VIDEO | Data4Good - Decent Growth & Economic Growth Award Winner: Neighborhood Trust + IBM

(US and Canada) CDO Magazine and EDM Council congratulate Neighborhood Trust and IBM for winning the inaugural 2022 Data4Good Award in the Decent Growth & Economic Growth category. Justine Zinkin, Neighborhood Trust Financial Partners CEO, along with Chris Konarski, VP, Client Engineering IBM, and Kush Varshney, Manager at IBM Thomas J. Watson Research Center, speak with Eric Bigeisen, Senior Advisor and Head of ESG working group, EDM council, in a video interview about leveraging data for economic growth, AI transforming businesses, ProtoDash, their pivotal areas of work, data for a better society, and the importance of data governance and stewardship.

Zinkin begins the discussion by introducing Neighborhood Trust as a 25-year-old nonprofit organization that provides financial coaching and products to enable workers' financial security and empowerment. Zinkin notes that the trust financial coaches have built with clients through the data platform has helped the organization gather rich data about workers’ financial lives. She adds that the company focuses on liberating working families from relying on expensive debt.

Through data, continues Zinkin, the organization motivates employers to invest in workers’ financial well-being and fintechs to design products to help workers avoid insolvency. She believes that a better application of their data can help workers control finances and inevitably lead to market change.

Regarding IBM, Konarski shares that the company takes a human-centered approach to AI and focuses on protecting all data. He adds that IBM keeps ethical principles at the core of AI technology and fosters it for the benefit of many. Konarski states that the data IBM shared with Neighborhood Trust focused on transparency to explain high-impact factors like users’ likelihood of experiencing financial distress. He also reveals that a part of this solution led to an IBM research algorithm called ProtoDash, which allowed the identification of prototypical users.

Next, Zinkin pinpoints value-driven work carried out by Neighborhood Trust:

• Work with IBM’s data-science-for-good team to analyze credit reports, debt data, and client bank transaction data to create predictive analytics.
• Identify when clients are at risk of taking on debt and intervene in real-time.
• Create a machine learning pipeline with the ability to predict the probability of a client entering financial distress.

She concurs that ProtoDash has proven invaluable in informing marketing strategies and the ability to design for client segments in a high-impact way. As a long-term organizational value, Zinkin mentions receiving free access to IBM’s cloud and visualization software, which enabled the company to operationalize data visualization.

Highlighting IBM, Konarski mentions that the organization commits to helping clients worldwide solve their biggest challenges.

Next, discussing data for the betterment of society, Zinkin mentions launching worker insights that surface the data and company insights in all aspects of financial coaching. She points out that by focusing on clients' experiences, the company is building a new data mining system. To deliver more inclusive and productive financial solutions, IBM expects to harness this data to create feedback loops for financial institutions, HR departments, and other benefit providers. Zinkin affirms that worker voice must be at the forefront of creating a more equitable financial and economic system.

According to Konarski, IBM continues to work with clients to drive that social impact. He adds that working with Neighborhood Trust has shown the potential acceleration in data-driven decisions, incorporation of explainability, agility, and data science for social good.

Konarski further states that data stewardship is a privilege to a leader, but it is also a responsibility to ensure that the technology deployed is trustworthy. He notes that transparency, data stewardship, and data governance are all built into IBM’s culture.

For Zinkin, the critical piece to governance lies in clients feeling ownership over their data. She believes that working with IBM has positively impacted its culture and operations.

In conclusion, Konarski stresses the need for good data and AI governance in every way. The massive changes happening result from organizations not only leveraging the data but also protecting it.