01IND-03
Underwriting memo drafts
The file summarized into your memo template, every figure linked to its source.
IND-03 · FINcstmAI™ · Custom AI for · Financial Services
Custom AI for financial services, documented for model risk.
Banks, lenders, insurers and investment firms need AI that examiners and model-risk teams can follow. We build underwriting support, KYC review and research tools with evaluation evidence and audit logs from the first day, on hardware you control.
Fig. 01 · Wiring a motor controller, NASA JPL
In financial services the question isn't whether a model is clever but whether you can explain, validate and monitor it. We deliver what model-risk teams ask for (intended use, evaluation results, known limitations and a monitoring plan) alongside the system itself.
Customer data stays on your hardware, which simplifies vendor-risk and data-residency reviews, and every request is logged for records retention.
| Typical data | Loan files, financial statements, KYC documents, research, call notes |
|---|---|
| Common systems | Loan origination, core banking, CRM, data warehouse |
| Hardware | cstmAI Rack or Cluster in your data center |
| Rules in play | GLBA safeguards, records retention, model risk management |
Common financial builds
Analyst-facing tools with the evidence to back them.
02IND-03
KYC document review
Documents checked against requirements, with gaps flagged for an analyst.
03IND-03
Research search
Cited answers across research, filings and internal notes.
04IND-03
Claims intake
First notice of loss and supporting documents structured for adjusters.
05IND-03
Internal service assistant
Answers for staff from policies, product terms and procedures.
06IND-03
Reconciliation exceptions
Breaks explained and grouped, with suggested resolutions for review.
Reel 02 · Milling and boring area, Paterson, NJ1994
How it's delivered
Four steps, each one signed off.
01
Discovery
Two weeks: pick the workflow, audit the data, size the hardware, write the evaluation set.
02
Build
A fixed-scope build against that evaluation set, reviewed every week with your team.
03
Burn-in & install
Hardware tested on our bench, then installed and connected on your site.
04
Operate
Your team runs it with our runbooks, or we run it for you.
FAQ
Questions we hear first.
Can you support model validation?
Yes. We deliver evaluation sets, results and documentation in a form your model-risk team can test independently.
Does any data leave our environment?
No. Models run on your hardware, and nothing is sent to an outside model provider.
Which tasks are safest to start with?
Internal, analyst-facing work where a person reviews every output: memo drafts, document review and research search.
Get a quote
Spec your system.
Tell us the models you want to run, how many people will use them and where the hardware should live. An engineer replies with a first configuration and the questions that decide the quote.