AI for All

AI for All represents the Mifos strategic initiative and forward-looking roadmap for data science effort around artificial intelligence and machine learning for use cases powered by solutions built on Mifos and Fineract.

In GSOC 2018-20, three use cases that were developed using AI/ML - Credit Scoring, Chatbot and PPI.

Join our bi-weekly AI and ML working group at https://discourse.mifos.org/g/AI-ML to track progress or pick out a task from those described in this section.

You can also view our presentation at the 2020 ApacheCon at:

 

Use Cases

Use Case Theme

Explanation

Type

Use Case Theme

Explanation

Type

Cash flow prediction

Predict future/present value of money and company’s inflows/ outflows for projected income/expenses over a period of time

Back office

Credit scoring

Determine chances a borrower will fail to make a payment on a loan and identity credit risk, cost of debt, interest rate, credit score

Back office

Cost of equity, risk

Calculate the return potential stockholders expect before investing in a company

Back office

Portfolio management

Which among a given set of investment decisions are most beneficial for a company by estimating opportunity cost, net present value, internal rate of return, payback period

Back office

Enterprise value

Calculate a firm's market valuation and liquidation value

Back office

Spend analysis

Spend management by tracking spending patterns of individuals, with saving suggestions and financial advice for ROI

Back office

Fraud detection

Audit transactions to identify fraud risk in credit cart application process, monitor suspicious account behavior, false positives like money laundering

Back office

Security

Analyse large amounts of data to identify risk patterns and improve security

Back office

Algorithm trading

Tracking market changes and fluctations in stock prices, high frequency trading in hedge funds / investment firms for trade decisions and manage stock volatility

Back office

Virtual Assistant & Process Automation

Automate manual and repetitive processes, approval/rejection, paperwork with chatbots, call center automation for cost reduction and ops efficiency

Front end

Product recommendation & Campaign Management

Predict customers with propensity to churn, their RFM score & lifetime value and retarget / win them back with personalised offers, insurance plans, lending etc.

Back office

Customer Experience based on Customer persona

Track customer behavior and usage across apps / web / social media activity and improve product experience and onboarding flow

Front end

NPA Management

Detect, measure, predict, and anticipate, among other things, market volatility, liquidity risks, financial stress, housing prices, and unemployment to reduce non-performing assets

Back office

Lending & Loan Management

Processing, disbursement and fulfilment of loans across borrowers and lenders E.g Home Loan Takeover, Home Loan Top-up, Loan against property

Back office

Loan Underwriting

Lender determining if a borrower's loan application is an acceptable risk. Underwriters assess the borrower's ability to repay the loan based on an analysis of their credit, capacity, and collateral.

Back office

Early warning system

Early Warning provides info to financial institutions about consumers' banking activity and history to help them detect fraud and assess risk

Back office

Working Capital Enhancement

Maximise (Assets - Liabilities)

Back office

Language Translation

Banks and financial institutions must translate large amounts of business documents from English into Spanish, Chinese, Portuguese, or other languages with quality & speed as well as consistent branding & legality in order to meet international customer expectations.

Front end

Adaptive Authentication

Adaptive authentication mechanisms evaluate the risks surrounding a particular user login attempt and dynamically steps up the authentication or prevents the login, based on suspicious activity.

Front end

Social Media Engagement

Automated Responses to Social Media posts and queries by prospects / clients / customers

Front end

Collateral document management

Scanning & identification of what can be committed as collateral for a transaction to be performed

Back office

Money Management

AI-driven Reconciliation, EWS, AML, Income leakage, Parking Accounts, Footfall Model, ATM Chargeback, IP infringement

Back office

Payment channel for making / accepting payments

Based on date, time, nature of transaction

Front end

 

References

White Papers on Artificial Intelligence in Banks
Artificial Intelligence in Banks
Redefine Banking with Artificial Intelligence
Artificial Intelligence Applications in Financial Services, Marsh & McLennan Companies
Artificial Intelligence & Financial Services by Apis Partners

Links
https://www.idrbt.ac.in//assets/publications/Best Practices/2020/AI_2020.pdf
https://www.mindtitan.com/case/artificial-intelligence-in-finance-and-banking/
https://www.paymentsjournal.com/the-18-top-use-cases-of-artificial-intelligence-in-banks/
https://www.fintechnews.org/ai-and-machine-learning-in-finance-use-cases-in-banking-insurance-investment-and-cx/
https://builtin.com/artificial-intelligence/ai-finance-banking-applications-companies
https://marutitech.com/ai-and-ml-in-finance/
https://towardsdatascience.com/ai-use-cases-for-finance-and-banking-716b43082c5b
https://www.wipro.com/en-IN/business-process/why-banks-need-artificial-intelligence/
https://www.datasciencecentral.com/profiles/blogs/19-ai-amp-iot-use-cases-in-banking-industry
https://www.mckinsey.com/industries/financial-services/our-insights/ai-bank-of-the-future-can-banks-meet-the-ai-challenge#