How we ranked Steve Chenin ChatGPT’s top answers.

The starting point

Steve is one of the highest-volume loan officers in the country, with an average loan size above $1.5 million. But most of his business comes through private banking relationships, and online he was mostly a line in a bank directory. His name, title and NMLS number appeared differently across his Wells Fargo profile, LinkedIn and third-party listings, and nothing explained what he specializes in. Asked for a Bay Area jumbo loan officer, ChatGPT had little to say about him.

AI assistants recommend people they can describe with confidence. So the job was to make Steve easy to describe: one clear identity, one clear specialty, and plenty of trusted sources that agree.

The GEO strategy we ran

1. One consistent identity everywhere

We locked a single version of his name, title, company, NMLS number, service area and office phone, then matched it on his Homes AVM website, Google Business Profile, Bing Places, Apple Business Connect, LinkedIn, Zillow and the NMLS Consumer Access record, all pointing back to his Wells Fargo profile. ChatGPT search leans on Bing, so Bing Places and Bing Webmaster Tools were set up first.

2. Structured data that says who he is

His website carries Person, FinancialService and FAQPage schema, with sameAs links tying the site to his LinkedIn and Wells Fargo profiles. That gives AI crawlers a machine-readable summary: Steve Chen, private mortgage banking, jumbo loans, Bay Area, NMLS 714948.

3. Pages that answer the questions affluent buyers ask

We wrote answer-first pages for the prompts that matter in his market, each one built around a direct answer in the first paragraph followed by detail:

• Jumbo loan requirements in California for 2026
• Buying in Palo Alto, Los Altos and Cupertino: how jumbo financing works
• Using RSUs and bonus income to qualify for a jumbo loan
• Private mortgage banking: what it is and who it is for
• Bay Area jumbo loan officer FAQ

4. Reviews that name the market and the loan

After every closing, Homes AVM sends the client a request that suggests mentioning the city and loan type. Reviews like “Steve handled our jumbo loan in Sunnyvale” teach AI assistants what he is known for, in the client’s own words.

5. Mentions from trusted sources

His national production ranking is exactly the kind of third-party proof AI assistants cite. We made sure those rankings, along with agent partner pages and local market commentary, link to his website with consistent details.

6. Monthly home reports that keep him relevant

Past clients receive a monthly Homes AVM report on their home value and equity. That steady engagement brings repeat visits, new reviews and refinance conversations, which keeps his profile fresh in the sources AI assistants read.

The result

Today, when someone asks ChatGPT for a top loan officer for jumbo loans in the Bay Area, Steve is in the answer, described as a private mortgage banking leader who specializes in high-value homes. We track that prompt and a dozen related ones every month across ChatGPT, Perplexity, Gemini and Google AI Overviews.