Operational Excellence

Industry Trends

The financial services industry is undergoing rapid and disruptive changes due to digital transformation, regulatory compliance, customer expectations, and market competition. Financial institutions need to adopt agile, scalable, and resilient operating models that can deliver value to customers, shareholders, and regulators. Operational excellence is a key strategic imperative for financial institutions to achieve operational efficiency, customer satisfaction, innovation, and growth.

The Challenge

Many financial institutions face operational challenges such as:

  • Legacy systems
  • Siloed processes
  • Manual workflows
  • Data quality issues
  • Cyber risks

These challenges hinder the ability of financial institutions to respond to changing customer needs, regulatory requirements, and market opportunities. Financial institutions need to overcome these challenges and transform their operations to become more:

  • Customer-centric
  • Data-driven
  • Agile

The Opportunity

By taking a holistic approach to operational excellence, financial institutions can assess their current state, identify gaps and opportunities, and design and implement solutions that optimize their operations. Operational excellence consulting can help financial institutions. We take a unique approach where we apply a design thinking methodology to:

  • Assess the current state of our clients
  • Benchmark against peer organizations and senior leadership's strategic objectives
  • Develop a roadmap for continuous increases in organization capabilities
  • Support ongoing progress in that roadmap

Leading Practices

Operational excellence consulting can help financial institutions to adopt the following leading practices for achieving operational excellence:

  • Benchmarking: Comparing the performance and practices of the organization with the industry standards and best practices.
  • Gap Analysis: Identifying the gaps between the current and desired state of the operations and prioritizing the areas for improvement.
  • Roadmap Development: Developing a roadmap that defines the vision, objectives, initiatives, and milestones for achieving operational excellence.
  • Change Management: Managing the change process and ensuring the buy-in and engagement of the stakeholders, employees, and customers.
  • Continuous Improvement: Monitoring and measuring the results and outcomes of the operational excellence initiatives and applying feedback and learning to enhance the operations.

Our Offerings

We offer a comprehensive range of solutions and services to support operational excellence tailored to the specific needs and objectives of the financial services sector, such as:

  • Application Integration: Integrating applications across the enterprise to enable seamless data flow, process automation, and business intelligence.
  • Payments Modernization: Modernizing the payments infrastructure and processes to enhance speed, security, and efficiency of transactions.
  • Business Transformation: Transforming the business processes, culture, and capabilities to align with the strategic vision and goals of the organization.
  • Technical Due Diligence: Conducting a comprehensive review of the technical aspects of the operations, such as systems, architecture, security, and performance.
Slide 1
Commercial Card Analytics

A national bank effectively addressed fraud risk and improved customer engagement in its commercial card business by implementing advanced data analytics and machine learning to analyze merchant card usage, resulting in enhanced fraud detection, increased customer loyalty, and boosted revenue.

Slide 1
Predictive lending, Cross-Sell/Up-Sell:

A large national bank boosted its lending revenue by developing a data-driven solution that utilized machine learning to analyze historical and external data, identifying deposit clients with high borrowing propensity and optimizing communication channels for loan and mortgage offers, resulting in increased revenue, improved customer retention, and enhanced bank reputation.

Predictive lending, Attrition Forecasting
Predictive lending, Attrition Forecasting

A major bank improved borrower retention by developing predictive lending models that utilized machine learning to analyze personal, financial, and behavioral data, identifying borrowers likely to refinance with other lenders and optimizing retention strategies, resulting in reduced attrition, increased customer satisfaction, and enhanced market share.

Deposit Attrition, Business Banking:
Deposit Attrition, Business Banking:

A bank increased its deposit retention rate by developing a data-driven solution that utilized advanced analytics to segment customers, created personalized offers, and leveraged multiple communication channels, resulting in higher customer satisfaction and additional revenue.

Wealth Management – Attrition, Segmentation
Wealth Management, Attrition, & Segmentation:

A bank grew its wealth management business by implementing a data-driven solution that utilized analytics and machine learning to segment customers based on financial health and life events, providing personalized solutions and communication strategies, resulting in improved customer satisfaction, loyalty, and increased market share and revenue.

liquidity management
Liquidity Management

A bank enhanced its liquidity management by developing an advanced analytics and machine learning system to accurately predict daily cash flow and optimize liquidity management, resulting in improved cash flow forecast accuracy, increased return on excess cash, and enhanced operational efficiency and compliance.

Payout Process Transformation​
Payout Process Transformation​

A leading insurance provider improved its payout process by implementing a cloud-based platform that transformed 86% of checks to digital, reduced fraud and errors by 92%, and achieved an annualized ROI of over 500%, while enhancing customer satisfaction by 30% and completing the transformation in less than 6 weeks.

Enhancing Fraud Detection and Enforcement for a US Financial Regulatory Agency
Enhancing Fraud Detection and Enforcement for a US Financial Regulatory Agency

A US financial regulatory agency enhanced fraud detection and enforcement by implementing a new Enterprise Data Warehouse platform that leveraged advanced analytics and machine learning to process and analyze data from over 6 billion records, resulting in a 20% increase in enforcement actions, improved data accuracy, and enhanced agency reputation.

Case Study: Post M&A Operational Alignment​
Post M&A Operational Alignment​

A large FinTech company addressed post-M&A challenges by implementing enhanced SDLC methodologies, consolidating key business functions, and realigning staff, resulting in a 20% reduction in operational costs, a 75% reduction in case backlog, and a 98% customer renewal rate, all while achieving substantial improvements in operational efficiency and customer satisfaction.

Case Study: Strategic Roadmap for a Global Bank​
Strategic Roadmap for a Global Bank​

A global bank overcame challenges in a competitive financial sector by partnering to develop a strategic roadmap for data and analytics transformation, leading to improved customer satisfaction and retention, increased revenue and profitability, enhanced operational efficiency, and better decision-making through a 360-degree view of the customer journey and optimized processes.

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MCG's team possess deep industry expertise, enabling them to craft actionable strategies, implement them effectively, and achieve tangible results.