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Banking & Finance

INDUSTRY

Banking & Finance

Securing Financial Infrastructure with Zero Compromise

BFSI organizations demand the highest levels of security and compliance. Our BFSI-specialized team delivers PCI-DSS, ISO 27001, and RBI-compliant security assessments alongside AI-driven fraud detection and compliance automation.…

RBI Cyber Security Framework SEBI LODR PCI-DSS v4.0 IRDAI Cybersecurity Guidelines FATF AML/CFT ISO 27001
₹8.4Cr
Fraud Prevented/Year
99.99%
CBS Uptime
18 sec
Fraud Review TAT (was 4 hrs)
60%
Compliance Cost Reduction
Industry Pain Points

Challenges We Solve in Banking & Finance

Escalating UPI & Digital Fraud

Real-time payment volumes mean fraud losses occur in milliseconds. Manual review queues average 4+ hours, leading to customer friction and regulatory scrutiny.

Regulatory Reporting Burden

RBI, SEBI, and IRDAI mandates require multiple concurrent reporting streams. Manual reconciliation across core and ancillary systems consumes 40+ analyst hours per quarter.

Legacy Core Banking Fragility

Ageing CBS infrastructure with limited API exposure makes integration of modern AI tools complex. Every unplanned outage triggers NPA classification and customer trust erosion.

What We Deliver

Use Cases We've Deployed in Banking & Finance

Specific capabilities we've built and run for Banking & Finance organisations — not PowerPoint features.

Real-Time Fraud Detection

ML models scoring every transaction in <200ms — detecting account takeover, card testing, and CNP fraud across UPI, NEFT, RTGS, and card networks.

RBI Compliance Automation

Automated regulatory reporting for RBI circulars, SEBI mandates, and IRDAI guidelines — reducing compliance team effort by 60%.

Core Banking Network Ops

AI NOC maintaining five-nines uptime for CBS, payment switches, and data centre interconnects with autonomous incident remediation.

ATM / PoS Security Monitoring

Behavioural analytics detecting card skimmers, jackpotting attempts, and logical ATM attacks in real time before cash is dispensed.

Digital Lending Automation

Straight-through processing for loan origination, document verification, and credit decisioning — cutting TAT from days to minutes.

AML / CFT RegTech

Automated CRILC, XBRL, and AML/CFT reporting with full audit trails and FATF-aligned transaction monitoring.

Client Success Story

Real Results from a Real Engagement

Regional Private Sector Bank (₹28,000Cr AUM, 1.2M digital customers)

THE CHALLENGE

Rising UPI fraud causing ₹8Cr+ in annual losses. Manual fraud review queues averaging 4 hours were causing customer churn. RBI flagged the bank for inadequate AML controls in a supervisory letter.

OUR SOLUTION

Deployed real-time ML fraud scoring integrated with the CBS and UPI switch. Autonomous case routing prioritises high-risk transactions for analyst review. RBI-ready dashboards generate submission-ready CRILC reports automatically.

RESULTS ACHIEVED
  • ₹8.4Cr fraud prevented in the first 12 months of operation
  • Fraud review TAT reduced from 4 hours to 18 seconds
  • 99.99% CBS uptime maintained through the integration — zero core banking downtime
₹8.4Cr fraud prevented annually

Our Services for Banking & Finance

PCI-DSS compliance audits & VAPT
ISO 27001 implementation
AI fraud detection integration
Core banking security assessment
API security testing (open banking)
SOC operations for BFSI

Typical Clients

Banks & NBFCs Insurance Companies FinTech Startups Payment Gateways
₹8.4Cr

fraud prevented annually

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FAQ

Banking & Finance — Common Questions

Yes. We use non-intrusive API hooks into your payment switch with sub-100ms latency overhead. We support Finacle, BaNCS, Temenos T24, and Oracle FLEXCUBE with pre-built connectors.

All ML models used in credit decisioning are explainable (XAI) by design. We produce decision audit trails with feature importance scores that satisfy RBI Model Risk Management guidelines.

For a mid-sized bank with a clean API layer, we typically go live in 8–10 weeks: 2 weeks data discovery, 3 weeks model training on your historical transaction data, 3 weeks parallel-run validation, 2 weeks go-live.