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When assessing consumer loan default, banks traditionally look at payment history, credit score and overall assets and liabilities to predict likelihood of repayment. However, there is an untapped potential to incorporate transactional and saving patterns into the equation. Join the Data Science and AI Elite team to discuss how you can leverage transaction data to enhance your predictions. During our session, we will debut our new Loan Default Industry Accelerator on Cloud Pak for Data to help your bank get a head start in mitigating default.
Kristen is a Data Scientist & Financial Services Industry Lead from IBM’s Data Science and AI Elite team (DSE). Based In New York City, Kristen has partnered with clients on their journey to AI across multiple industries, including banking, insurance, industrial, automotive, and health care. Her cross-industry experience allows her to bring a fresh perspective and lessons learned from other industries to Financial Services. Kristen engages daily with clients to identify business opportunities for innovation, accelerate time to value, and help onboard those new to machine learning and AI. Kristen is passionate about discovering data insights, solving challenging problems, and promoting women in STEM.
Vaisakhi is a Data Scientist with IBM’s Data Science and AI Elite team (DSE), based out of New York. She holds a Master’s degree in Information Management, specializing in Data Science and Business Intelligence and has over five years of industry expertise in machine learning, deep learning, data mining, and data engineering. Vaisakhi has worked with clients across multiple industries including oil and gas, communications, healthcare, distribution and banking; helping them solve their business problems with effective solutions using data science. When she's not coding, she can be found volunteering in outreach STEM activities.
Jessica is part of the Data Science Apprenticeship program at IBM. Over the last 20 months she has leveraged her background in neuroscience and mathematics to develop her skills as a data scientist. Her affinity for problem solving and multitasking has launched her skills from computer science 101 to building and deploying machine learning models within a few months. Jessica has met with clients as well as engaged in internal revenue driving projects. She looks forward to continuing her journey within IBM.
Kevin Potter is a Data Scientist with the Cloud Pak Acceleration Team based out of New York. Prior to IBM Kevin spent five years as a banking and insurance analyst, helping internal clients leverage AI to meet business needs. Kevin’s current responsibilities include client enablement and adoption on the Cloud Pak for Data platform with clients in all phases of their AI journey. Kevin has works with clients in financial services as well as consumer goods, and ecommerce to build and deploy their machine learning pipelines on the Cloud Pak for Data platform.