The profile is calculated on the basis of the information available at the moment of the decision. Experian Decision Analytics has been at the forefront of the credit scoring industry for over 20 years, gaining experience from statistical models built in many countries across several lending situations. Our company recognises the fact that the credit scorecard, normally focused on risk, is a key part in the complete business solution but places emphasis on the wider issues of marketing and customer profitability. Based on these issues, Experian Decision Analytics developed a synergy between different operational areas, streamlining business processes and allowing strategies to be designed with the aim to maximise the potential of each customer.

During the first stage Application Scoring is used, while during the management phase Behavioural Scoring is applied. In this last case, the score of the client can be calculated multiple times, observing in each occasion the most recent trends of behaviour.

Application Scoring estimates, at the moment of the request, the level of risk associated with each application before it is effectively approved. For this type of scoring information is required, such as: personal data (for example: age, marital status and profession in case of individuals, and time in business in case of companies that request financing), income data (for example: duration and amount of the requested financing), profit data (for example: data relative to the declaration of the individuals’ rent or the last balance presented by the company that requests financing), and external information (such as information contained in private or public Credit Bureaux). Furthermore, information regarding behaviour is essential in order to control each client’s capacity of reimbursement (Default/No Default).

Behavioural Scoring uses information available after the acceptance of the financing request and makes it possible to evaluate the behaviour of the customer that has been granted a credit. The Behavioural Scoring is highly discriminatory, as it is based on an information set of characters more predictive than the data of exclusively personal nature that is used in acceptance scoring.

The advantages of a scoring model are clear: greater control over portfolio quantity, minimisation of exposure to risk, profitability enhancement, reduction of costs and losses, customer service and communication improvement.

The first step is to build a predictive model using an optimization algorithm that will select the best variables and display the final model with the possible highest power of discrimination. The result of this procedure will be represented by a scorecard. By definition, the higher the final score is, the lower the probability of default will be and vice versa. The more common definition of a "bad" client in default or in a personal credit is generally associated with a maximum acceptable number of days not paid. For example, an individual who has delayed more than three consecutive monthly payments could be considered a default client. Up to here we could think that the Probability of Default (PD) could be a sufficient tool for an improvement of the global profit. The algorithm of scoring would differentiate in a simple way between applicants with a high probability of very poor margins (bad clients) and applicants with very good expectations. Unfortunately, the same criterion is not considered effective for long-term credits or greater amounts. In these cases, a second parameter that characterizes each loan receives importance: the Loss Given Default (LGD), which shows the global final loss of an account like a percentage of pending loans, in case this account is in default (effective loss), and considers many variables like: interest of default, fines by delays, commissions and all the costs associated with the recovery processes.

When combining both models (PD and LGD) a more complete calculation of the risk associated to the financial requests can be formed. With the traditional scoring systems, the clients are classified according to their probability of default, beginning by those with the lowest estimation (higher PD) until arriving at those with the highest estimation (lower PD). An LGD model would add a new dimension to this evaluation by the similar classification of the clients according to the type of loss expected in case of default. Therefore the advantage is clear: The LGD model increases the capacity to differentiate between potentially good clients and bad clients in a considerable way.

The traditional scorecards of probability of default (PD) are excellent tools for the effective evaluation of risk and consequently for the maximisation of profit, especially for associated credit products with medium and small amounts. The positive effect of LGD estimations are more evident for higher amounts and/or longer periods. The LGD assessment does not replace the traditional estimation of PD, but is a complement with the purpose to optimise the profit.

A monitoring system of scoring is an instrument of great value, essential for managing the clients’ portfolio objectively and efficiently in a financial institution during all the customer relationship phases, and handling more evolved and sophisticated risk solutions. Experian Decision Analytics always works in collaboration with the customers in order to ensure that each scorecard developed, whether working in isolation or not, meets their precise business objectives and specific needs.

Due to the rising interest in analytical overview on credit scoring methodologies and its practical applications, the Spanish Magazine “Estrategia Financiera” asked Experian Decision Analytics to provide an in-depth paper focused on credit scoring. The documentation prepared by Experian Decision Analytics was circulated in two seperate issues. The second part of this article will be presented in a forthcoming edition of our newsletter.

Experian plc announced that it has signed contracts to install its anti-money laundering and regulatory compliance software with two major banks in Latin America - Banca Afirme in Monterrey, Mexico and Banco del Pichincha C.A., a leading bank in Ecuador.

With the installation of Experian’s ASSIST//ck software, developed by its specialist anti-money laundering division based in Miami, Florida, these two banks will automate the detection, investigation and reporting of money laundering activities and streamline the processes and policies required for compliance with international and U.S. regulations. Banca Afirme is one of the fastest-growing financial services providers in Mexico, and Banco del Pichincha C.A. is the largest bank in Ecuador with 218 branches in 80 cities.

Experian provides a singular solution to meet the challenge of anti-money laundering and suspicious activity compliance. With installations in 35 countries worldwide, Experian’s anti–money laundering solutions provide a full range of global products and services for identity verification, fraud prevention, money laundering detection and compliance with government regulations, including the USA PATRIOT Act. These powerful solutions, combined with the industry’s largest proprietary consumer information databases, enable Experian to offer a complete suite of compliance solutions, including a customer verification program, negative list screening, transaction monitoring and reporting of suspicious activities.

“Money launderers don’t respect national boundaries,” added Gary Wood, Managing Director of Experian’s Fraud Business in the UK. “Money laundering is a global business and requires global solutions to combat it. Experian has a strong international capability, providing comprehensive fraud and compliance solutions globally across many industries and is making a major contribution in the fight against this insidious and corrupting crime that threatens the way of life of every one of us. We look forward to working with Banca Afirme and Banco del Pichincha to enhance their anti-money laundering programs.”

The Group includes private sector mortgage finance practitioners and policy makers from South Eastern Europe who help define pivotal steps and a regional role in the improvement of the mortgage finance sectors of SEE nations. It is part of a project, financed by USAID, and coordinated by the Urban Institute (Washington) and Institute for Market Economics (Sofia).

The participants discussed the legal and administrative support for mortgage lending in the region - Credit Bureaux, timely foreclosure, valuation skills, insurance products, and regulatory framework.

Among the main topics of this meeting were:

• Regulation and Supervision of Mortgage Finance in Bulgaria and Romania

• EBRD Minimum Standards Model

• Mortgages and Credit Scoring

• Real Estate Price Indices in Poland & Bulgaria

• Mortgage Guarantee Insurance in Emerging Markets

• Mortgage Life, Property, and Disaster Insurance in SEE

The principal regional issues discussed during the event focused on the lack of available information on credit and related issues - data on collection process and collection costs; information on real estate transaction prices; lack of centralized mortgage register, etc. Since most countries in the region have no substantial database on clients’ behaviour on servicing loans it is very important for all banks to start collecting information, in order to have the ability to utilise the mortgage application score modelling approach by 2006-2007.

A problematic issue in the region is associated with appraisals used in the loan process by banks. Lack of reliable information on real estate raises the question of creating some kind of inter-bank database that can remove the need from licensed appraisers. Another important question is the need for interaction and cooperation between insurance companies and banks.The introduction of mortgage insurance is seen as one of several possible approaches for serving mortgages and allowing lower income people to have access to financing. Moreover, mortgage insurance fits the security process. It is also important that banks grant mortgage loans imposing certain requirements that facilitate the security of such loans.  

Due to the long-term experience, know-how and expertise on the mortgage industry, Experian Decision Analytics was invited to participate and give a speech. This speech elaborated on the different phases of  the modelling mortgage parameters under Basel Il, as well as on the risk-based pricing for a small business mortgage portfolio. Before concluding, the difficulties and obstacles that arise while implementing the Mortgage Scoring Application for New European Banks were discussed.

Additional information about the Groups’ activities can be found on the website: www.ceemortgagefinance.org

IME webiste:http://www.ime-bg.org/en/index.html

One of the criteria for financial reliability in Western countries is the credit card, which plays the role of a special credit personal file for its owner. If a business person or a citizen does not have a “credit history”, it will be hard for him to be serviced by a bank or another financial institution with favourable conditions. Data about the overall financial status of the banks’ customers is extremely necessary for a credit card issue because through credit cards non-secured loans are practically granted. It is not a coincidence that banks demand credit applicants to fill in application forms with detailed information about their property status, as well as that of their wife/husband and parents.

In Bulgaria credit cards have not become popular yet. According to the information from Borika, at the end of 2004 the total number of credit cards is about 60.000. In comparison to the end of 2003, it increased by 18.000 in total but most banks in Bulgaria, especially the larger ones, spend a lot of money to attract solvent borrowers.

That is why it is predictable that with the growing number of credit card owners, the credit bureau business will also develop and people who will want to have such cards will have to become regular payers.

Despite worldwide established practices, the legal business with financial information in Bulgaria is still at a starting point. A year ago, BNB restructured its Central Credit Register for the needs of commercial banks. This step was made to enable the credit institutions to monitor the creditworthiness of both their corporate and consumer loan borrowers.

Moreover, every fifth day commercial banks are obliged to submit to the Central Credit Register information on loans lent to individuals and companies as stipulated under Regulation 22 of BNB and in compliance with the Law for the Banks (Article 52, Paragraph 5 for preserving the bank confidentiality). The Central Credit Register (CCR), which operates online, facilitates the decrease of delinquent bank loans and identification of debtors. Each bank can check whether its borrowers have non-serviced loans in other credit institutions. This information should prevent the banks from giving credit to borrowers who do not pay their duties regularly.

The most recent player amongst the private Credit Bureaux in Bulgaria is Experian-Scorex. Experian Decision Analytics has now signed Letters of Intent with thirteen banks, as well as leasing companies, insurance companies and some of the largest non-banking consumer lending institutions and credit card issuers. At a later stage, the goal of the Credit Bureau is for the telecom operators and utility companies to become members, thus making the information on the creditworthiness and the indebtedness of each borrower more complete.

Experian Decision Analytics will mark the start of its activity by providing the service of credit data sharing and once its credit register begins to operate it will offer various solutions for fraud protection and detection, as well as evaluation of applicants’ creditworthiness through the Credit Bureau database. The new Credit Bureau will provide constant access to accurate and reliable credit information on past payment behaviour of borrowers –individuals and companies – and on their current debt servicing status. Having access to this data, the banks will evaluate the credit risk more accurately and will reduce the application processing time and costs.

"The establishment of the Bulgarian Credit Bureau has been planned as part of our long-term strategy in the Balkans region, in which Experian Decision Analytics plays a leading role in the sphere of providing support to financial sectors, telecoms and utilities by means of supplying enhanced modern solutions for credit risk management" stated Roberto Giannantoni, the SCEE Director & Regional Board Member of Experian Decision Analytics, for The Banker newspaper.
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With the development of the banking services, the exact evaluation of the clients’ credit reliability will become more complex and a wider quantity of information will be needed.. This is why there are unexplored business opportunities for the Credit Bureau in Bulgaria. Many companies will be attracted by this business especially those which are start-up ones, but only the most competitive in terms of finance and information companies will remain.

The Next Wave of Direct Marketing in China – Learn How to Classify and Target Your Customers in China - Using Geo-demographics to Segment and Target Your Consumers.
China's expanding cities are exciting marketplaces, which sometimes can be baffling for marketers who need to quickly understand the segments and the consumers within them. This one-day workshop brought important new concepts and best practices to executives in direct marketing, customer communication and customer relationship management in China. The workshop was held in Shanghai on March 31^st  and was conducted by Professor Richard Webber, Fellow of the UK Institute of Direct Marketing and founder of China MOSIAC, China's first neighbourhood classification based on data sources for multiple geographic levels. Hosted by Harvard Business Review and Experian Business Strategies, this session taught marketers in China how to successfully apply the next wave of foreign direct marketing practices in their home markets. In addition a panel discussion was held with some of the leading industry experts in China.