Supports the NAIC's macro-prudential surveillance of US insurance industry assets by (a) monitoring investment markets for each of the major asset classes owned by insurers (fixed income, equities and real estate) as well as other potential markets insurers may consider for investment; (b) considering the potential risks and issues related to those investments and markets; and (c) analyzing the potential impact of adverse market conditions on US insurers' investments, individually and as a group. Demonstrates broad, innovative thinking that encompasses analyzing credit risk and other issues such as liquidity and volatility; and also takes into account portfolio and asset/liability considerations Leverages a variety of resources (i.e. industry experts, investment banking research, rating agency reports among others), with guidance identifying relevant theses, and deriving thoughtful conclusions as part of the analytical process Performs accurate and complete qualitative and quantitative analysis of investment portfolios or specific parts of an investment portfolio of insurance companies, identifying specific risks and potential concerns and any significant exposures that could impact insurer solvency Writes and interprets SQL or Access queries for standard as well as ad hoc data mining purposes. Tableau) to spot trends and anomalies as well as create unbiased stories and conclusions with data Attends conferences, webinars, seminars, NAIC continuing education courses, etc. to further knowledge of capital markets, various types of investments (i.e. Supports the NAIC's macro-prudential surveillance of US insurance industry assets by (a) monitoring investment markets for each of the major asset classes owned by insurers (fixed income, equities and real estate) as well as other potential markets insurers may consider for investment; (b) considering the potential risks and issues related to those investments and markets; and (c) analyzing the potential impact of adverse market conditions on US insurers' investments, individually and as a group. Writes and interprets SQL or Access queries for standard as well as ad hoc data mining purposes.
Dear Liz: I recently received a $38,000 windfall. I have a student loan balance of $37,000. I want to buy a home, but I can't decide if I should have a large down payment and continue paying down student loans slowly, or make a balloon payment on my student loans and put down a smaller amount on the home. The mortgage rate would be around 4% while the student loans are at 6.55%. The price of homes in my area is at least $250,000 for a two-bedroom house (which my income supports).
The GENIUS Automated Underwriting System is an expert advisor that has been in successful nationwide production by GE Mortgage Insurance Corporation for two years to underwrite mortgage insurance. The knowledge base was developed using a unique hybrid approach combining the best of traditional knowledge engineering and a novel machine learning method called Example Based Evidential Reasoning (EBER). As one indicator of the effkacy of this approach, a complex system was completed in 11 months that achieved a 98% agreement rate with practicing underwriters for approve recommendations in the fist month of operation. This performance and numerous additional business benefits have now been confirmed by two full years of nationwide production during which time some 800,000 applications have been underwritten. As a result of this outstanding success, the GENIUS system is serving as the basis for a major re-engineering of the underwriting process within the business. Also, a new version has recently been announced as an external product to bring the benefits of this technology to the mortgage industry at large. In addition, the concepts and methodology are being applied to other financial services applications such as commercial credit analysis and municipal bond credit enhancement. This paper documents the development process and operational results and concludes with a summary of critical success factors.
It can be difficult to design and develop artificial intelligence systems to meet specific quality standards. Often, AI systems are designed to be "as good as possible" rather than meeting particular targets. Using the Design for Six Sigma quality methodology, an automated insurance underwriting expert system was designed, developed, and fielded. Using this methodology resulted in meeting the high quality expectations required for deployment.
Southern California home prices jumped in February, posting the largest increase in more than a year, as buyers rushed to outbid one another for a meager selection of homes for sale. The six-county region's median price for new and resale homes hit $460,000 last month, up $5,000 from January, real estate firm CoreLogic said Tuesday. The median -- the point where half the homes sold for more and half for less -- is now 7% higher than it was in February 2016. That's the largest year-over-year rise in 15 months and follows nearly five years of steady price increases, a result of a rebounding economy, low mortgage rates and few homes on the market. Low inventory -- as well as one fewer day to record sales last month than in February 2016, which included a leap day -- probably had a role in the 1.7% decline in sales from a year earlier, CoreLogic said.