Data buddies: bridging the gap between data analysts and non-technical team members
Dietmar Böhmer joined Tyme seven years ago and he has been leading the data and analytics function across the group, which includes TymeBank in South Africa and the newly launched GoTyme in the Philippines. He has led lending, data science, machine learning, and big data teams in banking for close to two decades and has lectured in the actuarial field prior to that.
TKI: What are the key skills that a Chief Analytics Officer should possess in the context of your role at Tyme?
Dietmar: Firstly, the ability to embrace and adapt to change is critical, as change is the only constant. Secondly, a strategic mindset and a strong interest in new developments and trends in technology and machine learning are necessary to ensure the organization stays ahead of the curve. Effective communication skills are also essential to explain the strategic direction and convey complex data concepts and insights to non-technical stakeholders. Lastly, a willingness to be hands-on and take the initiative to get the job done is important in a start-up environment where there’s always more work than people available to do it.
TKI: How do you see AI impacting the banking industry in the next five years, and how is Tyme preparing for these changes?
Dietmar: The banking industry, like all other industries, will be significantly impacted by the rapid advancement of AI. While banks have already been utilizing AI and ML models for credit risk, fraud, Anti-Money Laundering (AML), and cross-sell optimization, there’s a greater focus on customer engagement and customer service. AI will play a significant role in interacting with staff and customers, unlocking unprecedented opportunities to improve the efficiency of staff at all levels. We are constantly reviewing our architecture to ensure that we have the correct data disciples, the ability to ubiquitously consume AI models, the appropriate data and AI governance, and the capacity to train the board on the latest capabilities and opportunities of the most relevant advancements.
TKI: In your opinion, what is the biggest challenge facing the adoption of AI for data analytics within the banking industry?
Dietmar: The primary focus of building and running a bank is to ensure its resilience and readiness. The top priority is to enable customers to always transact across all channels. However, this means many incumbent banks’ banking systems weren’t designed to seamlessly embed AI. Additionally, the highly regulated nature of the banking industry inherently creates a culture of risk aversion, relative to other industries with less oversight, leading to longer lead times for adopting new and disruptive technologies.
In today’s data-driven world, data analysts and non-technical team members must work together seamlessly to unlock the full potential of data. However, bridging the gap between these two groups can be a challenge. In this interview, Tyme’s Chief Analytics Officer, Dietmar Böhmer explores the importance of this type of collaboration and offers practical strategies to improve communication and understanding between these two critical parts of the workforce.
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