London, United Kingdom
London, United Kingdom

Time filter

Source Type

Nino M.,National Autonomous University of Mexico | Jaimes M.A.,National Autonomous University of Mexico | Reinoso E.,National Autonomous University of Mexico | Reinoso E.,ERN Inc
Natural Hazards | Year: 2014

A seismic-event-based methodology to generate earthquake-induced translational landslide maps using Newmark method is proposed. The steps are: (1) to construct a GIS-based geotechnical database; (2) to identify those areas that are susceptible to the occurrence of translational landslides based on available geological information; (3) to compute a static safety factor; (4) to compute the critical acceleration that defines the threshold acceleration required to cause a displacement; (5) to characterize the seismic hazard as a set of stochastic events, collectively exhaustive and mutually exclusive, that fully describes the hazard spatial distribution and annual frequency of occurrence (in accordance with the earthquake location, depth and magnitude) with the appropriate ground-motion prediction equations; (6) to compute the Newmark displacement; and finally, (7) to carry out a probabilistic translational landslide hazard analysis to estimate an exceedance rate of a given displacement. This methodology is applied to Mexico, and maps for return periods of 150 and 500 years are presented. Results shown in maps are estimations of where translational landslides may occur and should be useful to carry out local studies to elaborate recommendations of site specific hazard reduction plans as well as to calculate insurance rates. In addition, these results are useful to identify civil protection actions, risk management at regional and local level, and land use planning, as well as for promoting more detailed vulnerability and risk studies at different scales. © 2014 Springer Science+Business Media Dordrecht.


Jaimes M.A.,National Autonomous University of Mexico | Jaimes M.A.,ERN Inc | Reinoso E.,National Autonomous University of Mexico | Reinoso E.,ERN Inc | Esteva L.,National Autonomous University of Mexico
NCEE 2014 - 10th U.S. National Conference on Earthquake Engineering: Frontiers of Earthquake Engineering | Year: 2014

A criterion for the estimation of losses of a system exposed to several multi-hazard sources is presented. The procedure considers the statistical correlation of failure modes of a system due to the action of groups of multiple simultaneous natural processes, each group associated with events generated by a given hazard source; this means that the possible interaction between natural processes generated by that hazard source is taken into account in a formal way. Finally, all relevant hazard sources of different origins that may significantly contribute to the risk for the system of interest are taken considered as independent processes, with a negligible probability of producing simultaneous groups of significant events.


Jaimes M.A.,National Autonomous University of Mexico | Reinoso E.,National Autonomous University of Mexico | Reinoso E.,ERN Inc | Ordaz M.,National Autonomous University of Mexico | And 5 more authors.
Ocean and Coastal Management | Year: 2016

A new approach is proposed for the probabilistic financial risk assessment of earthquake-induced tsunami. The risk is evaluated in a probabilistic framework for a full set of hazard events including all uncertainties. The hazard is defined as a stochastic and historic set of events, collectively exhaustive and mutually exclusive, that describes the spatial distribution, the annual frequency and the randomness of the hazard intensity. The risk is expressed as losses in different terms: the average annual loss and the loss exceedance curve. These metrics are of particular importance for risk financing schemes and risk transfer instruments. As an illustrative example, this approach is applied to the probabilistic tsunami risk assessment for public schools in southern Mexico. © 2015 Elsevier Ltd.


Reinoso E.,National Autonomous University of Mexico | Reinoso E.,ERN Inc | Ordaz M.,National Autonomous University of Mexico | Ordaz M.,ERN Inc | And 3 more authors.
NCEE 2014 - 10th U.S. National Conference on Earthquake Engineering: Frontiers of Earthquake Engineering | Year: 2014

In this paper the main characteristics of the R-FONDEN, the non-commercial software built exclusively for the federal government to compute net losses (both for a given return period or a given scenario) for buildings and infrastructure in Mexico will be shown. Although this software is made for most of natural hazards such as hurricane (wind, flood, storm surge), hail, wildfires and drought, among others, emphasis will be given to the earthquake related hazards such as strong ground motion (including site effects due to soil amplification and liquefaction), landslides and tsunamis. Characteristics of the R-FONDEN modules for rapid risk assessment and for early warnings systems will also be shown.


Quijano J.A.,Instituto Nacional Of Investigaciones Forestales Agricolas Y Pecuarias Inifap | Jaimes M.A.,National Autonomous University of Mexico | Torres M.A.,National Autonomous University of Mexico | Reinoso E.,National Autonomous University of Mexico | And 5 more authors.
Natural Hazards | Year: 2015

An event-based approach for the probabilistic risk assessment of agricultural drought under rainfed conditions to estimate the economic impact is proposed. The risk parameters are evaluated in an event-based probabilistic framework for a set of hazard events; these results are probabilistically integrated including, in a formal way, all uncertainties related to every part of the process. The hazard is defined as a stochastic or historic set of events, collectively exhaustive and mutually exclusive, that describes the spatial distribution, the annual frequency, and the randomness of the hazard intensity. The risk is expressed in different economic terms: the average annual loss (or pure risk premium) and the loss exceedance curve; these metrics are of particular importance for risk retention (financing) schemes or risk transfer instruments. As an illustrative example, this approach is applied to probabilistic drought risk assessment of maize under rainfed conditions in Mexico. These results are the base of further studies in defining strategies for financial protection against agricultural losses and disasters. © 2014, Springer Science+Business Media Dordrecht.


Jaimes M.A.,National Autonomous University of Mexico | Nino M.,National Autonomous University of Mexico | Huerta B.,ERN Inc
Natural Hazards | Year: 2015

This paper proposes a hurricane event-based method to construct a map for heavy rainfall-induced translational landslides. This method involves five steps: (1) construct a GIS-based geotechnical database; (2) identify the areas in the vicinity which are susceptible to translational landslides based on the slope of the terrain and the geological information available; (3) characterize the heavy rainfall hazard due to hurricanes (typhoon) as a set of collectively exhaustive and mutually exclusive stochastic events, that fully describe spatial distribution and annual frequency of occurrence (in accordance with storm category, storm position, distance between the eye of the storm and the site of interest, among others factors); (4) compute the ratio between the steady-state rainfall produced by a hurricane event affecting the tributary area of the slope under analysis, Qs, and the critical steady-state rainfall necessary to trigger slope instability, Qc, and finally; (5) carry out a probabilistic translational landslide hazard analysis to estimate the exceedance rate of a given ratio Qs/Qc. This method is applied to maps of Mexico for return periods of 50 and 150 years. The results shown in these maps are estimates of where the translational landslides may occur, and they should be useful to carry out local studies and to elaborate recommendations of site-specific hazard reduction plans as well as to calculate insurance rates. In addition to this, these results are useful for identifying actions of civil protection, regional and local risk management, and land use planning, as well as the promotion of more detailed vulnerability and risk studies on different scales. © 2014, Springer Science+Business Media Dordrecht.


News Article | October 6, 2013
Site: techcrunch.com

In what feels like an ever-so-slightly protracted seed round, ERN has raised a further $1 million in seed funding, bringing the total raised by the London-headquartered company to $5.6 million. This time the fresh injection of capital is pegged to finance its expansion into Asian markets, as ERN is also announcing that it’s hired ex-American Express Head of Global Marketing Brian Thom as its president for Asia. Unsurprisingly, given the startup’s mission to use big data to enable banks and merchants to create loyalty-based offers for cardholders, Thom has a background in retail banking and cards, having previously served at American Express Bank, along with being Regional Marketing Head for MasterCard Asia Pacific, and President of Citibank Card Services for Japan. He’s also said to have “more than 10 years of experience” in managing startups in Asia. So, on paper at least, the fit is good. ERN’s analytics platform, dubbed “Looop,” enables banks/card issuers and participating merchants to boost customer loyalty by creating new products and offers based on the analysis of their card transactions. The idea is that by drilling into the big data around a customer’s transactional history — after they’ve opted in, of course — individually tailored offers can be pushed to their smartphones via the Looop app or other channels in the form of an e-coupon redeemable in-store. In addition to insights gained through mining customers’ transactional big data, the targeting of offers can also be geo-fenced, e.g. only pushed an offer when a customer who has previously bought a dress is within a certain radius of the participating store. Last month the company announced its first major client win since unveiling the platform at the FinovateEurope 2013 conference in February. It’s signed up The Retail Data Partnership (TRDP), which supplies a network of some 1,500+ independent merchants in the UK with EpoS systems, who will have access to ERN’s Looop Big Data Analytics platform and customer loyalty capabilities to maximise the transactions that customers make. In today’s announcement it also mentions a number of other unnamed clients in both Europe and Asia. As for why it needed to raise more funding, which once again comes from unnamed private investors, big data costs big money, while specifically, Asia expansion is the target this time around. We can also presume that some of its previous funds will have been spent on two acquisitions ERN made in August. It bought two UK companies, Inspired Analytics and Elucidata, to bolster the analytics side of its platform, not least personnel, in what looked a lot like an acqui-hire.


ERN, the London-headquartered startup that’s planning to use Big Data to enable banks and merchants to create loyalty-based offers for cardholders, has acquired two U.K. companies to bolster the analytics side of its platform. In a transaction consisting of “undisclosed fees and stock”, the company has purchased Inspired Analytics, which offers analytical consultancy services — specifically to help design and build production analytics solutions — and Elucidata, which also provides consultancy and specialises in “data strategy and high-complexity, regulated data implementations”. As a result, Jim Jeffrey, Inspired Analytics’ Director of Analytics, will become ERN’s Analytics Director, and James Baldwin, Managing Director of Elucidata, will become Managing Director of ERN’s Analytical Consulting Division. If it smells like an acqui-hire, it probably is an acqui-hire, though a spokesperson for ERN stressed that the acquisitions are for both the tech and the teams of the respective companies. Meanwhile, ERN is announcing yet another round of seed funding. This time it amounts to a further $1 million, once again from unnamed high-net worth individuals, all of whom have previously helped finance the startup to the tune of $3.6 million. This brings the total raised by the company before it’s shipped a commercial product to $4.6 million. As we’ve noted before, Big Data costs big money, not least when you’re gunning to be a major player in the FinTech/transactional data space. However, my understanding is that ERN is on the cusp of announcing its first commercial customer after trials with a number of “household names”. More on that should follow shortly. ERN’s analytics platform, dubbed “Looop”, enables banks (or more specifically, card issuers) and participating merchants to boost customer loyalty by creating new products and offers based on the analysis of their card transactions. The idea is that by drilling into the Big Data around a customer’s transactional history — after they’ve opted in, of course — individually-tailored offers can be pushed to their smartphone via the Looop app, in the form of an e-coupon redeemable in-store. In addition to insights gained through mining customers’ transactional Big Data, the targeting of offers can also be geo-fenced e.g. only push an offer when a customer who has previously bought a dress is within a certain radius of the participating store. The new management personnel picked up via the two acquisitions being announced today are definitely a good fit for ERN’s mission, and presumably should provide in-roads to exactly the type of B2B customers that the young startup is hoping to sign up. Inspired Analytics’ Jeffrey is the former Head of Data Innovation at Barclaycard Freedom, where he developed “market basket analysis algorithms” for retailers, and was also a Business Partner within Lloyds Banking Group’s Customer Insight area. Elucidata’s Baldwin also has ties with Barlaycard as former Head of B2B Targeting where he developed the analytics platform for the bank’s cardholder offers programme.

Loading ERN Inc collaborators
Loading ERN Inc collaborators