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Risk Management


AI has exacerbated racial bias in housing. Could it help eliminate it instead?

#artificialintelligence

Our upcoming magazine issue is devoted to long-term problems. Few problems are longer-term or more intractable than America's systemic racial inequality. And a particularly entrenched form of it is housing discrimination. A long history of policies by banks, insurance companies, and real estate brokers has denied people of color a fair shot at homeownership, concentrated wealth and property in the hands of white people and communities, and perpetuated de facto segregation. Though these policies--with names like redlining, blockbusting, racial zoning, restrictive covenants, and racial steering--are no longer legal, their consequences persist, and they are sometimes still practiced covertly or inadvertently.


Japan Post closer to scrapping Saturday mail deliveries

The Japan Times

Saturday deliveries of ordinary mail from Japan Post may soon be a thing of past. During a Diet session set to begin on Oct. 26, the government plans to submit a bill scrapping such deliveries, sources have said. If the bill is enacted during the session, Saturday deliveries are expected to be abolished as early as autumn next year, the sources said. The government has been refraining from submitting the bill to revise the postal law in order to prioritize responses to sales irregularities involving postal life insurance products. The postal law currently requires Japan Post Co. to deliver ordinary mail six days a week or more.


Japan Post closer to scrapping Saturday mail deliveries

The Japan Times

Saturday deliveries of ordinary mail from Japan Post may soon be a thing of past. During a Diet session set to begin on Oct. 26, the government plans to submit a bill scrapping such deliveries, sources have said. If the bill is enacted during the session, Saturday deliveries are expected to be abolished as early as autumn next year, the sources said. The government has been refraining from submitting the bill to revise the postal law in order to prioritize responses to sales irregularities involving postal life insurance products. The postal law currently requires Japan Post Co. to deliver ordinary mail six days a week or more.


Data Scientist - Credit Risk

#artificialintelligence

Cleo was created to improve your financial health. Already, she's helped over 3 million people improve their relationship with money through simplicity and a sense of humour. She's an interface for the 99% – an AI assistant defining a new category, one that goes beyond saving up to actually changing how we feel about our finances. Through chat, Cleo hits you with ridiculously personal insights into your spending, while suggesting personalised financial products that increase your ability to save. That means we're meeting our users where they are and building the type of relationship they expect.


Introducing IFRS 17 Software With Machine Learning

#artificialintelligence

"We designed our IFRS 17 solution from start to finish with data quality in mind. We are the first on the market to do that," says Pawel Wozniak, CEO of 3Blocks. They have been working on IFRS 17 projects for insurance companies and other IT firms since 2016. Their solution has been built on the back of these experiences, taking into account lessons learned from them. Algorithms designed by 3Blocks learn what patterns are exhibited by claims, expenses, premiums, and other reporting data.


AI Scorekeeper: Scotiabank Sharpens the Pencil in Credit Risk

#artificialintelligence

Paul Edwards is helping carry the age-old business of giving loans into the modern era of AI. Edwards started his career modeling animal behavior as a Ph.D. in numerical ecology. He left his lab coat behind to lead a group of data scientists at Scotiabank, based in Toronto, exploring how machine learning can improve predictions of credit risk. The team believes machine learning can both make the bank more profitable and help more people who deserve loans get them. They aim to share later this year some of their techniques in hopes of nudging the broader industry forward. The new tools are being applied to scorecards that date back to the 1950s when calculations were made with paper and pencil.


Insurance Company Uses Artificial Intelligence to Promote Worker Safety -- Occupational Health & Safety

#artificialintelligence

Artificial intelligence will offer ergonomic assessments to employers. Travelers Insurance Companies has started using artificial intelligence to administer ergonomic assessments, according to Insurance Journal. The company claims to be the first of its kind to provide this kind of service, which combines AI technology and ergonomic research to identify potential risk factors based on a video of an employee completing a task. The software produces a report based on the video, then an employee from Travelers develops an alternative, safer plan for the worker to follow. These ergonomic assessments are geared to enhance worker safety and reduce the number of workplace injuries.


[R] Artificial Intelligence is stupid and causal reasoning won't fix it

#artificialintelligence

If a ML system uses gender information in credit scoring, then gender information is probably relevant for credit scoring. We all know that women, for example, are more risk averse than men on average and that there are more men with very low IQ's; and more men take part in dangerous activities than can maim them. All those things contribute to credit risk. I looked at some actuarial motorcycle accident data from a Swedish insurance company a couple of years ago, and the accident rate of young men (18-25 maybe) was something like 40 times higher than women in the same age interval. Of course, EU law requires us to offer the same rate to men and women, so we have to ignore this; and thus the women pay more than they should if things were fair.


Credit Risk Management: Classification Models & Hyperparameter Tuning

#artificialintelligence

Which algorithms should be used to build a model that addresses and solves a classification problem? When it comes to classification, we have quite a handful of different algorithms to use unlike regression. To name some, Logistic Regression, K-Neighbors, SVC, Decision Tree and Random Forest are the top common and widely used algorithms to solve such problems. Here's a quick recap of what each algorithm does and how it distinguishes itself from the others: Let's see how they work with our dataset compared to one another: After importing the algorithms from sklearn, I created a dictionary which combines all algorithms into one place, so that it's easier to apply them on the data at once, without the need to manually iterate each individually. After applying the algorithms on both train and test sets, it seems that Logistic Regression doesn't work well for the dataset as the scores are relatively low (around 50%, which indicates that the model is not able to classify the target).


AI and Virtual Assistant for Insurance Sector: 10 Ways to Maximise Performance

#artificialintelligence

Evolution in business concepts and implementation of the latest technology trends are driving the thriving growth of businesses. Among all, artificial intelligence is best known to transform a business by automating the processes and making the tasks seamless. And the inventions like virtual assistant and chatbots are practically implementing these concepts to showcase results that promise skyrocketing growth and boost in business. A virtual assistant is a bot that assists the users to complete tasks throughout the time. By implementing the practical concepts of AI and machine learning, these assistants are created to provide a personalized feel to users and offer excellent user experience.