BFSI Technology Solutions — Core Banking Modernisation, AI Risk Scoring & RegTech | Statvion Infotech
BFSI banking core modernisation AI risk scoring RegTech compliance solutions by Statvion Infotech
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BFSI Technology & RegTech Consulting

BFSI

Mainframe modernisation, AI-powered risk scoring, and RegTech compliance automation for banks, NBFCs, and insurers.

800k+
Accounts Migrated
30%
Better Credit Accuracy
0
Service Disruptions
18mo
Full Migration
Strategic Overview

Banking, financial services, and insurance organisations carry the dual burden of legacy technical debt accumulated over decades and an accelerating regulatory compliance agenda that grows more demanding every year. Statvion Infotech delivers core banking modernisation programmes, AI-powered credit risk and fraud scoring platforms, and RegTech compliance automation that enable BFSI institutions to compete with digital-native challengers while maintaining the resilience and regulatory standing their operating licences demand.

Industry Challenges
01

Legacy Core Banking & Mainframe Technical Debt

COBOL-based core banking systems and mainframe infrastructure — some over 30 years old — are expensive to maintain, impossible to scale horizontally, and incompatible with the API-first open banking ecosystem that modern customers demand.

02

AI-Driven Risk Management Expectations

Traditional scorecards and rule-based credit underwriting cannot match the risk differentiation accuracy of ML models trained on alternative data — leaving institutions with either excessive credit risk or unnecessarily conservative approval rates.

03

Regulatory Compliance Cost & Complexity

RBI's CRILC, SARFAESI, PCA framework, IRDAI regulations, SEBI LODR, and international AML/CFT obligations create a compliance reporting burden that manual processes cannot sustainably satisfy — creating both cost pressure and regulatory risk.

Our Solutions

Core Banking Modernisation (Strangler Fig Approach)

Incremental migration from COBOL/mainframe core to cloud-native microservices — using a strangler fig pattern that replaces legacy modules progressively without big-bang cutover risk, with real-time data synchronisation between legacy and new systems during the parallel operation phase.

AI Credit Risk & Fraud Scoring Models

Custom ML models for credit underwriting (incorporating bureau scores, bank statement analytics, GST return analysis, and behavioural signals), fraud detection (transaction anomaly scoring), and collection prioritisation (propensity-to-pay modelling) — deployed via low-latency scoring APIs integrated directly into origination and transaction systems.

RegTech Compliance Automation Platform

Automated regulatory reporting pipelines covering RBI returns (BSR, SLR, CRR, CRILC), IRDAI investment reporting, SEBI disclosures, AML transaction monitoring, and FATCA/CRS reporting — replacing manual Excel-based compilation with scheduled, validated, audit-ready regulatory submissions.

Key Offerings

  • Core Banking System Modernisation (COBOL to Cloud-Native)
  • AI Credit Underwriting & Scorecard Development
  • AML / CFT Transaction Monitoring Platform
  • RegTech Regulatory Reporting Automation (RBI / IRDAI / SEBI)
  • Open Banking API Layer & Account Aggregator Integration
  • Digital Lending Platform (FLDG, Co-Lending, BNPL)
  • Insurance Policy Administration System (PAS) Modernisation
  • Capital Markets Trade Surveillance Platform
  • Fraud Detection & Prevention Engine
  • Customer KYC / CDD Automation & Digital Onboarding

Core Benefits

  • Legacy COBOL core migrated to cloud-native with zero service disruption
  • 30% improvement in credit approval accuracy via ML underwriting models
  • Automated RBI/IRDAI/SEBI reporting eliminating manual compliance preparation
  • AML alert precision improved by 40% reducing false positive investigation load
  • API-first open banking layer enabling fintech partnership integrations in weeks
Client Success Story
"Migrated the legacy COBOL core banking system of a mid-tier private bank to cloud-native microservices using a strangler fig pattern — achieving zero service disruption across 800,000 accounts, deploying AI credit scoring that improved approval accuracy by 30%, and automating all RBI regulatory returns within 18 months."
800k+
Accounts Migrated
30%
Better Credit Accuracy
0
Service Disruptions
18mo
Full Migration
Frequently Asked Questions
Domain-Specific Advisory

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