Helping financial institutions identify, quantify, and mitigate risks.
WHAT WE DO
We are experts in applying statistical and econometric techniques to time series, cross-sectional data, and panel/longitudinal data to model complex business environments. We help our clients develop customized models to support decision-making and manage risks. We have developed and implemented models to estimate the probability of default of publicly traded firms and of individual loans, to quantify the exposure of our clients to various changes in the economic environment, and to forecast the performance of various lines of business and loan portfolios.
Financial institutions rely heavily on quantitative analysis and models in most aspects of financial decision making and are therefore exposed to model risk. Basing decisions on incorrect models or misinterpreting, and consequently, misusing the models’ results can lead to adverse consequences including direct financial loss, loss of competitive position, wasted time and resources, and possible legal suits. The key to mitigating model risk is model validation which entails a comprehensive review of all components of the model: the data, the theoretical framework, the technical implementation of the model, the reports generated by the model, and the model’s documentation. We provide external independent model validation services making sure that our clients are fully informed about the strengths, weaknesses, and limitations of the models they use.
We assist financial institutions comply with regulatory requirements for Comprehensive Capital Analysis and Review (CCAR) and Dodd-Frank Act Stress Testing (DFAST), and the implementation of the Current Expected Credit Loss (CECL) standard. We support our clients in all stages of the process, including project management, data collection and preparation, econometric modeling, documentation, and report preparation. Compliance with these regulatory requirements provides financial institutions with a set of models that can be used to anticipate and mitigate micro- and macroeconomic risks. We work with our clients to derive actionable insights from these models.
We assist banking holding companies develop dynamic, forward-looking capital plans by developing accurate statistical models that identify and quantify financial and economic factors that drive business performance over a long-term horizon (3-5 years). We stress test these models to assess the impact of unanticipated events based on regulatory scenarios, internally developed scenarios, and our client-specific scenarios. We work with senior management to assess the results of these tests and to design strategies to mitigate strategic risks.
In today's highly regulated business environment risk management has become a technically complex, costly, and yet essential component of bank operations. Our team helps financial institutions assess and control risks. We bring together academic, technical, and business expertise to design highly customized solutions to the problems our clients face. We deliver unmatched value to our clients by following two principles:
Our experience in applying research-based methods to complex business environments enables us to design highly accurate models fitted to our clients' unique positions.
We believe that full transparency regarding modeling details, including assumptions and limitations, enables our clients make the best use of our models. Therefore, we provide our clients with detailed documentation of model development and implementation, and work closely with them to communicate technically challenging concepts to all levels of the organization.
ECON|Analysis is linked to a network of talented professionals including data analysts, quants, seasoned risk management professionals, and academic experts. To serve our clients best we build task-specific teams, led by our founder Dr. Oded Bizan. Our shared goal in each engagement is to enable our clients make decisions based on the most accurate analysis at a competitive cost.
ODED BIZAN, PH.D.
Dr. Bizan specializes in econometrics, industrial economics, and finance. For over 18 years, Dr. Bizan has assisted corporate and government clients in a variety of engagements that require expert interpretation of economic issues and data.
Recently, Dr. Bizan has been helping medium- and large-size banks comply with regulatory requirements for DFAST, CCAR, Basel II and III, and CECL implementation, supporting them in all stages of the process from data collection and preparation, through modeling, reporting, documentation, and model validation.
Dr. Bizan taught undergraduate and graduate courses at the economics departments of Northwestern University, Haifa University, and Tel Aviv University.
Dr. Bizan received his Ph.D and M.A. degrees in economics from Northwestern University, and his B.A. degree in economics, summa cum laude, from Tel Aviv University.
Our clients include a wide range of financial institutions including commercial banks, federal home loan banks, hedge funds, and risk management advisories.
A large regional U.S. bank
We developed a set of 20 time-zero public firm probability of default models: 1-year and 5-year default probability for ten industrial sectors. The models were subject to regulatory review as part of the bank’s CCAR submission.
A large regional U.S. bank
We performed independent model validation on 14 credit risk DFAST models (PD and LGD). Each validation involved a comprehensive review of Input, Processing, and Output components. For each PD and LGD pair we assessed empirically the PD-LGD correlation and its impact on expected loss.
A small regional U.S. bank
We validated 43 internally-developed balance sheet models, including deposit models, loan models, non-interest expense models, and non-interest income models. For each model the validation focused on assessing the soundness of the selected methodology, which led, in a second phase, to the re-development of 30% of the models. Benchmark models were developed for 24 of the evaluated models.
A Federal-charted Bank
Pursuant to FHFA 2013-AB-07, we validated two newly developed default probability models prior to first use: Banks & Thrifts and Credit Unions. Following our recommendations the models were modified substantially and were approved for initial use after a follow-up, limited scope validation.
A Federal- charted Bank
Pursuant to FHFA 2013-AB-07, we validated a vendor product that is used to calculate the Value at Risk (VaR) for the bank’s annual operational losses, consistent with the Advanced Measurement Approach (“AMA”).
80 Hillside Terrace, Belmont, MA 02478
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