Democratizing Data and AI in Finserv: DAIS 2021 Takeaways

For financial services providers, driving business forward with data is a longstanding practice—but as machine learning (ML) and artificial intelligence (AI) technologies improve, understanding the potential for data-based roadblocks is key. This year’s Data and AI Summit (DAIS) hosted over global attendees across more than 200 sessions, and highlighted leaders from ABN AMRO, Intuit, Capital […]

For financial services providers, driving business forward with data is a longstanding practice—but as machine learning (ML) and artificial intelligence (AI) technologies improve, understanding the potential for data-based roadblocks is key.

This year’s Data and AI Summit (DAIS) hosted over global attendees across more than 200 sessions, and highlighted leaders from ABN AMRO, Intuit, Capital One, S&P Global and Northwestern Mutual as they discussed how to unlock the full capabilities of data, ML and AI across all of finance and financial tech services.

Speakers shared their perspectives on the biggest issues facing financial institutions today, including data sharing and openness, cloud migration and Big Data management, as well as  how critical data’s role in shaping strategic decision-making. Most of our sessions will be available on-demand, but to help you navigate the content, here’s a rundown of what’s top-of-mind for Financial Services data teams and leaders.

Keynote & Experts Panel: The Biggest Data Challenges in FinServ

Kicking off the Financial Services sessions with an inspiring keynote, Northwestern Mutual’s Chief Data Officer Don Vu dug into historical data hurdles like fragmented information, governance and blind spots in the user experience. He detailed Northwestern Insurance’s digital transformation and how it used Databricks to modernize their data infrastructure, unify all of their data across multiple system inputs, and gain a complete, 360-degree view of their customers. This transformation allows them to align their data extraction and analysis strategies with the overarching goals of the business, leading to the development of innovative new features and greatly enhancing their integrated digital experience. Today, data is the engine powering every business decision.

Next on the virtual DAIS stage was a panel of industry experts moderated by Junta Nakai, Financial Services Industry Leader & Regional Vice President at Databricks. Panelists discussed their own journeys with data and AI, including common challenges they’ve faced and advice on implementing platforms and tools to support data ingestion and analysis at scale. Here’s what they covered:

The importance of openness

Nakai from Databricks opened the discussion with the open banking initiative and how, with the help of Databricks’ Lakehouse Platform, companies in the financial sector can “take all the transactional data, third party data, alternate data sources, such as social media and different types of data that come in multiple forms, and land them in one place so companies can do data science and machine learning from a single source of truth.”

ABN AMRO’s Head of Data Engineering Marcel Kramer touched on the importance of openness in data systems and how beneficial collaboration between data scientists and engineers can be to create seamless data handovers in the same environment.

With the Databricks Lakehouse Platform, they’re able to deliver new solutions 10x faster than before and with pinpoint accuracy — something their legacy infrastructure was unable to accomplish A lakehouse architecture enables faster, more reliable data pipelines to feed complete, accurate data into their ML models, improving downstream financial analytics and overall collaboration.

“Openness in data systems helps data scientists and engineers collaborate better with seamless handovers in the same environment,” said Kramer. Additionally, based on the transactions and patterns, ABN AMRO could identify patterns of human trafficking being perpetrated based on just the sheer combination of transactions — showing how data can be used for human rights and socialgood.

Innovate with the customer in mind

Intuit Principal Engineer Bharath Ramarathinam spoke about the necessity of openness and open source software, detailing how they accelerated Intuit’s data transformation by allowing them to leverage multiple partners and their community to achieve business goals. He also mentioned how his team “designs to delight customers, and data is critical to understanding what users want from your business”.

One common thread we often hear from customers is the growing importance of driving social and environmental impact. M&G’s Head of ESG & Research Transformation Priyank Patwa discussed the environmental impact of investments and the importance of quantifying qualitative environmental, social and governance (ESG) information to develop insights and how using enhanced AI and ML makes it possible. Nakai exclaimed how companies can “literally help to curb emissions through investments and data” by quantifying their ESG efforts.

Databricks partner KX Data is the world’s fastest streaming analytics platform and integrates seamlessly with the Databricks Lakehouse Platform for high-volume, continuous, real-time stock market intelligence. Their Managing Director, Conor Twomey, discussed how fast, real-time ML-powered insights are shaping the way people invest and working with “continuous intelligence is the smartest way to maintain value for customers”.

Main takeaways and moving forward

In addition to sharing anecdotal learnings, speakers offered a few core, overarching insights regarding the need for companies to use data and AI —both to minimize risk and create more engaging customer experiences, as well as  to drive future growth.

Openness in data is mission critical. Streamlining collaboration across different teams and entities accelerates transformation and is vital to the accuracy and depth of your data.

Data transformation depends on cross-functional engagement. Getting stakeholder approval and engagement across business units is important to data transformation; those involved are more invested when benefits are clear and outcomes align with individual goals.

We haven’t seen anything yet. More and more companies are leveraging data, ML and AI for a variety of tangible use cases in financial tech services. These technologies deliver exponential value in both information and profits, and experts believe we’re only just beginning to tap into the potential of data platforms.

Click below to watch the DAIS Financial Services sessions in full, and explore technical sessions and demos on-demand.

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Source: Databricks