Accounting for AI: Leveraging Actionable Insights in the Banking Industry
Take advantage of 3 big AI opportunities for banks.
Years of market volatility have underscored the importance of data-driven insights to help financial institutions respond quickly to new challenges and opportunities.
Now generative AI tools like GPT-4 are redefining what's possible. Banks can leverage AI to automate tasks, identify patterns, and make predictions. This improves business outcomes by growing revenue, lowering costs, and reducing risks—all while freeing people to focus on more strategic activities.
But the old rules of data-driven decision-making still apply. AI is just one pillar in the organizational structure needed to deliver insights. Financial services organizations can win by prioritizing risk and growth measures and building an insights-driven strategy that taps into AI’s full potential.
3 big AI Opportunities for Banks
“Nearly two-thirds of financial services leaders now deploy AI in their businesses,” according to a recent Gartner® survey.1 But banks have limited resources to invest. See the AI initiatives and use cases that banks prioritize, and how small and large banks differ when using this technology. Technology can touch any part of the business, but here are some of the ripest opportunities.
1
Personalized Banking
Financial institutions sit on vast pools of customer and transaction data. AI can spot patterns that inform customers' needs and preferences, such as recommending a service based on purchase history or browsing behavior.
Organizations can also use the data to attract new customers by leveraging predictive analytics in marketing campaigns to target customers most likely to be interested in a particular product or service.
2
Predicting Risks and Rewards
Armed with historical financial data, AI can make predictions about future behavior, such as market fluctuations or changes in interest rates. Predictive analytics help banks identify risks, make better lending and investment decisions, and fine-tune customer targeting.
With a solid grounding in future risks and opportunities, financial services companies can make more informed decisions on how to allocate resources.
3
Automating Analysis of Fraud and More
Some of the banking industry's most manual tasks—including fraud detection, customer service, and portfolio management—can be automated in part with AI to free up humans to work on more strategic tasks. It can also scour data to flag potential fraud or spot the telltale signs of money laundering.
These technologies can analyze transaction data and behavioral biometrics from multiple sources to identify suspicious activity and mitigate risk, helping your firm prevent fraud and protect your customers.
5 Pillars of Insight Generation
The opportunities presented by AI come with substantial challenges. To name just a few: data must be high quality for AI models to serve up accurate insights; interpreting the frequently opaque results from these models requires skill; and companies must guard against biases in the training data.
Successful deployment of generative AI rests on solid data governance, starting with a clear data vision. Companies need to emphasize data as a critical business asset, which means streamlining and consolidating cross-functional data, standardizing KPIs, and integrating data to allow self-service across the organization.
Overcome the challenges of AI to enable your organization to curate insights fast by establishing a foundation with these practices in mind.
- Streamline your data ecosystem. Streamlining includes rationalizing your existing data assets and prioritizing and executing value-added functions.
- Centralize your data and business intelligence. Building trustworthy insights requires a single source of truth supported by clean, enriched data that’s accessible across the business.
- Embed AI. Prioritize use cases that can benefit from advanced analytics capabilities to support speed to market.
- Improve your enterprise data governance and operations. You need robust data management, governance, and operations (e.g., DevOps, MLOps) practices that continuously adapt to evolving business demands and the shifting market landscape.
- Optimize a standardized set of metrics and KPIs. This will support the use of various data assets across your ecosystem.
Embrace the Minimum Viable Product
A successful MVP meets a few key criteria:
1
It provides a specific business value - an understanding of product success, revenue, and feedback.
2
It’s self-governed, meaning it improves data quality.
3
It can be managed independently from other data products—such as customer, finance, or marketing data.
Data Governance Overhaul in Practice
We recently partnered with a fast-growing global aerospace and defense technology company to address its siloed data ecosystem, which was burdened by a patchwork of manual processes and legacy knowledge. After assessing key data assets, we identified gaps and led ideation sessions to define strategic future-state architectures.
The solution was an enterprise data program with a best-fit org structure, best practices, and a scalable use-case-driven business intelligence and analytics platform. Additionally, we created an MVP roadmap for streamlining and consolidating data across a specific business segment.
As a result, the company is on target to realize $5 million in cost savings within the first year of enabling the prioritized use cases on top of their new centralized platform. Just as important, leadership is now fully aligned on opportunities to improve the data ecosystem and the quality of actionable business insights going forward.
Insights Designed for Your People
Delivering actionable insights at speed and scale requires a relentless focus on your business and customer needs and an iterative, human-centered approach that validates ideas with real end users.
Point B prioritizes your people in the quest to gain actionable insights that benefit your market position, reduce risk, and improve the bottom line. Our data-driven approach begins with demystifying your objectives and enabling the right technical solutions to support your end-to-end business operations.
About Point B’s Financial Services Consulting Practice
We bring expertise to financial services organizations looking to thrive now and in the future. Our experienced consultants bring broad industry knowledge and work alongside our customers to translate business objectives and strategies into sustainable results. Contact us to learn more.
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