How Banks Can Leverage AI and OKRs for Digital Transformation and Growth
7 min read

How Banks Can Leverage AI and OKRs for Digital Transformation and Growth

How Banks Can Leverage AI and OKRs for Digital Transformation and Growth

According to Forbes, AI has created a transformational change in banking:

“There are so many different applications for AI and they are increasing daily. Essentially, AI has three major technologies: cognitive computing, machine learning and natural language processing. As a result of these digital tools, there has been a significant shift in the banking industry. Bankers are using AI to improve their relationships with customers.”

The Finance industry Banking and Financial Services have gained significant traction over the past decade, bringing in significant investments and transforming how people manage their finances. 

Artificial Intelligence (AI) brings the advantage of digitization to banks and helps them meet the competition posed by FinTech players, according to Businesswire. The fintech market reached $131.95 billion in 2022 which is expected to grow to $324 billion by 2026. For traditional banks, this highlights the importance of digital transformation.


Auditing firm Deloitte asserts:

“Digital transformation is the essential bridge between the business of today and the business of tomorrow. For every organization, a strategic approach to digital transformation is crucial. Digital possibilities must shape strategy.”

It’s no surprise that AI has had a tremendous impact on the traditional banking environment. According to joint research conducted by the National Business Research Institute and Narrative Science in 2020, about 32% of banks are already using AI technologies such as predictive analytics, voice recognition, and various others, to have a competitive advantage in the market. In addition, Businesswire notes that the global AI in banking market size was valued at $3.88 billion in 2020 and is projected to reach $64.03 billion by 2030, growing at a CAGR of 32.6% from 2021 to 2030.

However, as banks continue to leverage AI, there are challenges to address, such as ensuring data privacy, maintaining ethical AI practices, and navigating regulatory compliance. Striking the right balance between innovation and responsible AI usage is crucial to reap the full benefits of AI in the finance landscape. As with any transformational change, an effective structure is needed to manage the shift, and that’s where OKRs (Objectives and Key Results) come in.

Let’s look at a few OKRs Examples for Banking Firms that delve into how AI and digital transformation can shape an effective, future-oriented strategy.

What are OKRs and Why Should Banks Use It?

OKRs (Objectives and Key Results) is a popular strategy execution framework used by companies across the globe to drive transformational growth. OKRs are especially effective during uncertain business climates, providing a sharp focus on measuring what really matters.

While so much is written about OKRs everywhere, many companies still don’t seem to get it right. This could be attributed to their lack of understanding of OKRs or could also be the inertia of stepping out of their comfort zones around traditional business practices.

Objectives and Key Results can play a significant role in helping banks drive digital transformation by providing a clear and focused framework for achieving strategic objectives in this rapidly evolving landscape. 

Here's how OKRs can contribute to a bank's growth in the context of digital transformation:

  1. Clarity and Alignment: OKRs set specific, measurable, and time-bound objectives that align with the bank's overall digital transformation strategy. This clarity helps ensure that all teams and employees understand their roles in achieving the bank's growth goals, fostering alignment across the organization.

  1. Focus on Strategic Priorities: Digital transformation initiatives can be broad and complex. OKRs help banks identify and prioritize key areas that will have the most significant impact on growth, i.e. create the right outcomes. Banks can then channel resources toward the most critical transformative projects and opportunities. Cycle times can be significantly reduced with OKRs.

  1. Agility and Adaptability: Digital transformation often involves experimentation and rapid iterations. OKRs are flexible and can be adjusted regularly to accommodate changing market dynamics, emerging opportunities, and evolving customer needs, allowing banks to stay agile and responsive to external factors. 

  1. Data-Driven Decision Making: Key Results in OKRs are measurable and based on data, encouraging banks to rely on metric evidence and insights when making decisions. By analyzing progress and results via OKRs, banks can continuously refine their digital transformation strategies for optimal growth.

  1. Encouraging Innovation: OKRs foster a culture of innovation within the bank, encouraging teams to explore new ideas and experiment with emerging technologies. This innovative mindset is crucial for identifying and implementing cutting-edge solutions that drive growth (see point no. 3).

  1. Collaboration and Communication: OKRs facilitate collaboration across different departments and teams within the bank. Regular check-ins and updates on progress (which are crucial OKR rituals) create open lines of communication, allowing for cross-functional learning and leveraging expertise from various parts of the organization.

  1. Measuring Success: OKRs provide a clear framework for evaluating the success of digital transformation initiatives. Key Results offer quantifiable metrics that allow banks to measure the effectiveness of their efforts and identify areas that require improvement.

  1. Motivation and Employee Engagement: OKRs offer a sense of purpose and direction to employees, motivating them to work towards meaningful objectives. Engaged and motivated teams are more likely to contribute positively to the bank's growth and success.

  1. Risk Mitigation: OKRs enable banks to set realistic goals and assess risks associated with their digital transformation initiatives. By breaking down objectives into measurable results, banks can identify potential challenges and adjust their strategies accordingly.

  1. Customer-Centric Focus: Aligning OKRs with customer-centric objectives ensures that the bank's digital transformation efforts prioritize delivering exceptional customer experiences. Satisfied customers are more likely to remain loyal and contribute to the bank's growth through increased usage and referrals.

In summary, OKRs provide banks with a powerful tool to drive growth through digital transformation. This critical change of pace can be made easier and more effective when banks use the OKRs framework to implement their digital transformation strategy.

OKRs Examples for Traditional Banking

The digital transformation of banking, fueled by the adoption of AI and other advanced technologies, presents several challenges that banks need to address to ensure successful and responsible implementation. 

However, the implementation of these solutions requires that banks are capable of handling customer concerns. As banks introduce AI-driven solutions, customer acceptance, and trust in these technologies become crucial. Banks must educate their customers about the benefits and safeguards of AI while being transparent about how AI is used in decision-making. 

Forbes notes that “The future’s looking bright for AI in banking, however, not everyone is convinced this new technology is without its issues. Many are concerned about the closure of bank branches, consumer fear of adopting digital tools and possible increased risk of data breaches.”

In the examples below, we address challenges such as ensuring data privacy, maintaining ethical AI practices, and navigating regulatory compliance. These examples can help banks navigate the fears around AI in banking and improve their relationships with customers. 

OKR Example 1: Ensuring Data Privacy Through Digital Transformation

Banks handle vast amounts of sensitive customer data. The use of AI in processing and analyzing this data introduces concerns about data privacy and security. Ensuring that customer information is adequately protected from unauthorized access/breaches is of utmost importance. Compliance with data protection regulations, such as GDPR or CCPA, becomes critical, as failure to do so can lead to severe legal consequences.

Objective: Enhance data privacy and security measures to safeguard customer information and build trust.

Key Results:

KR 1: Reduce the average time to detect and respond to data breaches by 50%(utilizing AI-driven threat detection and real-time monitoring systems)

KR 2: Reduce the number of major compliance incidents from 38% to 20% over the next six months.  

KR 3: Launch 1 pilot for regulatory reporting and data sharing,

KR 4: Achieve a customer satisfaction rating of 85% or higher in AI transparency surveys. 

KR 5:  Reducing the time spent on compliance checks by 30% and achieving 95%, by implementing an AI tool for identifying potential violations.

OKR Example 2: Maintaining Ethical AI Practices

AI algorithms are designed to learn from data and make decisions based on patterns and correlations. However, if the data used to train these algorithms contains biases, the AI systems can perpetuate and amplify those biases, leading to unfair or discriminatory outcomes. Banks must take measures to identify and mitigate biases, promote fairness, and ensure transparency in their AI models to maintain ethical AI practices.

Objective:  Increase coverage of training and audits on AI Systems inorder to reduce potential vulternabiiities 

Key Results:

KR 1: Conduct weekly audits of AI systems to assess fairness and transparency in lending and other critical decision-making processes 

KR 2: 100% of all AI development teams to be trained on ethical AI principles and guidelines 

KR 3: Increase audit of customer data storage and processing practices from X to 100% 

KR 5: Train 100% of employees on data privacy best practices and conduct regular workshops to raise awareness about the importance of safeguarding customer data.

OKR Example 3: Navigating Regulatory Compliance

The banking industry is heavily regulated, and the adoption of AI may introduce new complexities when it comes to compliance. Banks must navigate regulatory guidelines to ensure that their AI systems meet the required standards, especially concerning risk management, customer protection, anti-money laundering (AML), and fraud detection. Staying up-to-date with ever-changing regulations and ensuring that AI practices align with compliance requirements can be challenging.

Objective: Utilize AI and digital transformation to streamline regulatory compliance processes and reduce operational risks.

Key Results:

KR 1: Increase completion of the training program on emerging regulations and compliance requirements from 45% to 100% 

KR 2: Achieve 100% compliance with data protection regulations and industry standards by implementing robust encryption and access controls.

KR 3: Implement an AI-powered regulatory compliance monitoring system by September 30th 

KR 4: Reduce the time taken to address compliance issues in specific categories from 60 days to 20 days. 

KR 5: Launch 2 pilots on innovative compliance solutions 

Challenges that Can Hinder Banks from Achieving Their Digital Transformation OKRs

We have worked with companies of all sizes to get OKR implementation right. As banks are typically large, legacy enterprises, it’s fitting to caution against the most relevant challenges in OKR implementation. 

Here are the top obstacles that can hinder banks from achieving their OKRs:

  • Relevant Key Stakeholders have not bought into OKRs: Banks are large enterprises, typically consisting of multiple teams and units. Since there are so many business units, the buy-in from leadership teams and business unit heads is needed to ensure successful OKR implementation. One of the biggest challenges is when leaders cannot create the time or bandwidth to drive OKR adoption.

  • Set-Up Time is ignored: In a large company, onboarding OKRs takes time, a minimum of two months depending on the company culture. While external OKR coaches may be able to move fast, internal calendar availability often becomes a small obstacle. The good news is that the entire organization doesn’t need to start with OKRs all at once. Leadership teams and the 2 levels below can pilot OKRs, unlike with a start-up. Secondly, OKRs are not just a 90-day project as teams need to be committed to it for at least one year (a lot of reinforcement happens throughout the process). 

  • Check-ins are deprioritized due to an overwhelming number of meetings: In large enterprises, teams are drowned in a lot of meetings. OKR check-ins should not be seen as an additional chore, instead, an existing meeting should be converted into a check-in so teams are not overwhelmed. When check-ins are executed correctly, they will often remove the need for multiple meetings. The ideal check-in is short and outcome-focused, where teams meet weekly to update OKR progress and identify blockers. Over time, OKRs increase the efficiency of meetings with enterprises. 

Fitbots Can Help You Achieve Your OKRs

At Fitbots, our mission is to help companies drive transformational growth with OKRs, KPIs, and initiative/milestone management, by simplifying how they connect their mission to metrics. Fitbots has worked with over 5,000+ teams, helping them get OKRs right and tracking powerful insights on our OKRs software.

With Fitbots, your teams can achieve 10X more by setting & tracking the right outcome metrics, save an average of 450 hours each quarter on report-making and clumsy powerpoints and increase transparency by 100%. We have consistently rated as a High Performer on G2 and are the proud recipients of multiple G2 badges. Our top-rated offerings include:

  • 5-Step Method to reduce Strategic/Company OKRs writing to a matter of hours, helping leaders focus on action rather than verbose discussions
  • AI-Assisted OKR Writing to reduce the time spent by teams in crafting effective OKRs that reflect company strategy
  • Alignment and Misalignment Boards that ensure complete alignment such that there is no wastage of time, effort, revenue
  • OKRs and KPIs management alongside a vast number of integrations
  • Progress Boards, Trends Boards, Insights, and Reports at the organization and team level for effective decision-making and performance improvement
  • Individual reports and insights to support performance-related conversations
  • On-demand OKR Coaching and Certification 

Click here to book a call with our OKRs expert on how we can help you get OKRs right, and manage them with powerful insights.

About the Author

Bani is an OKR enthusiast who anchors content and marketing at Fitbots OKRs. She loves spreading the love of OKRs to enrich workplaces and collaborating to create engaging content for her readers.


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