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Banking on Predictive Analytics comprehensive 5-day intensive in-house data mining and predictive analytics course for bankers “The Basel II Accord, advised banks to use advanced analytics techniques to measure, monitor, manage and mitigate risk levels. Complying with the Basel II Accord is a critical issue for global banking institutions!!” www.valuefronteira.com 4th Floor (rear wing); 42, Olowu Street, Ikeja Banking on Predictive Analytics Introduction When banks are - on a sustainable basis - able to successfully mine the data that have been locked up in their operational and financial systems and speedily act upon the emerging insights, they unequivocally beat competition in such areas as risk management, operational efficiency, marketing and customer management as well as overall performance optimization. Banking on predictive analytics enables banks to have mastery over all the potential and actual key risk exposure areas namely credit, operational, market, financial and more. It equally enables the banks to gain a single view of customers in such a way as to help increase wallet share, improve customer satisfaction and loyalty, service mass market customers more cost effectively and offer the products and services they need. At the level of operations, it helps to shore up internal operations—including finance, IT, customer service, HR, sales—to ensure the entire organization is running at peak efficiency. Course Description Banking on Predictive Analytics is designed as a comprehensive 5-day intensive and hands-on data mining and predictive analytics course to equip participants with the skills for analyticsdriven value optimization in their banks along four critical areas namely: credit risk management, fraud prevention, marketing and operational efficiency. In this regards, participants will be equipped with the state-of-the-art credit risk measurement and management techniques as well as the skills for unearthing the needed insights for truly implementing a “one-to-one” approach to customer relationships. Participants will also learn how to anticipate and quickly detect fraud and take immediate action to minimize costs. This course is NOT DESIGNED as open course but to be offered in-house or among a collection of participants from a maximum of three organizations operating within the financial services industry. The objective is to build a reasonable cluster of analytics-savvy employees who can revolutionize business optimization and overall decision making in their firms in favour of facts and evidence (as against hunches and intuition) based prediction. The overarching expectation is that the trained clusters of bankers should be able to trigger and sustain a culture of aggressive search for insights based on evidence backed predictions, proactive as against reactive responses to issues, all of which are equally accomplished in real time. Learning Outcomes At the end of the five-day period, participants will have acquired the skills for: • Predicting and proactively measuring, monitoring and mitigating credit and operational risk exposures and defaults using different quantitative techniques; • Developing analytical models that can guide loan-related decisions that will effectively minimize potential losses arising from bad loans; Identifying key markets as well as customer segments, assess business needs and come up with effective business strategies using powerful algorithms; Harnessing the capabilities of advanced techniques in analyzing customer-centric data that helps banks to identify avenues to create business value, thereby making the business profitable; Structuring campaigns with higher success rates as well as fine-tune the campaign management strategy based on insights gathered by monitoring campaign execution and the aftermaths; © ValueFronteira-Training / 2011 P a g e |2 Banking on Predictive Analytics Reducing marketing efforts to unlikely buyers. Participants will learn how to bring down campaign cost by avoiding mass campaigning and targeting the customers with higher propensity to buy; Ability to create business value, enhance existing value and retain value generated by their strongest assets-‘’valuable customer base’’. Application Software All our training programmes emphasize the impartation of methodological skills and are absolutely hands-on utilizing relevant state-of-the-art software such as Microfit, R, Statistica, JMulti, Matrixer, SPSS, Rattle, SAS, excel, e-views, etc as the case may demand. Only Statistica and Eviews 7 will be used for this particular programme. In addition to that, this course is designed to utilize data and case studies on the Nigerian financial services sector particularly the banks for training. Pre-Requisites: 1. Basic knowledge of statistics; 2. Good practical knowledge of windows based computer applications. Participants are expected to come with their own laptops if trainings take place in venues outside our econometrics and analytics laboratory. Where this is however not possible we shall be notified in time so that we can make arrangements for those who do not have their own PCs. The Modules Day 1: Data Manipulation and Statistical Foundations Data Manipulation Review of Descriptive Statistics Tests of Statistical Significance Probability Sampling Regression Analysis Cluster Analysis Day 2: Credit Risk Analytics Credit Delinquency Scorecards Customer Approval and Conversion Optimal Loan Amount, Pricing and Loan Duration Market Risk / Basel II Analytics Portfolio Loss Forecasting Collections Analytics Day 3: Banking Fraud Analytics Areas in Which Fraud Can Occur What Fraudulent Activity Would Look Like in the Data Data Sources Required to Test for Indicators of Fraud "Fraud” Vs. “Erroneous” Claims, Information, Etc. Fraud Detection as a Predictive Modeling Problem Predicting Rare Events Fraud Detection as Anomaly Detection, Intrusion Detection Anomaly Detection © ValueFronteira-Training / 2011 P a g e |3 Banking on Predictive Analytics Rule Engines and Predictive Modeling Text Mining and Fraud Detection Day 4: Bank Marketing Analytics Market Mix Modeling and Media Optimization Campaign Effectiveness Discrete Choice Modeling Pricing Analytics Channel Analytics Churn Analytics Product Bundling Cross-sell/Up-sell Models Purchase Driver Analytics Introduction to Structural Equation Modeling Day 5: Banking Operations Procurement Analytics Capacity and Resource Scheduling Network and Logistics Cost and Quality Management Process Efficiency Who Should Attend? Credit Officers, Researcher officers, strategy and Planning officers, Retail Bankers, Portfolio Managers, Asset Managers, Wealth Managers, Insurers and anyone in a liaison position for business functions, credit approval, collections and other related roles in credit. The course will also benefit those calibrating portfolio risk and working with retail or SME portfolios who monitor overrides and gather feedback. It will be of particular relevance for persons in retail banking functions working with sales, product teams, finance, compliance and credit operations. Fees The schedule of fees charged for this in house course is as presented below. Please note that the fees cover course materials, facilitation fee, venue and lunch. Additional discounts beyond the one offered below may be negotiated where the client chooses to provide both venue and lunch for the course. Such additional discounts however will not exceed 10% of the amount payable (net of the offered discounts). Category Range of Participants Size Fee Per Participant(N) Discount Offered (%) A 100 + 120,000 30% B 50 -99 120,000 20% C 30 -49 120,000 15% D 20 -29 120,000 10% E 15 -19 120,000 0% F 10 -14 150,000 0% It is also important to note that regardless of the size of potential participants our maximum class size for this course is 20 participants at a time. Therefore most participants will be trained in batches. © ValueFronteira-Training / 2011 P a g e |4 Banking on Predictive Analytics Enquiries and Contacts For further inquiries on the Banking on Predictive Analytics course kindly contact the following persons: Ebele Vera Olanma Martin 08131218704 | [email protected] 08034546948, 01-8417203 | [email protected] 08033923041 | [email protected] 08033148722 | [email protected] Office Location Office address is as follows: ValueFronteira Limited, 4th Floor (rear wing); 42, Olowu Street, Ikeja. [email protected] © ValueFronteira-Training / 2011 P a g e |5