Name: How to Reduce Financial Risk with The Right Data
Start: 2020-11-10T17:00:00Z
End: 2020-11-10T17:00:41.000Z
Location: BrightTALK
Rating: 0

Explorium transforms the way organizations find and acquire data for their machine learning (ML) models. The platform removes the need to spend significant resources and time finding data that works by offering instant access to thousands of relevant external data sources and distilling the most impactful features for each business use case. A unique combination of capabilities and an innovative approach to data acquisition make Explorium’s platform the first of its kind in finding external data. Visit www.explorium.ai to learn more.

Gartner predicts that “by 2023, more than 33% of large organizations will have analysts practicing decision intelligence, including decision modeling”. In 2020, data analytics has evolved together with AI to produce more accurate predictions and educated suggestions. Join Eric Topham and a panel of industry experts and thought leaders to find out how data and analytics will transform human-machine relationships.

This month's episode of The Business Intelligence Report will look at the defining data and analytics trends to watch in 2021. Some of the topics to be covered during this session will include:
- The growing importance of external data
- Trends of how organizations are finding and using external data
- How data visualization enriches analytics and helps reveal correlations
- The evolution of dashboards. Where are we now and where are we headed?
- Data visualization in real-time for timely, actionable insights
- Visual analytics use cases. Building a data narrative to achieve business results.

Panelists:
- Mark Balkenende, Senior Director, Product Marketing at Matillion
- Dedy Kredo, VP of Customer-Facing Data Science at Explorium
- William McKnight, President of McKnight Consulting Group

This episode is part of The Business Intelligence Report original series with Eric Topham, Co-Founder & Data Science Director at The Data Analysis Bureau. 

We welcome viewer participation and questions during this interactive panel session.

Data & Analytics 2021: Defining Trends and Trajectories

ECommerce conversion is all about customer data. Having the right data means higher conversion rates, better segmentation, optimized ad spend, and more repeat purchases.

Today, when most businesses have been forced to move online, marketing and analytics leaders need to take their data to the next level, run predictive models, and stay ahead of their competition.

Join this webinar to learn three primary eCommerce use cases that data science tackles and how you can leverage them even if you're not a data scientist. This session is perfect for senior risk officers, and fraud analysts. Our presenters Gali Michaeli, head of customer success EMEA, and Eilon Baer, Explorium expert data scientist, will dive deep into:
* Customer lifetime value optimization
* Customer segmentation
* Repeat buyers

Boost ECommerce Conversions Using Predictive Models (Without a Data Scientist)

BI helps organizations across industries make sense of their data, but it still expects you to do the heavy lifting when it comes to finding insights. Building predictive models that can cut down your decision time and offer better insights is a must, but achieving them is not trivial.

Join Anthony Franklin, PhD., Senior AI Engineer at Microsoft and Fanalytical Co-Founder, and Zach Booth, Director of Business Development and Global Partnerships at Explorium, for a live conversation about the best practices, based on their experience with customers and partners, for transitioning to AI.

Register for this "Ask the Expert" session on Wednesday, August 19, at 12pm EST to learn:
* Why you should transition to AI
* The prerequisites required to make this transition run smoothly
* How Fanalytical helps transform sports fan clubs through AI

Keep Your Eye on the Ball: Best Practices For Transforming BI to AI

Lenders rely on machine learning models using accurate data for risk assessment. However, with COVID-19 rendering this once reliable data useless, time-intensive manual processing might seem like the only way forward. Or is it?

Register today to attend a live webinar on how augmented data discovery and timely risk signals can save you hours of manual processing. Join industry experts Maor Shlomo, Explorium CEO, and Victor Ghadban, AI/ML Evangelist and Chief Field Data Scientist, to better understand:
* How to stop manual processing and return to automated decision making
* Where and how to access timely and accurate data to mitigate risk 
* How to switch back to using machine learning models

Our panelists will also discuss how combining a wide variety of trusted industry-standard data sources and proprietary algorithms can provide you with reliable insights for:
* Company signals - including online and offline revenue channels and the company's response to COVID-19
* Industry signals - automatically identify a company's industry and consider the impact of COVID-19
* Location signals - measure vulnerability, response, and footfall traffic by location

How Risk Managers Use Real-Time Data to Restore Confidence in Predictive Models

Risk officers and analysts across financial services companies and banks realize that risk modeling in 2020 requires better data. Even the most sophisticated machine learning models are insufficient without the most relevant risk signals pulled from external data sources.

On Tuesday, November 10 at 12 pm EST, join Alvin Huang, business development lead for capital markets at Amazon Web Services (AWS), and Rishi Singh, Explorium VP customer success, as they discuss:

- The new challenges of risk modeling and how to increase model accuracy
- An innovative strategy for controlling risk by gaining the broadest insight possible on potential lendees
- The benefits of connecting to external data to accelerate results and time to market

How to Reduce Financial Risk with The Right Data

Data Science

Financial Risk Management

Machine Learning

Alternative Data

Predictive Analytics

Risk Signals

Data Discovery

Risk Modeling

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How to Reduce Financial Risk with The Right Data

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