Sep 23–26, 2019

Findata Day

Tuesday, September 24, 2019 | Location: 1A 08

Sponsored by: Sponsor by GridGain

Finance is information. From analyzing risk and detecting fraud to predicting payments and improving customer experience, data technologies are transforming the financial industry. And we're diving deep into this change with a new day of data-meets-finance talks, tailored for Strata Data Conference events in the world's financial hubs. Bringing together bankers, analysts, entrepreneurs, financiers, and technologists, it's a can't-miss day for anyone working in the financial sector.

Tuesday, 09/24/2019

9:00am

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9:00am–9:05am Tuesday, 09/24/2019
Tutorial
Secondary topics:  Financial Services
Alistair Croll (Solve For Interesting)
Alistair Croll, findata host and the Strata Data Conference program chair, welcomes you to the day-long tutorial. Read more.

9:05am

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9:05am–9:30am Tuesday, 09/24/2019
Findata
Case studies
Jennifer Yang (Wells Fargo ECS)
Jennifer Yang discusses a use case that demonstrates how to use machine learning techniques in the data quality management space in the financial industry. You'll discover the results of applying various machine learning techniques in the four most commonly defined data validation categories and learn approaches to operationalize the machine learning data quality management solution. Read more.

9:30am

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9:30am–10:00am Tuesday, 09/24/2019
Findata
Nitzan Mekel-Bobrov (Capital One)
Nitzan Mekel-Bobrov presents a framework for how enterprises can use real-time machine learning to provide long-term, recurring relationships with customers, with a focus on leveraging longitudinal omnichannel context, enhanced capabilities able to infer state from this new scale of data, and real-time personalization based on streaming data ecosystems. Read more.

10:00am

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10:00am–10:30am Tuesday, 09/24/2019
Findata
Viridiana Lourdes explains how banks and financial enterprises can adopt and integrate actual risk models with existing systems to enhance the performance and operational efficiency of the financial crimes organization. Join in to learn how actual risk models can reduce segmentation noise, utilize unlabeled transactional data, and spot unusual behavior more effectively. Read more.

10:30am

10:30am–11:00am Tuesday, 09/24/2019
Morning break sponsored by Microsoft (30m)

11:00am

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11:00am–11:30am Tuesday, 09/24/2019
Brian Lynch (TD Bank Group)
As data has become heavily ingrained in corporate strategy, businesses have been challenged to build and retain team with data science capabilities. Brian Lynch walks you through some of the materials he's used to grow, build, and maintain data-driven teams with diverse skill sets ranging from reporting and insights to data sciences. Read more.

11:30am

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11:30am–12:00pm Tuesday, 09/24/2019
Dan Barker (RSA Security)
Sometimes if you build it, no one comes. What do you do if your data and tools aren't being leveraged as expected? It's a massive shift in thinking, but the payoff can be even bigger. Dan Barker explains how he and his team took the National Association of Insurance Commissioners, a 150-year-old nonprofit, into the data age and how you can do it too. Read more.

12:00pm

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12:00pm–12:30pm Tuesday, 09/24/2019
Rochelle March (Trucost)
Trucost's Rochelle March is migrating a product that quantitatively measures company performance on UN Sustainable Development Goals from Excel to Python. Her team cut multiday workflows to a few hours, delivering rich 27-page interactive reports. Join in to learn modern techniques to design, build, and deploy a data visualization and reporting framework in your organization. Read more.

12:30pm

12:30pm–1:30pm Tuesday, 09/24/2019
Lunch (1h)

1:30pm

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1:30pm–2:00pm Tuesday, 09/24/2019
Catherine Gu (Stanford University)
With the emergence of cryptoeconomy, there is a real demand for an alternative form of money. Major cryptocurrencies such as Bitcoin and Ethereum have thus far failed to achieve mass adoption. Catherine Gu examines the paradigm of algorithmic design of stablecoins, focusing on incentive structure and decentralized governance, to evaluate the role of stablecoin as a future medium of exchange. Read more.

2:00pm

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2:00pm–2:30pm Tuesday, 09/24/2019
Findata
Peter Swartz (Altana Trade)
Peter Swartz explains how Altana uses natural language processing, machine learning, and network analysis to construct the world’s most comprehensive knowledge graph of the global trade and ownership network, connect this knowledge graph with customer data across governments and the private sector, and generate actionable insight from the combined data. Read more.

3:00pm

3:00pm–3:30pm Tuesday, 09/24/2019
Afternoon break sponsored by Dataiku (30m)

3:30pm

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3:30pm–4:00pm Tuesday, 09/24/2019
Karan Jaswal (Cinchy)
After 40 years of apps, leading financial services providers are realizing that building or buying an application for every use case has become a major threat to their agility, profitability, and data protection. Join Karan Jaswal for an introduction to data collaboration, the radical new paradigm that's the single biggest shift in technology delivery since the 1970s. Read more.

4:00pm

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4:00pm–4:30pm Tuesday, 09/24/2019
Findata
Case studies
Secondary topics:  Financial Services
Moto Tohda (Tokyo Century (USA))
Tokyo Century was ready for a change. Credit risk decisions were taking too long and the home office was taking notice. The company needed a full stack data solution to increase the speed of loan authorizations, and it needed it quickly. Moto Tohda explains how Tokyo Century put data at the center of its credit risk decision making and removed institutional knowledge from the process. Read more.

4:30pm

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4:30pm–5:00pm Tuesday, 09/24/2019
Secondary topics:  Financial Services
TBC Bank recently started doing analytics in a new way: embedding data scientists directly in the businesses they're working for, along with staff dedicated to connecting them to data and business. It also made sure all projects had clear measures of success. Mikheil Nadareishvili explains how this shift unlocked value—in one project, helping improve the profit of a major loan product four-fold. Read more.

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