Sei AI Blog
Insights on AI-powered compliance, voice agents, document intelligence, and customer experience for financial institutions.
Reg X §§1024.35 and 1024.36 on the AI Servicing Desk: The Five-Day Ack, the Thirty-Day Substantive Response, and the Categorization Problem That Decides Everything
The mortgage servicer's Notice of Error and Request for Information rules under Regulation X 1024.35 and 1024.36 are the two response clocks that produce more CFPB findings than any other servicing provision. The categorization of a borrower's letter or call is the decision that sets the clock, and the AI agent that gets the categorization wrong hands the servicer a violation the servicer will not know about until the exam. The architecture we run to keep the clock, the categorization, and the response record aligned.
Elder Financial Exploitation on the Voice Channel: What the Senior Safe Act, FinCEN FIN-2022-A002, and the State APS Handoff Actually Ask the AI Agent to Do
Elder financial exploitation is the fraud pattern retail bank compliance teams talk about the least and lose the most on. The Senior Safe Act, FinCEN's 2022 advisory, and the state Adult Protective Services reporting statutes set the response the bank is expected to run when the agent detects it, and the voice channel is where most of the signal lives. The detection cues we score, the temporary-hold decision the agent does not make alone, and the reporting flow the branch does not have to design from scratch.
The Beneficial Ownership Intake the Commercial Bank Still Has to Run: CDD Rule 1010.230, CTA/BOI After the March 2025 Interim Rule, and Where the AI Agent Sits
The Corporate Transparency Act's beneficial ownership filing regime has been through two injunctions, a Supreme Court stay, and a March 2025 FinCEN interim final rule that exempted domestic reporting companies. What has not changed is the bank's independent Customer Due Diligence rule at 31 CFR 1010.230, which requires beneficial-ownership collection at legal-entity account opening under the same 25 percent and substantial-control tests. The intake architecture we run on the commercial-banking desk while the two regimes remain unaligned.
The Annual Escrow Analysis Under Reg X 1024.17: Aggregate Accounting, the Two-Month Cushion, and the Explanation the AI Servicing Agent Owes the Borrower
Escrow analysis is where servicing math meets borrower incomprehension, and where a small computational error at the servicer produces a large volume of borrower calls the agent has to answer accurately. Reg X 1024.17 sets the aggregate-accounting method, the two-month cushion limit, and the shortage/surplus/deficiency rules the analysis has to produce. The intake the agent runs so a borrower gets the actual explanation the analysis warrants, and so the servicer does not create an error under its own rule.
Ability-to-Repay Under Reg Z 1026.43 in AI-Assisted Underwriting: The Eight Factors, the Revised General QM Price Test, and the Documentation Boundary the Agent Cannot Cross Alone
The ATR/QM rule at Reg Z 1026.43 has been through three rounds of major revision since 2013, and the current General QM definition anchors on an APR-to-APOR price threshold rather than the old 43-percent DTI cap. AI underwriting participates in ATR analysis by producing the eight-factor computation, but the documentation of the third-party verification the rule requires and the qualification decision the rule allocates to the creditor are places the agent's autonomy stops. Where AI actually sits in the ATR workflow and what the audit file has to contain.
RESPA Section 8 and AI-Driven Mortgage Referrals: The Anti-Kickback Architecture for Lead Routing, MSAs, and Co-Marketing
Lead-routing scores, AI co-marketing tools, and pay-per-application platforms have rebuilt the mortgage referral economy in vocabulary that maps very cleanly onto the RESPA Section 8 'thing of value' standard. The posture we put in front of marketing and partnerships so an AI workflow does not produce a 12 CFR 1024.14 finding the next exam catches.
HMDA Data Integrity for AI-Driven Loan Origination: The Reg C LAR Fields, the Resubmission Threshold, and the Audit File That Survives
AI agents on the mortgage intake desk now populate a meaningful share of the 110 HMDA LAR fields before a human ever looks at the file. The Reg C accuracy rules and the CFPB resubmission threshold catch the gaps before fair-lending analysis ever runs, and the architecture has to make field provenance and correction provable per loan.
The SAFE Act Line for AI Mortgage Assistants: When Quoting a Rate Becomes Loan Origination and What NMLS Cares About
The SAFE Act and Reg G/H were written for human MLOs and the definition of 'loan originator' bites on any person who takes an application or offers or negotiates loan terms. AI assistants on the mortgage intake desk straddle that line without realizing it, and the state regulators that examine NMLS are starting to ask. The boundaries we hold the agent to so the institution does not have to sponsor a license for software.
GLBA Safeguards for AI Vendors: 16 CFR 314, the Interagency Guidelines, and the 30-Day Notification Bank IT Cannot Push to Anyone Else
The FTC's 2023 Safeguards amendments added a 30-day breach-notification duty and a list of nine information-security elements every covered non-bank financial institution has to encode. Banks operate under parallel Interagency Guidelines with their own notification rule. AI vendors sit inside both perimeters and the institutions we serve are running diligence and contract terms that anticipate what the next regulator will ask for.
UCC Article 4A and the AI Wire-Verification Architecture: Commercially Reasonable Security Procedures When the Caller Is Verified But the Instruction Is Not
Wire fraud losses are running at multi-billion-dollar annual totals and the legal allocation of those losses runs through UCC Article 4A's commercially-reasonable-security-procedure standard. AI voice authentication of the caller does not, by itself, satisfy the security procedure for a payment instruction. The architecture we run so the bank's Article 4A position holds in court when the instruction was the fraud.
California's Final ADMT Regulations for Banks and Lenders: What the CPPA Lands on Significant Decisions and What Is Due in 2027
The California Privacy Protection Agency finalized its automated decisionmaking technology regulations in late 2025, with phased compliance through 2027 and 2028. The pre-use notice, the access and opt-out rights, the risk assessment attestation, and the cybersecurity audit, applied to a bank or non-bank lender's AI agent on a California consumer.
Sei AI vs Observe.ai: Voice AI Built for Mortgage Lenders and Servicers
A detailed, mortgage-specific comparison of Sei AI and Observe.ai — from speed-to-lead and loan-officer appointment booking to FDCPA-compliant servicing calls and 100% QA against TRID, RESPA, and UDAAP.
BOOK A DEMO
- Deploy in weeks, not months
- Trained on FDCPA, TCPA, TILA, UDAAP, and RESPA
- SOC 2 Type II and PCI DSS L1 certified
- Integrates with your LOS, CRM, and telephony
