Launch a bank from your bedroom? Why not!

I guess the key thing about becoming an AI-native bank is to start with a clean sheet of paper. Most banks are adding AI services to old systems and dysfunctional processes; what we should be doing is starting from scratch, creating an AI core that looks at how to deliver the best customer experience.

For example, when asking ChatGPT how to build an AI-native bank account, I got this:

Great question — let’s unpack what an AI-powered bank account could look like. This is not just a “digital account” (which already exists with Monzo, Starling, Revolut, etc.), but one where AI is embedded at the core of how the account works.

1. Core structure of an AI bank account

• Regulatory shell: it’s still a bank account under FCA/PRA rules (deposit protection, KYC/AML, Consumer Duty). The AI sits on top of a standard current account, not outside regulation.
• Data foundation: connects to transaction history, open banking feeds, credit file, savings/investments, bills, and (with consent) employment/benefits data.
• AI orchestration layer: an intelligent agent that analyses transactions, predicts cash flow, monitors risks, and executes automations with safeguards.
• Channels: app, voice, chat, maybe API for third-party services.

2. What the AI actually does

Everyday money management

• Categorises spend automatically (groceries, bills, subscriptions, etc.).
• Spots duplicates, errors, or fraud patterns faster than humans.
• Flags “you’ll be short £120 before payday unless you adjust X.”

Smart saving & investing

• Predicts when disposable income is genuinely safe to sweep into savings/investments.
• Auto-allocates into “goal pots” (holiday, emergency fund, mortgage overpayment).
• Uses reinforcement learning to adjust how aggressive/conservative to be.

Cashflow & credit

• Real-time creditworthiness: AI can suggest an overdraft or micro-credit line before a bounce occurs.
• Could auto-refinance overdraft into a cheaper product (with customer consent).

Payments & automation

• Natural-language “rules”: e.g. “Pay my rent on the last weekday before the 1st.”
• Negotiates better tariffs (energy, broadband) by scanning market APIs and switching with approval.

Security & compliance

• Continuous anomaly detection (location/device vs. spend pattern).
• Adaptive KYC: asks for more proof only when signals are weak.
• Transparent explanation of why payments are held, declined, or flagged.

3. Tech stack under the hood

Layer	AI role	Examples
Transaction understanding	NLP + embeddings	categorise, merchant match
Forecasting	Time series ML	salary, bills, cashflow
Risk	Anomaly, fraud models	out-of-pattern spend
Advisory	LLM + policy layer	explain finances, answer queries
Orchestration	Agent planner	decides when to move, block, suggest

4. Safeguards

• Explainability: user must see why the AI moved money or blocked a payment.
• Consent gates: defaults conservative; automation only after opt-in.
• Regulator alignment: FCA Consumer Duty requires fair, understandable advice.
• Human override: customer or bank staff can always reverse/stop an action.

5. What it feels like to the customer

• Instead of just seeing a balance, you see “projected balance until next payday”.
• Instead of static pots, you get an AI budget coach that updates weekly.
• Instead of asking “why was my card declined?”, you get an immediate explanation in plain English.
• Feels less like a ledger, more like a financial autopilot with co-pilot mode.

👉 Do you want me to sketch how this AI bank account would earn money for the bank (business model side), or how it would be architected in phases if you were building it?

Pretty impressive?

Well, let’s take a harder one. ChatGPT: please create an AI-native mortgage process, and here’s what I got:

Here’s a practical, UK-centric blueprint for how an AI system would build an end-to-end mortgage lending process using design rules of “compliance-first,” human-in-the-loop, and production-ready.

1) Ground rules (baked in from day one)

• Responsible lending & affordability (FCA MCOB 11): every automated step must evidence affordability checks and produce an audit trail for human review. FCA Handbook+1
• Consumer Duty + transparency & fairness (ICO): explain what data is used, why, and provide meaningful explanations; test for bias; respect safeguards on solely automated decisions. ICO+2ICO+2
• Model Risk Management (PRA SS1/23): register every model (credit, AVM, pricing, fraud, LLM extractors) in an MRM framework with validation, monitoring, and governance. Bank of England+1
• Open Banking (with consent): use bank-transaction data to streamline income/expense verification and affordability. Open Banking+1
• Property valuation standards (AVMs): use AVMs with guardrails and escalation to human valuation when confidence is low. RICS+1
• Stay current on FCA changes: e.g., Mortgage Rule Review updates (July 22, 2025) reaffirm affordability expectations. FCAFCA Handbook

2) System architecture (layers)

Data & Integration

• KYC/AML, credit bureaux, land registry & property data, payroll/payslips, Open Banking feeds, document uploads.
• Feature store + data quality layer; immutable audit log.

AI/Decisioning

• Rules engine for eligibility & policy.
• ML models: identity/fraud, income inference, expense categorisation, affordability & probability-of-default, early-warning.
• AVM for property; confidence scoring & overrides.
• Pricing & offer optimisation constrained by policy.
• LLMs for document OCR/classification/extraction & applicant Q&A (answers sourced from policy, not free-form).

Orchestration

• Workflow engine (case state machine), human review queues, explanation generator, document composer (ESIS/offer), monitoring dashboards.

Channels

• Web/app chat/voice assistant for borrowers; adviser console for underwriters. (Real-world analogue: Better.com’s “Tinman” platform + “Betsy” voice AI for pre-approval/locking, with humans in the loop.) investors.better.comBetter MortgageHousingWire

3) The end-to-end flow (what the AI actually does)

1. Pre-application & triage
   • Collect goals, property & applicant basics; eligibility rules filter obvious no-fits.
   • With consent, pull Open Banking data to estimate income/expenses and show an indicative borrowing range with clear caveats. Open Banking
2. Identity, fraud & KYC/AML
   • eIDV + liveness + document check; device & behavioural signals; sanctions/PEP screening.
   • Fraud model flags anomalies; high-risk routes to manual review (never auto-decline without human sign-off).
3. Document intake & truth-matching
   • OCR/classify payslips, P60s, tax returns; LLM extractors populate fields; cross-check against Open Banking and employer data; surface discrepancies to an underwriter, not the customer.
4. Affordability & credit decisioning
   • Rule-constrained ML calculates stressed affordability and risk; policy caps (LTV, DTI) enforced; explanation object generated for every decision to satisfy MCOB + transparency duties. FCA HandbookICO
5. Property valuation
   • Run AVM; if low confidence or edge cases (new builds, unusual properties), escalate to desktop/full survey per RICS guidance. RICS+1
6. Pricing & offer
   • Optimiser proposes rate/fee options within risk & policy bounds; adviser reviews; system composes ESIS and pre-populates conditions; human releases the offer.
7. Conveyancing & completion
   • Milestone bot chases outstanding actions; monitors changes (e.g., new credit, bank activity) and alerts for re-underwrite if needed.
8. Post-completion monitoring
   • Early-warning models watch payment behaviour and macro signals; trigger proactive support if risk rises (Consumer Duty).

4) Minimal model inventory (keywords only)

Area	Core models (keywords)	Key inputs	Key outputs
Fraud/KYC	anomaly, identity, device	ID docs, device, OB txn	risk score, flags
Income	payslip parser, OB classifier	OCR, OB txn	net/gross income
Expenses	merchant & category	OB txn	essential spend
Affordability	stress calc, PD/LGD	income, spend, credit	max loan, buffers
Valuation	AVM, confidence	comps, geodata	value, CI, escalate
Pricing	risk-based optimiser	PD/LGD, LTV	APRC, fees, ESIS data

5) Governance & controls (non-negotiables)

• MRM (PRA SS1/23): model registry, validation, backtesting, change control, performance & drift monitoring, challenger models, and independent review. Bank of England
• Fairness & transparency (ICO): bias tests across protected characteristics; clear notices; human review for high-impact outcomes; accessible explanations. ICO+1
• Affordability evidence (FCA): store data, checks, and rationale per case; reproducible “why approved/declined” trails. Recent FCA updates (July 2025) still expect robust affordability consideration. FCA

6) What to build vs buy (quick take)

• Buy: Open Banking connectivity, eIDV/liveness, credit bureau connectors, e-signature, conveyancer integrations, AVM providers. Open Banking
• Build (or customise): orchestration/workflow, feature store, affordability & risk models, explanation service, adviser console, document composer.
• Hybrid: OCR/LLM pipelines (hosted but with your prompts/schemas), pricing optimisers bound by your policy.

7) KPIs to run the business

• Time-to-“Yes”, % straight-through decisions, manual-review rate, doc-defect rate, cost/loan, fairness deltas (approval & pricing), AVM-to-survey variance, and adverse-action explanation quality.

Why this is realistic

Lenders are already doing parts of this: e.g., Better.com publicly documents a unified platform (“Tinman”) and a voice AI assistant (“Betsy”) that can pre-approve and lock rates—with humans supervising. It’s a concrete proof-point for AI-orchestrated underwriting while keeping advisers in the loop.

How AI Mortgage Lending is Transforming the Home Loan Process

Better launches voice-based AI loan assistant

If you want, tell me your context (new lender vs. incumbent, UK only vs. multi-region), and I’ll tailor this into a phased build plan (90/180/365 days) with suggested vendors and an MRM checklist.

That’s pretty awesome! What about the key things to consider when moving home?

That’s a big step—exciting and a little overwhelming! Moving house and then turning it into a home involves both practical planning and emotional settling. Here are the key things to consider:

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🏠 Before the Move

1. Declutter & Downsize

   • Go room by room and decide what to keep, donate, sell, or discard.

   • Less to move means cheaper and easier logistics.

2. Plan the Logistics

   • Book movers (or a van) in advance.

   • Measure doorways and large furniture to make sure it fits.

   • Collect packing supplies (boxes, tape, labels, bubble wrap).

   • Pack essentials separately (clothes, toiletries, charger, important documents).

3. Admin & Utilities

   • Notify banks, insurance, work, doctors, etc. of your new address.

   • Arrange utilities: electricity, water, gas, internet.

   • Update your driver’s license, voter registration, subscriptions.

4. Financial Planning

   • Budget for movers, deposits, cleaning, new furniture, and unexpected costs.

   • Keep receipts for tax or employer reimbursements (if applicable).

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🚚 During the Move

1. First-Night Essentials

   • Pack a “first-night box” with bedding, towels, kettle/coffee, snacks, and basic toiletries.

   • Keep important documents and valuables with you.

2. Safety & Cleanliness

   • Do a quick clean of the new space before furniture arrives.

   • Check smoke alarms, locks, and water shut-off points.

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🪴 After the Move – Making It a Home

1. Unpack Strategically

   • Start with the bedroom (rest matters), then kitchen, bathroom, and living space.

   • Don’t rush—set realistic goals (a few boxes a day).

2. Layout & Functionality

   • Arrange furniture to suit your lifestyle (light, flow, comfort).

   • Test different layouts before committing.

3. Personal Touches

   • Add familiar items—photos, favorite blanket, plants.

   • Lighting, scents (candles, diffusers), and music can instantly make a place feel like yours.

4. Community & Surroundings

   • Explore your neighborhood: grocery stores, cafes, parks, transport.

   • Introduce yourself to neighbors (a smile and hello goes a long way).

5. Routine & Comfort

   • Establish new routines quickly (morning coffee spot, walking routes).

   • Balance unpacking with rest and small moments of enjoyment.

6. Longer-Term Projects

   • Think about decorating, DIY projects, or renovations slowly.

   • Prioritize comfort and functionality before aesthetics.

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👉 A good mindset: treat moving not just as relocation, but as an opportunity to reset habits, reorganize life, and design your environment intentionally.

What about the key financial things to think about?

Great question — the financial side of moving house is often underestimated, and costs can creep up quickly. Here are the key financial things to consider, broken down into stages:

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🔑 Before Moving

1. Upfront Costs

   • Deposit / Down Payment (if buying or renting).

   • Stamp duty / taxes (if purchasing).

   • Agency or solicitor fees (legal, conveyancing, credit checks).

   • Survey / inspection costs (for buyers).

2. Moving Costs

   • Professional movers or van hire.

   • Packing supplies (boxes, tape, bubble wrap).

   • Cleaning fees (end of tenancy or preparing your old home for sale).

   • Storage (if there’s a gap between moving out and in).

   • Insurance for belongings in transit.

3. Utility Transfers

   • Connection / disconnection fees (internet, gas, electricity, water).

   • Overlap costs if you’re paying for both old and new utilities temporarily.

4. Travel & Time Off

   • Fuel, transport, parking permits on moving day.

   • Lost earnings if you take time off work.

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🏡 After Moving In

1. Ongoing Monthly Costs

   • Mortgage or rent (be mindful if it’s higher than before).

   • Utilities (internet, electricity, gas, water, trash collection).

   • Council tax / property taxes.

   • Insurance (contents and buildings).

2. Furnishings & Essentials

   • Furniture (beds, sofa, table, storage).

   • Appliances (fridge, washing machine, microwave, etc.).

   • Curtains, blinds, rugs (often forgotten but expensive).

   • Small household items (kitchenware, cleaning supplies, lightbulbs).

3. Unexpected or Hidden Costs

   • Repairs / maintenance (especially in older homes).

   • Security upgrades (locks, alarms, cameras).

   • Service charges or HOA/condo fees (if applicable).

   • Decorating (paint, wallpaper, tools).

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📊 Financial Planning Tips

• Create a moving budget with “planned” and “buffer” categories (10–15% extra for surprises).

• Compare movers’ quotes and check insurance coverage.

• Track overlapping bills — make sure you’re not double-paying utilities or rent.

• Plan cash flow — large lump sums (deposits, fees) can strain liquidity, so keep an emergency fund.

• Review affordability long term — higher housing costs shouldn’t crowd out savings or lifestyle needs.

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👉 Would it help if I put this into a moving house financial checklist / budget template (Excel or Google Sheets) so you can track and estimate your own costs?

In all of this process, we have banks saying that they are not selling mortgages but making homes ... and yet, ChatGPT in a minute or two, has done far more to guide this simple user to answers the bank has never offered me in my many house moves over time. Maybe GenZ will get all of their financial advice from AI whilst fintech visionaries will start building AI-native financial services by asking basic questions like the ones above. After all, this is not rocket science. In fact, an AI-driven bank could be created by anyone, anywhere in a short space of time. Getting a licence to sell such services takes more time but, over time, you could even envisage an AI regulator authorising AI processes from someone who asked for a licence from the designs they made in their bedroom.

The day of the bedroom-based AI-native bank is right here, right now and, for those who think it is way more complicated than this, or for those who think it is far more important to continue with their current operations, well, there’s a song about that.

https://www.youtube.com/watch?v=zkHOVJINRD8

 

You've done me wrong
Your time is up
You took huge fees
For your bonus cup

Move right out of here, bank, go and pack your bags
'Cause I'm moving on up
You're moving on out
Moving on up
Nothing can stop me