Credit default scoring debt portfolio

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www.valiancesolutions.com © 2014 Valiance Solutions Credit Default Scoring: Asset Portfolio Analytics Consulting Technology Consulting Business Intelligence

description

Risk assessment of existing asset asset portfolio for eagerly detecting high risks and performing targeted interventions.

Transcript of Credit default scoring debt portfolio

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Credit Default Scoring: Asset Portfolio

Analytics Consulting

Technology Consulting

Business Intelligence

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What is Default Scoring?

Default scoring means applying a statistical model to assign a risk score to an existing credit account. On a higher level, default scoring also means the process of developing such a statistical model from historical data.

Need for Credit Scoring

Banks aggressively monitor their asset portfolio for future risk of defaults. This is useful for early detection of high risk and enables the organization to perform targeted interventions. There are number of ways Banks do this, some banks adopt highly sophisticated and automated approach of default scores resulting in more accurate predictions whereas for some it is still more of a manual process requiring human intervention. Default Scoring has also evolved with firms experimenting with various new techniques like machine learning, support vector machine etc.

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Default Scoring Solution

Framework to eagerly detect high risk accounts and perform targeted interventions.

Existing Customers

Potential Defaults in Near Term

Targeted Intervention/

Adequate Provisioning

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Existing Loans Regression Modeling

Borrower Details Fed into the

System

The algorithm developed will return default

score

Feedback Process Response tracking

Feed

back

Loo

p Implementation Framework

1 2 3 4

Low Risk

Medium Risk

High Risk (Pro-Active

Intervention)

Feedback is used to improve the model performance over period of time.

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Modeling Phases

Data Mining

Hypothesis building Data cleansing

Validation of Model on test data

Host the algorithm on the client’s system Cross-validate the

scores generated by the system

Understanding Default patterns

Profiling patterns Algorithm for fraud prediction

Roll-out the algorithm on the live system

Continuous monitoring of through the door

population for any changes in patterns

Strategy roll-out and

testing

Implementation of framework

Default Likelihood

Model

Iteration & Validation

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Determining Cut Off Score

Point at which separation between cumulative percentage of good and bad customers is maximum determines the cut off score for distinction between high risk & low risk customers.

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Sample Output

Deciles are order by default scores in decreasing order.

Nearly 70% of customers who are likely to turn into bad debt in next 6 months found in 40% of total customer base.

Decile: 10% of customers

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Default Score: Benefits Over Business Intelligence

Predictive in nature rather than reactive. Gives early indicator of portfolio turning into bad debt. Detects hidden patterns in default scenarios and interaction amongst different attributes

that can’t be modeled in BI tool. Identification of significant factors that affect portfolio default. Provides objective assessment of risk in hands of team. Complements business judgment

in a way making it more effective. Solution can be integrated with IT systems to provide alerts to Risk department for

potential bad debt indicators. Saves time and money involved in verification of accounts. Solution can be further extended to build collection scores for predicting amount that can

be recovered in case of potential bad debt scenario.

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About Us

Valiance Solutions is an analytics consulting firm providing business solutions to clients globally using cutting edge technologies.

Valiance started it’s journey in 2011 with two employees and since then it has grown to 15 plus team. It has served as consulting partner in CRM space for retail firms, US based market research firm and firms like Reliance and Easy Cabs in India.

Leadership team comes from IIT’s and IIM’s with 24 years of combined experience in delivering IT and analytics solutions to Investment Banks globally and BFSI companies in India.

Advisory team comprises of seasoned industry executives who have serve as thought leaders with global firms.

Head Quarters: Delhi, India Strong Team Global Clientele

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Executive Team

Vikas Kamra (Chief Executive Officer) B.Tech, IIT Delhi

Ankit Goel (Chief Technology Officer) B.Tech, IIT Kharagpur

6 years of strong experience building and delivering technology solutions globally. Heads overall strategy, business development and marketing for Valiance. Takes keen interest in Big data technology and its application for commercial business solutions collaborating with clients on Data Analytics strategy. Consulted with Fortune 100 firms like Bank of America, Merrill Lynch, Jefferies out of onsite locations.

9 years of strong experience in software development, application architecture and scalable applications development. Served in roles of Technical Architect, Technology Consultant for Fortune 100 investment banks. Heads product development, engineering & delivery for clients.

5 years of analytical consulting experience working with Fortune 100 Financial companies across EMEA, US and Indian Subcontinent region. Worked on several advanced level analytics initiatives with Life Insurance companies, Mutual funds, Credit Card Companies, NBFC’s in India in Credit Risk, Marketing and Customer Analytics He is responsible for design and development of analytics framework for Banking and Insurance clients globally for Valiance

Shailendra (Chief Analytics Officer) DMET MERI

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Advisory Team

Lokesh Gupta (General Partner, Spice Investment Fund) B.Tech, IIT Delhi MBA- IIM Ahmedabad

Ajay Piwhal (Head BI & Analytics, Airtel) B.Tech, IIT Delhi MBA- IIM Ahmedabad

Lokesh is working as General Partner in Spice New Investment fund. In this current role, Lokesh is responsible for identifying startup companies in Education domain and help them transform their ideas into big enterprises. Prior to that Lokesh was heading Spice Labs as its CEO. Ajay spearheads analytics division at Bharti Airtel since 2 years with responsibility for customer insights, Cross Sell up sell and other key analytics initiatives. Prior to this he was responsible creating analytics competency and successfully applied analytics in direct marketing initiatives and multiple business functions across the organization with Max Life Insurance. Before Max Life Insurance, he has worked with firms like GE in setting up analytics team for its Insurance clients and IBM and PWC on similar initiatives.

Dinesh has 12 years of strong experience in data driven analytical consulting, modeling and statistical analysis. He has held senior positions in companies like Cequity, ICICI, GE Capital, Inductis at senior positions in analytics capacity. Throughout his career has provided analytical leadership, tactical solutions and measurable delivery of financial opportunities through advanced data mining/predictive analytics solutions for various business verticals like Retail, Insurance, FMCG, Automobile, Travel & Hospitality, Telecom, Mutual Funds etc.

Dinesh PHD, IIT Delhi

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What do we bring Onboard?

• Learning's from industry on data collection, data analysis and MIS. We have interacted with 14 plus Banking & Insurance firms on their business problems, met with stake holders and presented solution frameworks.

• Team with strong desire to excel and succeed not just for us but for our clients. Advisory panel consists on individuals who have spearheaded analytics in India.

• Successful implementation of decision frameworks in areas of Claim fraud, Customer Retention and Marketing.

• Knowledge of setting up consistent and right data collection process and framework for future Analytics & BI initiatives.

• Strategic partnership vision to establish Analytics as a key competitive advantage in Industry for our clients.

Domain Knowledge Industry Exposure Technical Expertise

Result Focus Passionate Team