Right after presenting his prediction models at G20 Summit, CEO of US Based Fintech Company choose to share his knowledge with students at Institute of Banking & Finance, New Delhi. A veteran banker Patrick Reily, Co Founded Verde International in Greater Atlanta to remove the bias in loan decisions through behavioural and financial modelling. Patrick has an experience of 25 years in financial services, underwriting, credit risk, predictive modelling, cross selling and fraud prevention. Since 2006 his company has been delivering objective analytics and decision making resources to financial institutions and companies.
The key theme of the session was set by his opening remarks when he said that, “Bankers have the ability to change and uplift the country”. His session delved on technical and philosophical aspects of how bankers can lend profitably and yet ensure a strong social impact on the community. He shared many International examples from developing and developed economies to enumerate his points. The key learning from his session were,
- Every loan relationship creates an ecosystem with different stakeholders and externalities which could impact the community positively or adversely.
- In manual loan underwriting factors such as income, qualifications, occupation, history of repayment, etc are given consideration.
- Many other neglected factors, if taken into consideration can improve the ability to make better loan offers.
- An ideal loan decision is a result of synchronising four key factors – Customer Story, Environmental Context, Pricing Functions and Loan Structure.
- The repayment terms in a loan structure have interdependence with customer’s story such as occupation, seasonality of income and expenditure. So with convenient repayment terms defaults on small ticket loans can be brought down.
- More than a billion data pointers are available that can help in creating mathematical models to create a context at economy or industry level.
- These equations when fed in a decision support system can help in calculating Probability of Default (PD) and Loss Given Default (LGD) for every individual Loan Decision.
- Automated decision support systems can increase the number of loans given and optimize risk distribution over a larger customer base.
- The system if automated can take small loan decisions automatically with no human intervention.
- A robust financial system increases the profitability of share holders and capital providers while serving the objectives of community development.
The session concluded with the vote of thanks and presentation of memento by Prof. Amit Goyal, Director, Institute of Banking and Finance. Patrick was enthralled with the enthusiasm of students and shared kind words of wisdom to encourage them.