In the normal course of business in the deregulated environment, the retail electricity component of the utility undertakes transactions that expose the value of its overall assets and liabilities to the basic cyclicality of the economy. Regular economic cycles result in fluctuations in electricity demand, price elasticities, and inflationary pressures on costs and cash flows. Cyclical changes in input fuel market conditions, and cyclical changes in the labour and raw material markets are also risk factors The utility required understanding of different processes in their retail electricity business process. Prescio Consulting, LLC was approached to develop a detailed flow map of the business process, systems and data flow, and identify all the market risks involved in retail pricing of electricity. Prescio Consulting worked with the utility to completely chart the business and identify all market risks. Prescio Consulting completed the project ahead of schedule and in keeping with customer expectations of the quality of the project.
The client used an existing general time series model capable of capturing salient features of the data, but solving for the conditional distribution of the asset price or total returns associated with arbitrary dates in the future proved to be extremely difficult. Prescio Consulting Commodities Practice was approached to provide a solution to this problem. Although substantial academic literature existed relating to unconditional moments, very little research existed to provide a solution for the moments which are most relevant to traders — the moments which exploit known information today. Using rigorous analysis and advanced statistical theory, Prescio Consulting worked with the utility to adapt this pricing methodology to a wide variety of issues facing the firm, including the pricing of complex structured physical supply contracts.
Prescio Commodities Practice provided a solution to this problem, and detailed a combination of numerical and analytical procedures to solve for the conditional distribution of asset prices or returns, for any arbitrary date in the future, based on the original model.
The firm planned to build a marketplace for energy derivative products whose values were very sensitive to the correlation between heating oil, gasoline, and crude oil prices. In response to the client's request, Prescio Consulting undertook an exhaustive analysis of these energy market correlations. Prescio Consulting utilized advanced econometric methods to estimate time varying correlations that depend on prevailing market conditions (such as the spread between gasoline and crude oil prices). Prescio Consulting also developed an algorithm to forecast the relevant correlations over any time horizon. The client has implemented this methodology in its new energy trading operations.
The utility recognized that pricing approaches which applied in financial markets (and some other commodity markets) were inappropriate for electricity due to the unique characteristics of this product. Prescio Consulting proposed and implemented a novel valuation and risk measurement approach that addressed the utility's concerns about traditional pricing approaches. The Prescio Consulting approach (described in our Electricity page on this website) exploits the transparency of the fundamentals in the power market and explicitly models the effects of the non-storability of power, the seasonality of demand, and the non-linearity of power prices. Prescio Consulting used this model to create a customized derivatives pricing software for the client.
The utility wanted to develop a new load profiling model and application software in order to aggregate the present and future customers into finer load profile classes. Load profiling classifies a customer into a given group according to certain key characteristics. The finer the aggregation within a group, the higher the accuracy of the load profiles. The primary purpose of a finer aggregation is to attempt to reduce the biases resulting from assigning a class load shape to a subgroup of customers whose shape may be different from the class shape.
Prescio Consulting designed a Load profiling model to statistically attempt to segment different classes of customers into finer sub-classes with homogenous and functional characteristics This was done to minimize misclassification errors. Additionally Prescio Consulting fully incorporated weather patterns and economic indicators, as well as time characteristics into the profile curve models to make them dynamic and realistically driven by these key factors. The load model was also designed to forecast monthly average usage per profile class. These monthly aggregates could then be distributed over hours in each forecasted month, factoring in expected weather conditions, time of day characteristics, and economic activity trends.
A customer-switching model was developed to calculate switching impacts on the number of customers in each profile class. The switching model was used to generate the dynamics of the population over time within each profile class. Customized application software was then designed and developed to be seamlessly incorporated within the existing hardware and software architecture of the utility. The model was coded in C with a VB interface and Oracle 8i database.
Prescio Consulting initiated a comprehensive research on the feasibility of call centers in the specific Asian company's country to serve the global marketplace. The effort resulted in a significantly positive outlook for the conglomerate to invest in a stand-alone, web-enabled, inbound outsourcing call center for the Asian and North American retail and commercial customers of global corporations. Outsourcing was the largest segment of the worldwide call center services market and was projected to grow to $42 billion in 2003. It was determined that a growing number of corporations were outsourcing their call center services to call centers in Asian countries. The specific country of interest to the conglomerate was identified as one of these countries.
Additional efforts were directed towards developing the call center architecture and implementation strategy for inbound call center services through telephone, web-enabled call back, net phone, and net video.
The wholesale power-marketing analytical group of a large US utility needed to validate their state-of-the-art in-house electricity forward curve and stochastic price forecasting models by an independent third party. Prescio Consulting developed the complete flow map of the models from data input to results and reporting. Prescio Consulting identified the fundamental premises on which these models were based and the mathematical techniques applied to develop the models. While the models were appropriate in most aspects, Prescio Consulting recommended certain additions and mathematical techniques to incorporate several missing variables.
A model was built that could analyze a given consumer portfolio, be able to filter customized portfolios given an original portfolio for different loan variable scenarios, and value the different portfolios and report the portfolio results. Additionally, the model was designed to be able to compare the values of portfolios created under different loan variable scenarios. The application software developed for the model included capabilities for analysts to perform ad-hoc statistical analysis on the portfolio data as well.
Prescio Consulting performed a comprehensive study of B2B commerce for the Asian region in question. The outcome of the study was a concept paper for the feasibility of such a venture for the client in question. The key outcome of the study pointed towards the company not venturing into developing a stand-alone B2B e-commerce site but as a distribution channel for their existing core business lines. The study concluded that the new B2B venture would have a considerable probability of success if it were initiated as an extension of the current business lines. The venture would then develop toward a stand-alone B2B e-commerce portal. In addition, a complete implementation plan of such a B2B site was also developed and submitted to the client for consideration.
The project required an in-depth analysis of the data flow from various data storage systems, data flow within the software, reporting, model assumptions, and logical and coding errors in the software. Prescio Consulting was to perform the work within a specific period of time so that the client could meet an important deadline. After completion of the initial project, the engagement was extended to include several additional projects. The client requested further work on incorporating major changes and additions to the model and the software to address several loan history idiosyncrasies due specifically to the clients' operational systems.
The initial project and the extensions were performed and implemented in record time and exceeded the clients' expectations.
Prescio Consulting was requested to perform the analysis of the historical weather data to identify specific issues related to the precision of the data. Specific statistical and simulation models were needed to analyze the historical data.
Prescio Consulting was requested to conceptualize the model and develop an application that could be applied by different levels of staff and management. The client requested that the model and the application be built in a way that allowed for maximum flexibility in data storage formats, operating systems, and reporting platforms. In addition, the client requested that the model be based on a conceptual platform similar to the Value at Risk concept for ease of decision making.
The project called for thorough analysis of the client's portfolio of products and data. Modification of the client's data was required to extract relevant information required by the Average Loss Rate analysis and Markov forecasting model. This information included determining data for variables such as Outstanding, Commitments, Chargeoffs, Recovery, and LTVR among others. Prescio developed the application to extract the data in the format required by the Migration Model. Prescio proceeded to exceed the client's expectations by both implementing the application software and training the client's personnel in record time.
The client's personnel recommended to senior management that Prescio Consulting address some of the Bank's other Risk Measurement and Management issues as well as its quantitative and business process issues.
The project requires thorough understanding of the clients business, including the client's portfolio of products, current risk management methodologies, business processes, systems, data architecture and data flow. This intimate knowledge of the client is necessary in order to apply the Basel II Accord's recommendations to the client's unique conditions.
The project is current and an update will be provided as the project is completed.
The project required complete understanding of the banking loan process and different scenarios for different loan types. Although being a completely new project for Prescio, we at Prescio took it as a challenge and worked around the clock to understand a loan process. We were able to deliver to the client a thorough detail on the loan disbursement process.
The SAS based application was developed internally by the statistical and quantitative modelers of the Bank. Prescio's personnel included business domain experts, statisticians, mathematicians, SAS experts and project managers. Discussions between the Prescio team and the executives of the risk management and the quantitative group of the Bank were held. From these discussions, it was decided that a validation project would examine different facets of the model according to standard validation practices of the industry. Prescio performed a multiple step validation process which included, analysis of the theoretical fundamentals of the model, analysis of the business fundamentals, analysis of the internal data, analysis of the Structured Scenario data, determination of the distributions applicable to individual loss events, the combining of internal and structured scenario data, addressing issues related to the Extreme Value theory, and validating their SAS code. Prescio was able to deliver the clients’ requirements within a very tight delivery schedule. Prescio’s performance resulted in follow-on work for other Basel related models in commercial and retail credit.
The intent of the exercise was to determine ways to develop better alternatives to reduce losses from home foreclosure and, if needed, to maximize the REO value for all concerned stakeholders. The objective was to integrate and analyze market data from different vendors and develop a loss mitigation utility, through which delinquent mortgages could be passed to reduce losses and maximize value for all stakeholders. To that effect Prescio was the key member to receive, integrate, cleanse, analyze and distribute data and results to various groups of the development team. Analyses were performed on several variables including House Price Index (HPI) for different Metropolitan Statistical Areas (MSA) and national HPIs, historical Probability of Default (PD), discretionary spending index (DSI), discretionary spending (dsdollar), age, ability to pay (ATP), Combined Loan to Value ratio (CLTV), income (Income360), and FICO / BEACON scores among others. The final utility was a net present value (NPV) calculator for different loan, property, and borrower behavioral and credit scenarios that could be used by the client to determine the best option(s) available to all stakeholders prior to or after foreclosure. This project was performed within a four week period under a strenuous environment in partnership with more than five vendor and development groups.
Some enterprises such as wineries use LIFO based financial statements to reduce federal and state taxes and increase the cash flow of the enterprise. However the quarterly and interims are in FIFO or Spec-ID basis. This requires outsiders to transform the annuals, the interims and the quarterly to the same format for comparison purposes. Also this transformation allows easier comparison with other enterprises who report in FIFO format. The intent of this exercise was to develop an application that would take the LIFO based financial statements of some wineries and transform them into FIFO based statements and allow for additional analysis of the reports. The objective was to develop an Excel based application that would take several annual LIFO statements generated by Moody’s Financial Analyst (MFA) and convert them into FIFO statements. The application needed to provide Credit Recommendation (CR), Problem Loan Reporting (PLR), and Primary Source Break Even (PSBE) analysis capability to the users. The project required financial statement analysis, report generation, analytics and coding in VBA. The end product was delivered to client specification well in advance of the delivery date. The end product is now being used by several Credit Administrators within the bank. An enhancement to the original product has since been requested.