“Alert-O-Monitor” is a one-stop solution for managing end-to-end flow of Early Warning Signals in Banks to prevent slippages of accounts into NPA (Non-Performing Asset) category. It involves “Alert Generation”, “Alert Monitoring”, “Alert Resolution” as well as “Alert Prediction” giving a complete 360-degree comprehensive solution which none of the Banks has implemented till now.
Business Outcomes :
1) Reduction in "Provisioning for Credit Losses" leading to increase in Profitability of Banks
2) Decrease in Impairment of Assets leading to "Better Asset Quality"
3) Decrease in instances of Frauds in Banks
4) Improved Credit Decision-Making and Underwriting process
5) Faster TAT (Turn Around Time) for Loan Recovery
6) Accountability and Transparency within Bank to ensure timely identification and closure of Alerts
The Real Hidden Power lies in the BUSINESS VALUE that this Usecase can generate which aims to increase Profitability of Banks to the tune of $150-200 mn every year.
Key Challenges of Chief Risk Officer (CRO) in Banks :
Banks all across the globe are facing challenges in terms of increase in “Provisioning for Credit Losses” which is causing a direct hit at their profitability.
The REAL PROBLEM lies in lack of prompt Recovery Action which starts only when the account is already overdue for more than 60 days i.e when it reaches “SMA-2 Stage”.
The moment this overdue period touches 90 days, the account becomes NPA i.e Non-Performing Asset which attracts provisioning of 15% on Secured portion and 25% on Unsecured portion that can eventually become 100% once it moves to Loss Asset category.
Unfortunately, there is no concrete solution in Banks to prevent accounts from slipping into NPA category and this is where our solution “Alert-O-Monitor” plays a major role in pro-actively generating and managing alerts at initial stages itself even when the account is Standard i.e Regular.
It aims to answer the following questions :
1) Can a Bank's CRO visualize end-to-end flow of Alerts being generated ?
2) Can a robust Business Rule Engine be created to generate alerts based on Loan Agreement Covenants ?
3) Can alerts be created for deviation in financial ratios like Debt-to-Equity, DSCR, Quick Ratio etc. ?
4) Can the alerts be assigned with Maker/Checker concept ?
5) Can External News Alerts be generated and monitored ?
6) Can a Risk Officer recommend effective Risk Mitigation Strategy for Closure of Alerts ?
7) Can a Risk Officer check how many High-Impact Alerts (with high limit exposure) are still open for compliance ?
8) Can notifications be sent to relevant stakeholders ?
9) Can a Risk Officer understand the Sentiment of Customer’s Voice Calls for timely & effective Recovery action ?
10) Can we predict Probability of Recovery to optimize Cost ?
What is the USP of "Alert-O-Monitor" ?
Its USP is that it has robust Business Rule Engine of over 73+ Triggers and comes with an added layer of Advanced Analytics capabilities like GenAI based LLM Chatbot "Intell-O-GENie", External News Crawling, Risk Mitigation Recommendation, Call Sentiment Analysis and AI-ML driven Probability of Recovery for each account so that it results in Cost Optimization & overall increase in profitability due to reduction in provisioning for credit losses.
To begin with, we categorized various alerts into 5 buckets –
Financial Triggers
Operational Triggers
Payment-related Triggers
Internal management Triggers
External News Triggers
On top of these triggers, we created a Robust “Business Rule Engine” and further classified them into “High Impact”, “Medium Impact” and “Low Impact” alerts. Apart from a robust Business Rule Engine, we have added layer of “Advanced Analytics” where are focusing on various AI-ML capabilities.
GenAI based LLM Chatbot – “Intell-O-GENie” to capture External News Triggers along with “News Crawling feature” to extract news feeds from websites like BBC News.
“Voice Analytics” where we are capturing overall sentiment of a customer based on his conversation with Bank’s relationship Manager. We are using features like Speech to Text conversion, Speaker Diarisation, Spell Correction, Keyword Spotting and Text Summarization.
A Machine Learning Model to calculate “Probability of Recovery” for each customer.
“Risk Mitigation Recommendation Engine” to assist Field Officers to take the right corrective action to close the alerts.
We are using following features of Microsoft Fabric and Artificial Intelligence/GenAI :
1) Data Modelling – For Creating Data Models on lakehouse for Power BI report
2) Data Lakehouse – Data Storage
3) Power BI - For illustration of 4 Views - Aggregate, Customer Level, Voice Analytics and External News Triggers
4) Azure AI Search – Creation of Knowledge Base for RAG implementation, chunking and creation of Vector Database.
5) Azure Open AI – Retrieving the data from Azure and making interpretations/adding the Intelligence layer
6) Azure Webapp : User Front End Screens
7) Azure Blob Storage – for storing multiple PDF files
Project name
Alert-O-Monitor
Description
“Alert-O-Monitor” is a one-stop solution for managing end-to-end flow of Early Warning Signals in Banks to prevent slippages of accounts into NPA (Non-Performing Asset) category. It involves “Alert Generation”, “Alert Monitoring”, “Alert Resolution” as well as “Alert Prediction” giving a complete 360-degree comprehensive solution which none of the Banks has implemented till now.
Business Outcomes :
1) Reduction in "Provisioning for Credit Losses" leading to increase in Profitability of Banks 2) Decrease in Impairment of Assets leading to "Better Asset Quality" 3) Decrease in instances of Frauds in Banks 4) Improved Credit Decision-Making and Underwriting process 5) Faster TAT (Turn Around Time) for Loan Recovery 6) Accountability and Transparency within Bank to ensure timely identification and closure of Alerts
The Real Hidden Power lies in the BUSINESS VALUE that this Usecase can generate which aims to increase Profitability of Banks to the tune of $150-200 mn every year.
Key Challenges of Chief Risk Officer (CRO) in Banks :
It aims to answer the following questions :
1) Can a Bank's CRO visualize end-to-end flow of Alerts being generated ? 2) Can a robust Business Rule Engine be created to generate alerts based on Loan Agreement Covenants ? 3) Can alerts be created for deviation in financial ratios like Debt-to-Equity, DSCR, Quick Ratio etc. ? 4) Can the alerts be assigned with Maker/Checker concept ? 5) Can External News Alerts be generated and monitored ? 6) Can a Risk Officer recommend effective Risk Mitigation Strategy for Closure of Alerts ? 7) Can a Risk Officer check how many High-Impact Alerts (with high limit exposure) are still open for compliance ? 8) Can notifications be sent to relevant stakeholders ? 9) Can a Risk Officer understand the Sentiment of Customer’s Voice Calls for timely & effective Recovery action ? 10) Can we predict Probability of Recovery to optimize Cost ?
What is the USP of "Alert-O-Monitor" ?
Its USP is that it has robust Business Rule Engine of over 73+ Triggers and comes with an added layer of Advanced Analytics capabilities like GenAI based LLM Chatbot "Intell-O-GENie", External News Crawling, Risk Mitigation Recommendation, Call Sentiment Analysis and AI-ML driven Probability of Recovery for each account so that it results in Cost Optimization & overall increase in profitability due to reduction in provisioning for credit losses.
To begin with, we categorized various alerts into 5 buckets –
On top of these triggers, we created a Robust “Business Rule Engine” and further classified them into “High Impact”, “Medium Impact” and “Low Impact” alerts. Apart from a robust Business Rule Engine, we have added layer of “Advanced Analytics” where are focusing on various AI-ML capabilities.
We are using following features of Microsoft Fabric and Artificial Intelligence/GenAI :
1) Data Modelling – For Creating Data Models on lakehouse for Power BI report 2) Data Lakehouse – Data Storage 3) Power BI - For illustration of 4 Views - Aggregate, Customer Level, Voice Analytics and External News Triggers 4) Azure AI Search – Creation of Knowledge Base for RAG implementation, chunking and creation of Vector Database. 5) Azure Open AI – Retrieving the data from Azure and making interpretations/adding the Intelligence layer 6) Azure Webapp : User Front End Screens 7) Azure Blob Storage – for storing multiple PDF files
Project Repository URL
https://github.com/shaleen410/Alert-O-Monitor
Project video
https://youtu.be/f0v1lh8aKOA
Team members
shaleen410,cvlmonica,sunspai1