Lisa Christofilos, chief information officer of data and analytics at BMO, recently sat down with Bank Automation News to discuss data and analytics at the bank-level, along with best practices for ensuring data security. Christofilos helps lead data engineering, analytics and architecture efforts for the $805.9 billion bank. What follows is an edited version of the conversation:

Bank Automation News: Can you discuss some emerging technologies that intrigue you?

Lisa Christofilos: There’s no doubt that we’re seeing a lot of fascinating technology emerging at an incredible pace — from robotics to virtual reality. What’s intriguing is the way we’re using technology for personal and business use. For instance, the effective use of data and analytics can change the trajectory of a business; you can harness the power of data and analytics to completely revolutionize an industry.

The mainstream use of AI and machine learning to advance how we interact and use data to derive value is growing. The role it plays at BMO, through the digital-first approach we are taking, is really put into context from the perspective of our customers. It means creating a highly personalized digital experience that is informed by data and analytics, with easy-to-use tools and easy-to-access advice.

BAN: What are some of the biggest data challenges facing banks, and what best practices do you recommend taking to overcome them?

Christofilos: In banking, we need to ensure that our customer data is protected and that our treatment of that data is in line with regulatory — and societal — expectations, which is evolving as new technology emerges. In addition to that, many large institutions like BMO have heavily interconnected legacy data and analytics platforms, with highly ingrained processes and institutional knowledge.

For us, it starts with strong data management practices, governance and a supporting data-operating model that outlines processes, roles and accountabilities to help manage data risk.

Data security and compliance of privacy regulations and expectations is top priority for BMO. We take a disciplined and integrated approach to managing risk, which is fundamental to the success of our operations. BMO’s risk management framework provides independent risk oversight across the enterprise and has a seat at the table when we are designing our data sharing and self-serve capabilities.

Also, both our governance program and operating model were co-developed by a large group of BMO stakeholders through our data and analytics teams. This gave leaders from across BMO an opportunity to help shape the outcomes and ensure that when it came to operationalizing governance and the operating model, there would be no roadblocks in place.

Lastly, when developing a data and analytics roadmap, you need to engage technology and business leaders from across the organization and ensure their short and long-term objectives are considered. It is important that you don’t just chase the shiniest new technology because practically it may not always be the best solution for your business.

BAN: What will BMO’s data capabilities look like in six months?

Christofilos: Foundational platforms need to reduce friction in digital innovation and the support required to maintain the platforms that are our digital engines. This means they need to be customizable, readily scalable, operationally and economically efficient, all while providing us access to cutting-edge capabilities.

To enable all of this, last year BMO announced Amazon Web Services as a preferred, strategic cloud provider to modernize our banking platforms and build digital financial services applications as part of our ongoing digital journey. Using Amazon Web Services’ extensive portfolio of cloud capabilities, including AI, will help us develop and scale digital platforms and services for our customers globally.

BAN: What is unique about BMO’s approach to data analytics and management?

Christofilos: For us at BMO, the value of data and analytics always starts with our customers and employees. We are using data, analytics and AI to deliver increasingly relevant solutions optimized for customers to create a reimagined customer experience and support employees by providing them with easier, more efficient ways to work.

BAN: What data and automations has BMO developed over the past six months?

Christofilos: In the past six months, several of our automation initiatives have been focused on financial crimes, fraud, and anti-money laundering. We are working together with several business partners to build creative solutions for the bank. For instance, our robotic process automation technology team used cutting-edge innovation to automate a U.S. regulatory process — it’s the first UiPath unattended BOT implementation in BMO. Automation of this process has helped BMO address the new regulatory requirement, reduce operational risk, reduce cost of operations and streamline the processes.

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