EWS is an AI-based predictive analytics solution that collects comprehensive borrower information from multiple sources (internal and external to a bank) and analyses it for early identification of incipient stress, based on global compliance standards. EWS helps banks to reduce NPAs (non-performing assets) and improve profitability.

1. EWS – Early Warning Signal
Prepared By : Ravindra Gupta
Date: 22-10-2022 rt360

2. RT360-Early Warning System

3.  Problem :
 Banks In India Are Reeling From The Overhang Of Bad Loans On Their Books Across
Both The Public And Private Sector.
 After A Prolonged Period Of Stress, Which Saw The Gross Non-performing Assets (GNPA)
Of Scheduled Commercial Banks Rising Drastically.
 Situation:
 The Early Detection Of Fraud And The Necessary Corrective Action Are Important To Reduce
The Quantum Of Loss Which The Continuance Of The Fraud May Entail.
 Opportunity :
 The Government Is Separately Looking Into The Issue Of Timelier And Coordinated
Action By The Law Enforcement Agencies.
 A Bank Cannot Afford To Ignore Such EWS But Must Instead Use Them As A Trigger
To Launch A Detailed Investigation Into An Red Flagged Account(RFA).
Situation/Problem/Opportunity:
Alert Generation Process
S.No Alert Generation Process
1
Extract exposure data (Base borrow and
Wam) tables
2 Extract new customers from finacle
3 Share new customers data to saverisk
4 Share data to crif
5 Extarct corebanking data into ews system
6 Extract Saverisk data into ews system
7 Extract crif data into ews system
8
Populate pre staging tables for data
aggregators
9 Populate stagging tables
10 populate RFA tables
11
Populate generated alerts into workflow
tables
12 Release alerts to users

4. Business Process Model (BPM):
Goal- To develop an online model for IDBI Banks for reducing RFA & NPA.
Inputs- Alert ID, Alert Description, EIN, EIN full name, Location, asset details
Outputs – EWS helps banks to reduce NPAs (non-performing assets) and improve
profitability.
Activities- Web application Account login, Information about Alerts, Order ID.
Application database, Order details, driver details.
End value to user- EWS helps banks to reduce NPAs (non-performing assets) and
improve profitability.

5. Objectives :
Purpose Statement (Goals):
 To Deliver An Online Model For IDBI bank to reduce loans taken by multiple assets and RFA and NPA
Project Objectives:
The rt360 – EWS Is manages the entire risk portfolio of banks
and financial institutions.
 It including credit risk, capital allocation, pricing risk, liquidity
risk, model risk and operational risk.
 It Is A Sync View Of Asset And Resource Data.
Gaining A 360° View Of The End-to-end Banking Operations
Would Simplify The Entire Process
 It Will Reducing Costs And Increasing Monthly Volume
Delivery.
Also Offers Complete Visibility Of Data, Assets & Resources,
& Automates Processes To Increase Productivity & Reduce
Costs.
Success Criteria:
Improve Data Records Availability And Accessibility Of Information About
Products.
Solve The Issues, And Take Reviews From Customers
Reduced Fulfilment Time By 75% Through Automation
Net Margin Improvements Of Up To 1% By Dynamic Optimization Of
Emerging Constraints
100% paper work Optimization & 75% Net Margin Improvements
Delivered
 SMA will be 30 days. 60 days, 90 days for fast closure on loans status
High level manager escalation Planning fast submission on alert
status.

6. Implementation and Model :
Methods/Approach:
 The Agile SDLC method will be the best approach.
 The process contains Planning, Requirements
Analysis, Design, Coding, Unit Testing and
Acceptance Testing
 Designed by bankers, risk practitioners and
technology specialists with a Business-First,
Technology-Next approach,rt360 empowers banks
and financial institutions to focus on their credit
growth and profitability.
 FM engineer can be the best option to consult
 Training/User Manual will be provided to each user
and employee for easy understanding of project.

7. Resources & Risks:
Resources:
People – Project team members from client community and BCT.
Time – implementation within 9 months.
Budget – hardware, software, training and services not to exceed Rs.20,00,000.00
Other – third party software evaluation, site visits, Dataquest reports – not to exceed Rs. 5,00,000
Risks and Dependencies:
Current solution in place for over 2.5+ years and it is intuitive to current users.
Cost justification in ease of use, quality of information, speed of accessibility, ease of support and maintenance is
difficult to quantify in a way management can see improvements in utilization of system investment

8. Prototype
Data Sources
Workflow Management
Reporting & Dashboards
Rule Engine and Processor
Data Ingestion
Alerts Thresholds
Customer Profiling
Case Manager
Follow-up
EWS Scoring
Rule Engine
EWS
Staging
Staging Area
External Source Internal Sources
Unstructured
Reports
Data
Aggregator
CBS, Rating
System,
LOS/LMS etc.
Corporate
MSME
Early Warning Signals
Extraction
module

9. Thank You