What is “Seamless Blended Learning” in the Metaverse?

Wilma Hartenfels: “Today I’m talking to Philippe Séjalon. Together with his brother Patrice and another founder, Marion, Philippe founded Ingage several years ago. Ingage brings innovative and immersive training experiences to the still quite traditional insurance industry.

Our interview (in English, with an introduction in German) is about the potential of the metaverse as a new stage of development of the Internet. Philippe explains how he brings together various disruptive technologies such as VR, AR, Blockchain, NFTs and crypto in a Seamless Learning approach to increase learner engagement.”

Listen to this podcast!

(see the Wilma Hartenfels’podcast

Read More

Can you paint this too? ;-)

Have you ever wished you had a talented designer all the time with you to help you create learning content?

Think about this A.I. from NVidia! You are welcome to try it

#artificialintelligence #contentcreation #onlinelearning #teacher #paint #talent

Read More

Do you still think that you are smarter than an AI? 🧐

Artificial intelligence (AI) can now solve grade-school math problems and, more impressively, university-level math problems.    

This AI is based on a language model called Codex that is able to write computer programs. It gets additional guidance in the form of being told what topic the problem is about, what code library to use, and what the definition of mathematical concepts is. It is also able to generate new math problems. According to human evaluators, it is almost as good as humans at solving math problems.   

What if I told you that AI wrote this text?   

AI can even help create online courses for insurance for example!   

#singularity #artificialintelligence #ai #onlinecourses #coursecreators #coursewizard 

 

 

Read More

Tecnología al servicio de los suscriptores de Líneas Comerciales

Guest Author: Juan D’Alessandro

Siguiendo con nuestro ultimo post sobre el impacto de la inteligencia artificial en la industria de seguros hoy vamos a hablar de seguros comerciales. Con agrado, vemos cada vez mas iniciativas, proyectos de transformación integral y capital fluyendo a Insurtechs enfocadas en Líneas Comerciales. Años de mercado blando han puesto mucha presión en los equipos de suscripción. Ajustes, recortes y reestructuraciones que han sobrecargado el día a día de los suscriptores al punto de comprometer su nivel de servicio a los brokers y clientes.

Desde RiskTech, trabajamos en distintas iniciativas que se adaptan a las necesidades y requerimientos de nuestros clientes como son:

. Triagge en base al apetito de la compañía al momento de la recepción a fin de definir prioridades y atender los casos mas importantes.

. Alertas de parámetros o exposiciones en base a autoridad o pautas de suscripción que se generan en tiempo real al momento de cargar la cuenta.

. Generar de forma automática la mayor cantidad de información posible. Tanto de fuentes internas (pago de prima, siniestralidad, otras líneas activas, etc.) como externas (google maps, NatCat, Nathan, noticias de actualidad).

. Estimación de la siniestralidad potencial a nivel cuenta y portafolio en base a datos históricos.

Estas iniciativas apuntan a liberar a los técnicos de tareas repetitivas para poder enfocarse en actividades de estrategia, desarrollo de negocios y suscripción pura impactando de forma positiva el resultado de la compañía.

Read More

Utilización de Inteligencia Artificial para lograr eficiencias en el proceso de suscripción de líneas comerciales.

Guest Author: Juan D’Alessandro

Las Compañías de Seguro comienzan a poner los datos a trabajar para ofrecer a sus clientes productos innovadores. La ciencia de los datos, impulsa la automatización de procesos repetitivos y provee más conocimiento para, al final del día, ofrecer un servicio personalizado a los clientes aumentando su satisfacción y relación con la marca.

Para empezar, vamos a repasar que es la Inteligencia Artificial. En 1956, John McCarthy acuñó la expresión «inteligencia artificial» como «la ciencia e ingenio de hacer máquinas inteligentes, especialmente programas de cómputos que reúne características y comportamientos asimilables al de la inteligencia humana. Una definición mas actual que se adapta a la realidad es la siguiente: la capacidad de un sistema para interpretar correctamente datos externos, para aprender de dichos datos y emplear esos conocimientos para lograr tareas y metas concretas a través de la adaptación flexible.

Sin duda, adoptar una estrategia integral sobre el manejo de la información es vital para garantizar el correcto funcionamiento de los modelos desarrollados y su resultado. Este es el principal desafío de las compañías. Recolección, transformación, clasificación y almacenamiento es esencial para poner en practica estos modelos. El origen de los datos pueden ser fuentes externas como redes sociales o internas (formularios, histórico de siniestros y primas).

Algunos casos de impacto de esta tecnología en la industria:

  • Reducir el tiempo dedicado a tareas repetitivas. Estas tareas simples que ocupan un gran porcentaje del tiempo de los equipos de Suscripción, Operaciones, Siniestros pueden ser realizadas por modelos entrenados.
  • Ofrecer un servicio personalizado a sus clientes y corredores anticipándose a sus necesidades. Conocer mejor a los clientes.
  • Desarrollar nuevos canales de venta utilizando el IoT
  • Mejorar el resultado de la compañía implementando modelos de detección de siniestros fraudulentos. 

Estos son solo algunos ejemplos propios de la industria. También existen productos ya operativos en otras industrias (fintech, ecommerce) que se están adoptando como Chatbots, Manejo de recursos humanos, etc.

Read More

Insurance 2030

McKinsey report

The industry is on the verge of a seismic, tech-driven shift. A focus on four areas can position carriers to embrace this change.

Welcome to the future of insurance, as seen through the eyes of Scott, a customer in the year 2030. His digital personal assistant orders him an autonomous vehicle for a meeting across town. Upon hopping into the arriving car, Scott decides he wants to drive today and moves the car into “active” mode. Scott’s personal assistant maps out a potential route and shares it with his mobility insurer, which immediately responds with an alternate route that has a much lower likelihood of accidents and auto damage as well as the calculated adjustment to his monthly premium. Scott’s assistant notifies him that his mobility insurance premium will increase by 4 to 8 percent based on the route he selects and the volume and distribution of other cars on the road. It also alerts him that his life insurance policy, which is now priced on a “pay-as-you-live” basis, will increase by 2 percent for this quarter. The additional amounts are automatically debited from his bank account.

When Scott pulls into his destination’s parking lot, his car bumps into one of several parking signs. As soon as the car stops moving, its internal diagnostics determine the extent of the damage. His personal assistant instructs him to take three pictures of the front right bumper area and two of the surroundings. By the time Scott gets back to the driver’s seat, the screen on the dash informs him of the damage, confirms the claim has been approved, and that a mobile response drone has been dispatched to the lot for inspection. If the vehicle is drivable, it may be directed to the nearest in-network garage for repair after a replacement vehicle arrives.

While this scenario may seem beyond the horizon, such integrated user stories will emerge across all lines of insurance with increasing frequency over the next decade. In fact, all the technologies required above already exist, and many are available to consumers. With the new wave of deep learning techniques, such as convolutional neural networks,1 artificial intelligence (AI) has the potential to live up to its promise of mimicking the perception, reasoning, learning, and problem solving of the human mind (Exhibit 1). In this evolution, insurance will shift from its current state of “detect and repair” to “predict and prevent,” transforming every aspect of the industry in the process. The pace of change will also accelerate as brokers, consumers, financial intermediaries, insurers, and suppliers become more adept at using advanced technologies to enhance decision making and productivity, lower costs, and optimize the customer experience.

Read More

Jornada de Seguros

The Insurance Day in Buenos Aires

The Insurance Day took place in Argentina this year on May 22.

The key topic were digitization, disruption, Artificial Intelligence and Big Data.

As the behavioural economist Dan Ariely once tweeted, “Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.”

 

 

 

Read More
Send