Data System

DANILO F. BASSI, PhD

*** ********* **, ******, ** 19312 Mobile: +1-215-***-**** ******.*****@*****.***

Senior Consultant in Credit Risk Analytics and Management

SUMMARY OF QUALIFICATIONS

Expert in Credit Risk Modeling with over 20 years of experience creating and analyzing mathematical and

probabilistic credit risk models, and designing systematic methods for optimal decision-making.

Over 20 years of experience in development of models from facts, by the application of Knowledge

Discovery from Data (KDD) paradigm: data-mart design, data mining, selection and synthesis of variables,

functional modeling based on machine learning and statistical approaches.

Depth understanding of credit business and development of solutions for all its stages: modeling and

systematic decision-making in credit marketing, screening, behavior, collection and debt recuperation.

Strong experience in innovation, research, leadership/team building and project management.

Good interpersonal and communication skills, proficient in three languages (English, Spanish & French)

PROFESSIONAL EXPERIENCE

04/1994-Present: Senior Consultant in Credit Risk Modeling. Worked on multiple projects and studies

on quantitative credit risk modeling involving machine learning paradigm, probabilities, data-mining and

decision support systems. Specific projects and studies in credit risk modeling included:

• “Recommendations for building better models that comply with Basel II rules”, for Banking

Association (2012-13): advise given to help banks improve their models, resulting in more precise

risk assessment and therefore improvement on capitalization efficiencies and overall bank risk.

• “Development of a reference credit-risk scoring system” for Ecuador’s Credit Bureaus Inspection

(2008-09): this system is used as a reference tool to audit private Credit Bureaus credit-scoring

models, and assess its compliance. The main challenges were to build a very generic model, using

only publicly available information, and to deal with massive databases (with over 50GB).

• “Development of new applicant’s scoring system in order to assess initial risks”, for Chilectra (2007-

08). Chilectra S.A., Chilean main electric utility (over 2M clients) requested this model in order to

enter credit card business, using, its massive electric client data-base as main dynamic factor.

• “Senior advising in development of generic risk credit scoring”, for SINACOFI (2005-06): I defined

the main attributes of this new scoring model, and then helped building and its supervision.

• “Senior advising and development of neural networks applications” for BancoEstado (2005): how

to build sound models of credit risk probability, based on real, noisy, information.

• “Selective collection scoring system”, for Procobro (2001-02): was used to contain collection costs,

and increase its returns, by better targeting at more profitable lender profiles.

• “Credit card holder segmentation” and “Selective collection scoring system” (1997-2002), for

Almacenes Paris. The client, a large department store (with over 1M cardholders), improved its

operations by optimizing collection efforts and having better mapping of lender segments.

• “Computing Support system for managing micro business credits” for Fundacion OCAC (1999-

2002): the client streamlined its operations, targeted at small business loans, including a specific

credit scoring.

• “Client segmentation and analysis”, for Banco del Desarrollo, Microempresas (1996-97): better

client segmentation, based on actual data, allowed increased efficiencies at banking operations.

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“System for Client segmentation and analysis”, “Scoring system for selective collection” and “

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“Scoring system for charged-off debt recuperation” for Financiera Conosur (1996-2001): the

projects were systematic credit management tools, necessary for this company that offered

personal loans to a large base of clients (over 1M accounts), improving dramatically its bottom line.

“System for micro business credit client evaluation” for SOINTRAL and FINAM (1995): the

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introduction of this system produced a significant improvement in the business, making it feasible

to attain a large number of lenders, while increasing profitability.

06/2011-Present: Associate Researcher at the Center for Business Analytics, Villanova University,

Villanova, PA. Working in Business Analytics research, credit risk analysis and modeling: analysis of

massive credit database to find hidden patterns that explain or predict credit default.

09/1995-12/2010: Full Professor & Associate Professor at Universidad de Santiago de Chile, Computing

Engineering Department, Santiago, Chile. Doing research & development of different aspects that can

improve credit risk modeling: in Probabilistic model estimation, how to obtain fair and useful model, when

data distribution is problematic, in Anomaly detectors, an important feature in credit modeling (fraud

detection), in Improved time-series modeling, necessary to model behavior of on-going credits, Clustering

analysis and unsupervised learning, models that emerge automatically from data, facilitating segmentation

and labeling.

07/1996-04/2003: President, CEO & Founder of Tecnologías y Sistemas Rednova S.A. Santiago, Chile.

By founding Rednova I put in action my academic developments in risk modeling into a profitable business.

The company delivered credit modeling and decision support solutions and advice, for entities such as

banking, retail and insurance. RedNova was technological entity based its solutions in proprietary and

advanced technologies and methodologies:

• NovAccion Data Mining System, software for performing automatic analysis and modeling, using

data mining techniques, advanced neural networks models and rule synthesis.

• Remote function evaluation system (ERFUS), software/hardware generic platform for real time

computation of risk models (neural networks, decision trees and induced rules).

01/1991-08/1995: Assistant Professor, Universidad de Chile, Department of Industrial Engineering,

Santiago, Chile. Pioneering work in financial quantitative modeling: I introduced the use of Machine

Learning techniques and methods to create risk models that emerged from actual data.

EDUCATION

Doctor of Philosophy (PhD) in Computer Science, University of Southern California, Los Angeles, CA

Master of Science in Electrical Engineering (MSEE), Universidad de Chile, Santiago Chile.

Bachelor of Science in Electrical Engineering (BSEE), Universidad de Chile, Santiago Chile.

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