Individuals (B2C)
Retail banking customers, borrowers, insureds, retail investors, and payment end-users. The mass-market side of the book.
Holds an accountWho it servesTwo sides, one
Two sides, one
infrastructure.
Individuals on a B2C model and institutions on a B2B model share the same infrastructure but optimize toward different outcomes under different trust and compliance regimes. The substrate is shared. The dials are not.
Institutions (B2B)
Corporate treasury, asset managers, hedge funds, pension funds, insurers, and correspondent banks. The high-value, contract-led side of the book.
Carries the systemShared Infrastructure
Exchanges, clearinghouses, central banks, payment networks, and the regulators that govern them. The system both sides depend on to clear and settle.
Routes & settlesRegulated trust
Outcome Stakeholder
How it serves them
Five subindustries, one underlying logic: risk pricing.
01
02
03
04
05
01
Capital markets
Origination, trading, settlement, custody, and research. The high-velocity, latency-sensitive surface where alpha and execution quality compound.
OriginationTradingSettlementCustodyResearch
02
Banking
Lending, deposits, payments, treasury, and wealth management. The mass-market and corporate layer where balance-sheet productivity meets customer experience.
LendingDepositsPaymentsTreasuryWealth
03
Insurance
Underwriting, policy administration, claims, and reinsurance. The long-horizon book where underwriting accuracy and claims cycle time decide combined ratio.
UnderwritingPolicy adminClaimsReinsurance
04
Fintech
Payments infrastructure, digital lending, embedded finance, and crypto. The infrastructure layer collapsing settlement time and unbundling the bank.
Payments infraDigital lendingEmbedded financeCrypto
05
Real estate
Origination, valuation, asset management, title and settlement. The capital-intensive long-cycle asset class where data fragmentation decides deal speed.
OriginationValuationAsset mgmtTitle & settlement
Every transaction is a bet on a future state.
Money exchanging hands conditionally. A loan repays, a policy does not trigger, a trade settles, a premium holds. The medium is not the money itself but the conditional logic that governs when and how it moves.
What we're optimizing
inside the envelope.
Five targets across the firm. The dials don't all move in the same direction. Returns pull against risk, coverage pulls against loss ratio, customer experience pulls against control, innovation pulls against the compliance envelope. Trust decides the trade.
#StakeholderOutcomeDirection · Current → TargetPriority
00Regulated trustThrough-lineBetter customer and counterparty outcomes.current → faster, safer, cheaperTiebreaker
01Investment & LendingReturnsHigher returns.alpha · NIM → +N ptsHigh
02InsuranceCoverageBetter coverage and combined ratio.premium / loss → improvingHigh
03RetailCustomer experienceBetter holistic customer experience.days/case → minutesHigh
04FinanceMarginHigher risk-adjusted margin.RAROC → +N ptsHigh
05ComplianceEnvelopeStronger regulatory compliance.findings · breaches → near-zeroGate
06Speed ↔ ControlConstrainedShip faster without breaking the compliance envelope.velocity ↔ controlConstrained dial
The throughline
Every financial firm is a risk-pricing machine.
The AI opportunity is compressing the gap between signal and decision: faster underwriting, real-time risk, personalized pricing. The non-negotiable constraint is that every model must be explainable to a regulator. The firms that win close the gap without sacrificing the explainability that earns them the right to operate.
01 · What's known
The data fabric
- Loan bookLending
- Trading historyMarkets
- Claims recordInsurance
- Customer profileIdentity
zeb + you
We build the resolving layer
03 · What gets decided
The decision
- Faster underwritingSame-session
- Real-time riskPre-trade
- Personalized pricingPer customer
- Explainable modelsAuditable to regulator
- Regulatory reportingFirst-submission clean
Where zeb connects.
The Engagement
= Reshaping toward this orbitNot configuration
The work itself
= Reshaping toward this orbitNot configuration
The work itself
01 · Source systems
where banking, markets, and insurance data originate
Core banking · Trading · Policy admin · CRM · Market data · Regulatory reporting02 · Data fabric & ontology
the unifying schema across customer, transaction, and risk
Unified customer identity · Risk ontology · Transaction graph · Regulatory taxonomy03 · Workflows
underwriting to reporting, intake to payment, onboarding to activation
Underwriting → Execution → Settlement → Reporting · Claims intake → Adjudication → Payment · Onboarding → KYC/AML → Activation04 · Value chain handoffs
where latency is measured in days and should be measured in seconds
Front-office → Middle-office · Origination → Servicing · Underwriting → ClaimsFeatured Financial Services Stories
View all customer stories
Integration
How We Built 100% Seamless Data Integration and Scalable Analytics Foundation for a Fintech Client
Data & Analytics
How we streamlined financial data management and enhanced 40% operational efficiency for Credit Genie
ServiceNow
How We Simplify Workflows and Drive Digital Transformation With ServiceNow
Move faster inside
compliance.
Let's build something that lasts. Our team is ready to talk.