is banded wrongly. As elsewhere in this index, the automated disposal is the point where oversight matters most and is the one point left undescribed.

Model Risk Management and Transparency
BB on Model Risk Management and TransparencyReal transparency mechanisms are published, such as per alert explainability, confidence scoring or split testing, without the validation package or supervisory mapping behind them.
Vendor Published

Three real signals: one product is described as an explainable platform with explainability named as a property rather than implied; models are tailored to each client's own data and claims can be rescored, so versioning and refit are working features; and the firm publishes research built on its own models, including comparative work on machine learning against traditional mortality models and a published analysis using the claims product finding a condition underreported in workers compensation.

Publishing findings from your own models is a transparency route almost nothing here uses. Held off A: no model documentation, performance figures, validation report or drift policy. And a model risk fact that belongs on this row rather than only on the liability row, because it concerns input quality rather than remedy: the statutory obligation to follow reasonable procedures for maximum possible accuracy has been the subject of both a federal enforcement action and class litigation alleging mixed files containing other people's records.

Operational and Outcome Evidence
BB on Operational and Outcome EvidenceVendor aggregate claims with real figures, or audited scale disclosures from a publicly listed company.
Vendor Published

A quantified outcome is published, average cost savings of five to fifteen percent for companies deploying the claims product, and named client work exists including a public risk pool case study. The award for the claims product was chosen by an independent panel of senior industry experts rather than bought. Held at B on the standing shape: the quantified figure is aggregate and self reported, and the named references and the numbers never join.

Worth recording that an unusual independent corroboration exists for the consumer report product, since federal court filings name the carriers receiving its reports, which establishes the installed base from a source with no marketing interest.

AI Safety and Data Stewardship
CC on AI Safety and Data StewardshipGeneral assurances that do not answer the question this axis asks, which is whether one customer’s data trains models serving its competitors. Unbounded cross client learning stated with no boundary grades here too.
Vendor Published

The pooled corpus question again, and this is the most sensitive instance the ladder has produced. The claims product states that it tailors models to a client's own claim and text data while leveraging its own database as support, which means a shared reference corpus sits behind every client model, and nothing published says what enters it, whether contribution is optional, or whether one carrier's claim narratives improve models sold to another.

The underlying material is not trades or public filings but individuals' prescription histories, medical claims, adjuster narratives, medical notes and police reports. Compare the public filings corpus elsewhere in this pocket, which achieves peer comparison from data that is public by law and therefore raises none of this.

Regulatory and Compliance
GLBA and Data Privacy Posture
BB on GLBA and Data Privacy PostureA substantive privacy document that reaches the product itself, short of the subprocessor list or the full data handling detail.
Regulatory Filing

Unusually strong for this index because a statute supplies the posture rather than a policy page. The consumer report business collects under an authorisation the applicant signs, may release only for a permissible purpose, must give an individual free access to their own file within a statutory window, and appears on the federal consumer bureau's official list of consumer reporting companies with the access route published.

Held off A: no data processing detail, subprocessor list or residency statement is published, the data is among the most sensitive in this index, and the accuracy obligations attached to it have been contested in enforcement and in court, which is recorded on the model risk and liability rows.

Security Certifications and Trust Center
CC on Security Certifications and Trust CenterA single footer line, or certifications asserted without being enumerated, which is weaker than naming them because it invites an assumption a buyer cannot check.
Vendor Published

No certification located in the vendor's own material during this pass, so nothing is credited, and the rule that an unverified credential earns nothing has to apply when it costs a grade. Banked check, cheap and specific and likely to move this: a firm handling protected health data at this scale for life underwriting almost certainly holds a service organisation control report and operates as a business associate under the health privacy statute. Look for a trust or security page on the consumer report business, which runs on a separate domain from the parent firm and was not fully swept here.

Regulatory Status and Licensure
BB on Regulatory Status and LicensureThe regulatory position is clearly stated and appropriate to the product, with part of the verification left to the buyer.
Regulatory Filing

The consumer report business operates as a consumer reporting agency, a status defined by federal statute and supervised by the federal trade regulator and the consumer financial bureau, and it appears on the bureau's official published list of such companies.

Critically for consistency with how this index treats large groups, that status attaches to the graded product itself rather than to an adjacent business, which is the exact distinction that held the broking group in this pocket at C for licences that cover broking rather than software.

Held at B rather than A: this is a status acquired by operating in a regulated category with supervisory oversight, closer to programme enrolment than to a licence granted after examination, and the firm has been the subject of an enforcement action under that statute.

AI Governance and Bias Disclosure
CC on AI Governance and Bias DisclosureResponsible artificial intelligence committed to in policy language with no evaluation behind it, on a product whose bias surface is modest.
Vendor Published

No fairness testing, no protected class analysis, no governance disclosure, and the exposure is as direct as any in this index. One model predicts whether a claimant is likely to litigate, which is a prediction about whether a person will assert their rights and correlates with income, geography, language and access to representation. This is the second instance of that exact mechanism in this pocket.

A second product line scores insurability from prescription and medical claim history, which tracks health status and disability by construction and includes mental health prescribing, since the firm's own published research uses that data to study depression. Two of the highest stakes inferences in the index, and silence on both.

AI Liability and Recourse
BB on AI Liability and RecourseA published falsifiable commitment such as an accuracy figure with its method, or a real correction route for the affected person, such as step up verification instead of silent denial.
Regulatory Filing

The first grade above C on this axis anywhere in the index. An individual affected by the consumer report product can obtain their own report free of charge, dispute any item with the vendor directly, trigger an internal reinvestigation, and where the report is revised have the corrected copy sent both to them and to the entity that originally requested it.

That is statutory, individually exercisable and published by the vendor, which is exactly the recourse this index has never previously found. Held firmly at B for two reasons. First, it reaches the underlying data record and not the model: there is no route to contest a predicted litigation likelihood or a risk score, only the facts beneath it. Second, the mechanism has a performance record, and it is poor.

A federal enforcement action was brought under the statute, and class litigation has alleged mixed files containing other people's prescription records, non disclosure of data sources, and a reinvestigation process that pushes the burden onto the consumer, a criticism the vendor's own published process partly matches by asking disputants to obtain records from providers themselves.

Write it up as the finding it is: this is the only vendor in the index whose recourse can be assessed at all, and the reason is that a statute created both the right and the complaint record. The absence of litigation against every other vendor here is not evidence of good behaviour, it is evidence that nobody has standing to sue.

Integration and Deployment
Model Supply Chain Disclosure
CC on Model Supply Chain DisclosureThe architecture is described and no provider is named.
Vendor Published

Cutting edge machine learning techniques, powerful algorithms and proprietary language processing, with no model, provider, architecture or version named anywhere. The interesting asymmetry is that the data supply chain is disclosed at category level, since pharmacies, pharmacy benefit managers and medical providers are named as sources, while the specific sources for an individual record were the subject of a non disclosure claim in litigation, and the model supply chain is not disclosed at any level at all.

Core Systems and Integration Depth
BB on Core Systems and Integration DepthNamed systems or a documented public API, with the depth or the production evidence left open.
Vendor Published

Real depth where it counts: the consumer report products are pulled inside carrier new business workflows at the point of underwriting, which is about as deep into a core process as a data product gets, and Nodal is a fully managed service requiring no client installation, scoring and rescoring claims against a client's own systems of record. The scenario generator is cloud native with an integration ready interface, and the healthcare line ships a data warehousing platform. Held off A because no named policy administration or claims system connector is published, so the integration story is described by function rather than by named counterparty.

Deployment Model and Data Residency
CC on Deployment Model and Data ResidencyCloud only with nothing stated, which is the category norm.
Vendor Published

Described as fully managed software as a service with no client installation, running on hyperscale cloud infrastructure. Nothing published on region, residency, tenancy or hosting arrangements, which is a notable silence for products holding individual prescription and medical claim histories across multiple jurisdictions.

Commercial
Commercial Transparency
CC on Commercial TransparencyNo price is published and engagement runs through a demo form, which is the norm in this index.
Vendor Published

No published price, tier, unit or pricing basis for any product in the portfolio. Everything routes to a contact form. Standard for a consultancy led seller and standard for this pocket, where only the smallest vendor publishes a number at all.

Institution and Segment Coverage
AA on Institution and Segment CoverageThe financial segments served are named and each carries its own maintained material, whether the coverage is broad or deliberately narrow.
Vendor Published

Among the broadest in the index. Buyer types: life carriers, health carriers, property and casualty insurers, reinsurers, self insured employers, third party administrators and health plans carrying government programme risk. Lines: life, health, long term care, disability, annuities, workers compensation, auto liability, general liability, property and flood. Products address underwriting, claims, reserving, pricing, capital and payment integrity, and the firm operates globally rather than in one market.

Alternatives to Milliman

The closest documented capability profiles to Milliman in the same categories, ordered by similarity across the same fifteen axes the index grades every vendor on. Closest documented profile, not a claim that either product does the same job. No vendor pays for placement.

A lighter documented profile than Milliman

Stronger documented coverage on Operational and Outcome Evidence

A lighter documented profile than Milliman

Stronger documented coverage on Core Systems and Integration Depth

Stronger documented coverage on AI Centrality

Documents AI Safety and Data Stewardship where Milliman does not

Similarity is computed axis by axis from published grades, not from a composite score. The index does not aggregate grades into a total. See the fifteen axes and the methodology.

Commercial

Pricing

Vendor-published figures are labeled as such. Figures labeled “Estimated” are derived from third-party sources and have not been confirmed by the vendor.

No pricing data has been verified for this vendor. Pricing information will be published here once confirmed through vendor disclosure or third-party estimation.

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AI FinTech Index

The AI FinTech Index is an independent index that tracks changes to AI vendors in financial services. It holds 489 vendors across banking, lending, insurance, wealth, capital markets and financial crime compliance, each graded on the same 15 capability axes from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
September 5, 2026
The AI FinTech Index is an editorial reference, not a regulatory body. Vendor data is verified against published sources and public regulatory filings. Figures labeled “Estimated” have not been confirmed by the vendor. See the Methodology page for evaluation standards and limitations.
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