Realizing the promise of AI in Financial Services for exceptional customer experience

How can we take a step back from our current processes and improve them with new Machine Learning tools, or just clever reporting? In this session, our in-house solutions expert Alyson Kelley discussed how to monetize your current processes by: - Understanding current trends in data analytics - Creating strategic alliances within your organization - Taking advantage of partnerships with current vendors

Data science and AI are game-changing technologies for engineering and manufacturing companies. To embrace the need of today and the future for self-service data science and analytics in manufacturing, we need more data engineers to make this all possible.
At Altair, we envision a future where engineers are well equipped to apply data science techniques to derive powerful predictive analysis that transforms the way they operate. There are a plethora of applications for data science in manufacturing - from product design, supply chain optimization, and fault prediction, and preventative maintenance to demand forecasting, and quality assurance. By bridging the gap between the data scientist and engineering roles, your organization can breakdown data silos and extract actionable insights to drive real business value.
The movement has just started. Watch our on-demand webinar to learn more.

In this webinar, we highlighted challenges and opportunities in RPA strategy, investigated the current state of RPA across industries, and mapped out ways in which Altair Monarch can be a complementary solution to current and future RPA deployments. Stephen Smay, Altair Solution Specialist Director and expert in RPA troubleshooting, discussed the questions businesses working with RPA need to ask in 2021: -Whether you’re implementing or integrating RPA into your systems, careful consideration of the pre- and post- processing gaps in data preparation/formatting is crucial. Where are some common areas to find efficiency? -What are the key things to expect in the world of RPA in the next year? -What are the most common challenges with RPA today?

Gartner recently released their  'Top 10 Data & Analytics Trends for 2020' where they stated that "the collision of data and analytics will increase interaction and collaboration between historically separate data and analytics roles. This impacts not only the technologies and capabilities provided, but also the people and processes that support and use them. The spectrum of roles will extend from traditional data and analytics to information explorer and citizen developer as examples". With Forbes predicting that there will be a shortage of at least 250,000 data scientists in the US alone by 2024, how will our data-driven enterprises survive? Should we empower citizen data scientists and embody a data democratisation approach or is there a better way to optimise our data science teams? Join us as we discuss  'The Next Generation Data Scientist’  with our expert panel. Discussion Points: What type of person is the Next Generation Data Scientist? How can organisations develop these highly prized people? Can you explain one of the most advanced data science projects in your organisation and some of the stumbling blocks you have encountered along the way? What do you see as the most pressing trend in data science? If you had to boil it down to one sentence, what is the most important thing organisations should do to stay ahead of the competition?

Post COVID-19 and as we navigate our new normal - banking and lending will undoubtedly be transformed. As the economic fallout spreads, financial firms are grappling with a major influx of relief requests from consumer and business customers. Our panelists discuss whether modern technology, advanced analytics, and a data-driven approach can hold the keys to ensuring banks and fintech leaders continue to scale despite this rapidly evolving credit crisis.

Featuring an enviable lineup including; Frederic de Sibert, Global Head of Investment Banking Services Strategists at Goldman Sachs, Paul Downes, COO at Autovista Group, Kerem Talih, General Manager/CFO at Doğuş Otomotiv and Dr. Mamdouh Refaat, Chief Data Scientist at Altair. This hour-long webinar is full of insight, guidance, and tips from global businesses that are at various stages of their Data & Analytics journeys.

Hear from a prestigious panel of experts including David Huguet, Data Lead at SNCF, plus Martijn van Baardwijk, CFO - Continental Europe at Inchcape plc.

Augmented Analytics is being touted as the next frontier in AI’s Evolution with Gartner defining it as “the use of enabling technologies such as machine learning and AI to assist with data preparation, insight generation, and insight explanation to augment how people explore and analyze data”.

Fraud mitigation requires technologies and business processes that are flexible in their construct, easily understood by all who are involved in fraud prevention, and are agile enough to adapt to new attacks without needing to be rebuilt from scratch.
Data from all business units and functional silos must be included to create a holistic view of the success of fraud operations. The insight found in classical auditing techniques and predictive machine learning models, combined with the expertise of fraud analysts can foster an evidenced-based methodology to quickly respond to new financial crimes.