Case Study
BANKING
1
Customer Onboarding and KYC
Challenge
KYC files were built by hand. Analysts pulled adverse media, sanctions results and corporate data from disconnected systems. One file took two to five days. Most of that time was searching, not deciding. Customers dropped off. Regulators flagged the inconsistency.
Solution We Built
- Automated eKYC and KYB reads IDs, corporate filings and ownership documents.
- Screens against sanctions, PEP and adverse media in one flow.
- Business Rules Engine approves low risk cases straight through. Unclear ones go to a compliance officer with the evidence already assembled.
- Full audit log on every case from intake to decision.
Impact It Created
- Dossier turnaround from days to under an hour on standard cases.
- Manual desk research down 40 to 60 percent.
- Full audit trail on every case, ready for examination.
- Fewer customers abandon during verification.
How We Made It Sustained
- Compliance team owns the screening rules. Regulations change without an engineering cycle.
- Scales to KYB and periodic KYC on the same platform.
- New jurisdictions need a rule set, not a redesign.
Days to under an hour
40 to 60 percent less desk research
Core banking systems never touched
2
Risk Management and Regulatory Compliance
Challenge
Transaction monitoring, control testing and regulatory tracking each sat in separate teams with separate tools. Analysts spent the day clearing false positive alerts while real risk surfaced late. Mapping new circulars to policy was a quarterly manual exercise. Gaps stayed open for months.
Solution We Built
- BRE Engine holds control logic as configurable rules, not scripts.
- Temporal orchestration links monitoring workflows so a flag in one area raises scrutiny in another automatically.
- IDP reads incoming regulatory circulars and maps obligations against existing controls.
- Natural language reporting so compliance teams query outputs without SQL.
Impact It Created
- Alert triage time down 30 to 50 percent.
- Regulatory change to control gap moved from quarterly to continuous.
- Evidence trails generated automatically on every action.
- Every automated decision carries a written rationale.
How We Made It Sustained
- Compliance owns the rules and updates them as regulations change. No vendor backlog.
- New risk domains or jurisdictions plug in without redesigning the workflow.
- Audit trails are an output of the process, not an afterthought.
30 to 50 percent faster alert triage
Quarterly compliance reviews replaced by continuous monitoring
3
ADA Liquidation and Bank Statement Reconciliation
Challenge
Reconciling bank billing statements against provider invoices across 11,000 accounts took 65 to 70 person days every month across three people. Effort rose with volume, not complexity. A multi year backlog built up. Audit preparation meant collecting evidence scattered across repositories.
Solution We Built
- Proprietary IDP using OCR, Vision Language Model and LLM reads bank statements and invoices across many PDF formats, with a confidence score on every field.
- AI agents watch billing inboxes continuously. Intake is no longer a monthly scramble.
- BRE Engine flags mismatches, missing invoices and charges on terminated accounts.
- People handle exceptions only.
Impact It Created
- Monthly effort down 70 to 75 percent, from 65 to 70 person days to 10 to 20.
- 65 to 70 percent of team capacity released.
- 540 to 620 person days saved annually.
- Multi year backlog cleared without temporary staff.
- Proof of payment produced by the reconciliation itself, not assembled by hand.
How We Made It Sustained
- Existing payment controls left untouched. Automation works inside the current environment.
- New provider formats added as configuration, not a rebuild.
- Automation scope widens as confidence scoring proves out per document type.
70 to 75 percent less monthly effort
540 to 620 person days saved a year
11,000 accounts reconciled automatically
Backlog cleared on the same platform as live work
4
Financial Spreading and Credit Memo Generation
Challenge
Commercial underwriters extracted figures from tax returns, financials and entity filings by hand, then wrote credit memos themselves. Complex borrowers took days per file. The team hit a monthly ceiling on how many files it could clear. Loan decisions ran late.
Solution We Built
- IDP extracts and normalises financial figures from statements, filings and entity documents.
- Ownership and cash flow traced automatically across related entities.
- Credit memo drafted with every figure cited to its source document and page.
- BRE Engine flags policy exceptions automatically.
Impact It Created
- Credit memo preparation from days to hours on standard files.
- More files per underwriter without more headcount.
- Every decision carries a source cited audit trail.
How We Made It Sustained
- Sits alongside the existing loan system. No migration required.
- New filing types added as configuration.
- Credit team updates policy thresholds directly in the BRE.
5
Personalised Wealth Management
Challenge
Building a personalised view for each client required advisor time. Account data, transaction history and holdings sat in different systems and had to be pulled manually. Mid tier clients received generic, segment based advice. Cross sell was limited.
Solution We Built
- Client intelligence layer aggregates accounts, transactions, lending and goals into one live profile.
- Relevant recommendations surface in the relationship manager workspace before client meetings.
- Natural language queries let managers identify which clients need attention, no data team needed.
- Human advisor stays in the loop on all suitability decisions.
Impact It Created
- Advisory quality extended to the mass affluent segment, not just top tier clients.
- Relationship manager prep time before meetings fell noticeably.
- More relevant product recommendations supporting better cross sell.
- Clients receive timely nudges rather than quarterly generic statements.
How We Made It Sustained
- New product lines plug into the same client data model.
- Suitability rules updated centrally and applied consistently at every touchpoint.
- Bank retains client data rather than renting it from a third party platform.
6
AI Customer Support
Challenge
A scripted chatbot handled only basic queries. Anything needing account context went to a live agent. Wait times climbed, especially at night and on weekends. Customers named slow, impersonal service as their top complaint.
Solution We Built
- Generative AI handles multi turn questions instead of matching a fixed script.
- Connector Framework pulls real account context so answers are specific, not generic.
- Where it can safely resolve, it does. BRE rules define the exact boundary of what it handles unaided.
- Unclear or sensitive queries go to a human with the full conversation attached.
Impact It Created
- Live agent contact volume down 20 to 35 percent.
- After hours wait times near zero on supported queries.
- Customer satisfaction improved on supported channels after launch.
- Agents freed for complex, high value interactions.
How We Made It Sustained
- New products added as configuration, no rebuild of the conversational engine.
- Service team tunes escalation thresholds as trust grows, with no development cycle.
- AI disclosure and conversation logs built in from day one.