Malaysia general insurers missing from AI shortlists

A risk manager at a manufacturer in Shah Alam is reviewing the group's property and engineering programme before renewal. Before calling the broker, she asks ChatGPT: "Which general insurers in Malaysia are strong in industrial all risks and business interruption for manufacturing plants?" Your company writes that business, has a long claims record and ranks well on Google for "fire insurance Malaysia". The AI answer names three other insurers and a broker's blog. For a Malaysia general insurer, that is a seat on the shortlist lost before the formal process starts.

This article is for marketing, digital and commercial lines leaders at general insurers and general takaful operators in Malaysia. It explains why AI assistants leave established commercial insurers off their shortlists, what corporate buyers and intermediaries actually ask, how to audit your position, and what to publish so assistants describe your commercial lines accurately.

Why the general insurer AI shortlist gap happens

AI assistants build shortlists from pages that answer the buyer's scenario in plain words. Most insurer websites are organised by product name and keyword, with the detail locked in policy wordings, PDFs or "contact your agent" forms. That works for search rankings but gives an assistant little it can quote.

The commercial market is large enough to attract plenty of competing content. PIAM, the general insurance association, reported gross written premium of RM24.2 billion in 2025, according to The Star. Motor made up 45.2 per cent of the business, fire 20.9 per cent and marine, aviation and transit 7.4 per cent. Fire and specialty lines are where risk managers do the most research, and where AI answers draw on whoever has explained the risk most clearly.

How the main engines pick sources:

• Google AI Overviews and AI Mode. Google's Search Central documentation says supporting links must come from pages that are indexed and eligible for a snippet. It describes "query fan-out", where one prompt becomes several related searches across subtopics. A question about a plant's property programme may fan out into business interruption, flood, machinery breakdown and claims. A single product page per class covers only one of those.
• ChatGPT search. OpenAI's documentation says OAI-SearchBot is used to surface websites in ChatGPT's search features, and that sites which block it will not be shown in ChatGPT search answers. Security teams at regulated firms sometimes block unfamiliar bots by default.
• Microsoft Copilot. Where a company runs Microsoft 365, staff may ask Copilot at work. Microsoft's documentation says Copilot sends the Bing search service a generated query that "consists of a few words informed by the user's prompt", and that a user's referenced document can shape that query. A risk manager who asks Copilot to compare insurers named in last year's renewal pack will get answers built from what Bing returns for each name.

The result is predictable. Brokers' explainers, comparison articles and rivals with detailed coverage guides become the retrieved proof, even when your underwriting capability is stronger.

What buyers in Malaysia actually ask AI

Commercial buyers ask in English, often with Malay terms and local places: "Klang Valley", "Pasir Gudang", "kilang", "banjir", "CAR", "EAR", "PL". General takaful is part of the same conversation for many buyers.

Understanding the risk (risk managers, CFOs, company secretaries)

• "What does industrial all risks insurance cover in Malaysia and how is it different from a fire policy?"
• "Is flood covered under a standard fire policy for a factory in Selangor?"
• "Insurans kebakaran untuk kilang di Johor, apa yang perlu ada dalam polisi?"

Shortlisting insurers (procurement and risk teams)

• "Which general insurers in Malaysia write contractors' all risks for large infrastructure projects?"
• "Compare insurers for directors' and officers' liability for a Bursa-listed company."
• "General takaful operators offering cyber cover for Malaysian SMEs and mid-size firms."

Checking claims and service (finance and operations)

• "How long does a business interruption claim take with Malaysian insurers?"
• "Is this insurer licensed by Bank Negara Malaysia?"

These prompts mix education, comparison and reassurance. The insurers that appear are the ones whose pages answer all three.

How to check where you stand

You can run a first audit within a week. Our measurement method describes how we do the same thing with larger, repeated prompt sets.

Step 1: Build a prompt set by class of business

Ask your commercial underwriters and broker relationship managers for the questions they hear most. Turn them into 25 to 40 prompts covering fire and industrial all risks, engineering, liability, marine, cyber and any specialty lines you write. Include Malay prompts and takaful variants if relevant.

Step 2: Run them across engines and days

Run each prompt in ChatGPT with search, Copilot Chat with web content on, Google AI Mode and Perplexity. Repeat on at least three different days. Answers vary between runs and users, so one screenshot proves little.

Step 3: Record mentions, sources and the queries behind them

Log whether you are named, where, and which URLs are cited. Microsoft says Copilot Chat shows the exact web search queries it sent to Bing in the citation section. Those short queries are the phrases your line pages must answer.

Step 4: Check accuracy

Where you appear, check every fact against your current position: classes written, risk appetite, claims contacts, branch locations and licence status. Old product names and closed branches are common errors.

Step 5: Check access and indexing

Confirm that robots.txt and your firewall do not block OAI-SearchBot, Googlebot or Bingbot from public product and claims pages. Confirm those pages are indexed in Google Search Console and Bing Webmaster Tools.

How to fix it

The goal is to make your commercial line knowledge readable, factual and consistent. Our content service does this with insurers, but every step below can start in-house with your underwriting and compliance teams.

Build a hub for each class of business

Give each major class its own HTML page: what it covers, who typically buys it, common extensions, common exclusions in plain words, what an underwriter needs for a quotation and how long quotation usually takes. Link the policy wording PDF, but do not make it the only source.

Answer scenarios, not just keywords

Add short scenario sections a risk manager would recognise: a plant after a flood, a contractor with a damaged crane, a data breach at a listed company. Explain which classes respond and what affects the outcome. Keep it educational and factual, and have compliance review every page.

Publish claims facts plainly

Buyers ask AI about claims service. State the claims notification route, documents needed, how loss adjusters are appointed and who the corporate claims contact is. Avoid unsupported promises about speed or outcomes.

Page type	Why AI uses it	What to publish
Class of business hub	Answers "what covers X" prompts	Scope, extensions, exclusions, underwriting information needed
Claims guide by class	Answers service and reassurance prompts	Notification steps, documents, contacts
Broker submission page	Answers intermediary prompts	Submission requirements, appetite, contacts
About and licence page	Answers "is this insurer licensed"	Legal name, licence type, link to BNM's list

Keep entity facts consistent

Use your exact legal name as it appears on Bank Negara Malaysia's list of licensed general insurers, and keep it identical on your site, LinkedIn, PIAM or MTA listings and press releases. Mergers and rebrands leave old names scattered across the web, and AI tools mix them up. Add Organization structured data that matches the visible text, as Google advises.

Earn expert citations

AI answers about commercial risk often cite trade press, broker explainers and industry association material. Put your underwriters and claims leaders forward for bylined articles and conference talks on construction, flood, cyber and marine risk. Our authority service helps plan this. Accurate third-party coverage gives assistants a second source that confirms your own pages.

Give intermediaries their own page

Commercial risks are often placed through brokers and agents, and some of them now use AI tools to scan the market before approaching insurers. A dedicated intermediary page helps both groups. State the classes you write, the information a complete submission needs, typical turnaround for a quotation and the right contact for each region. Keep it factual and current, and date it so an assistant can tell old appetite statements from new ones.

Publish in Malay where buyers do

Many owner-managed firms and their finance staff ask in Malay. Translate core class hubs and claims guides properly rather than machine-translating policy text, and keep terms consistent with your Malay policy documents.

What to measure

Track four measures on a fixed prompt set every month, and after any product launch, rebrand or major claims event.

• Mention rate: the share of prompts in which you are named.
• Citation share: how often your own pages are the cited source rather than brokers or rivals.
• Accuracy: the share of mentions with correct classes, appetite, contacts and licence details.
• Framing: whether you are presented as a specialist in a class or only as a general name.

Report results by class of business, because you may be visible for marine and invisible for engineering. Expect gradual change and month-to-month noise, and treat trends across many prompts as the signal.

Common mistakes

• Leaving commercial lines detail only in policy wordings and PDFs.
• Writing product pages for keywords while ignoring the scenarios risk managers describe.
• Making superlative claims that compliance would never sign off and AI rarely repeats.
• Letting old company names from mergers or rebrands persist in directories.
• Blocking AI crawlers by default without a decision from marketing and compliance.
• Measuring only Google rankings and assuming AI visibility follows.

How Shubi helps

Shubi is an AI visibility company based in Malaysia, working across Asia. Through AI Visibility Intelligence we measure how ChatGPT, Copilot, Gemini, Perplexity and Google describe your commercial lines against rivals, then help you publish facts AI can quote accurately. We do not promise mentions or rankings, and every result we report comes with its prompt set. Message Shubi on WhatsApp