Elanev

elanev® provides simple to apply comprehensive data and AI products that will increase your profit and reduce your risks and costs. • Increase your right customer contacts to increase efficiency and reduce costs, risks and (IFRS9) provisions• Quickly identify financial vulnerable customers and reduce risk• Inform the customer journey and reduce your costs by using our customer behaviour scores• Quantify your operational, conduct and IT risks to ensure you are adequately capitalised and insured• Instantly value defaulted loan portfolios and optimise for increased profitAll without the need to share personal identifiable customer data and priced as a percentage of demonstrated gain. Delivered through a SaaS approach elanev products avoid the need for long running expensive IT projects, we deploy using simple low frequency file transfers to our cloud based architecture. And by purposely not using personal identifiable information your compliance department will be happy. Yes, it is possible. Our suite of products include: • Customer contact optimisation (works on new to attempt accounts! ) • Customer resilience / Financial vulnerability screening • Customer propensity (e. g. propensity for payment) • Operational risk modelling • Predictive MI for customer contact operations • Daily decisioning for customer contact operations • Debt portfolio purchase pricing and valuation • Debt portfolio purchase price optimisation • Debt portfolio seller /investor price evaluation • Conduct risk propensity analytics • Credit concentration risk calculation • Cyber risk modelling • Extended recovery curve valuationMeaningful results are ensured by our considered use of statistical procedures, machine learning (aka AI) and other modelling techniques such as Monte-Carlo methods. And as time is of the essence we use the latest automation techniques (aka RPA) and parallelisation to return these promptly.
Social Link - Twitter: https://twitter.com/elanev_UK
Social Link - Linkedin: http://www. linkedin.com/company /elanev
Employee Count: 4
Keywords: data science