Genpact Reveals Urgent Need for AI Adoption in Banking

The financial services sector is witnessing a pivotal shift as artificial intelligence (AI) transitions from experimental phases to practical applications. This evolution is crucial for banks and insurers that face the daunting task of integrating AI into regulated environments where governance, auditability, and human oversight are paramount. The concept of the "last mile" in AI deployment highlights the critical gap between developing AI models and effectively implementing them in live operations, which is where many institutions currently struggle.

Financial institutions have made significant strides in AI model development over the past two years, launching programs and modernizing their platforms. However, the challenge now lies in translating these advancements into operational value. Genpact, a leader in financial services operations, identifies this operational reality as the last mile—a term that encapsulates the difficulties of moving from theoretical AI capabilities to practical, reliable applications in banking and insurance workflows.

The last mile manifests most prominently in areas such as financial crime, compliance, and customer experience in banking, as well as underwriting and claims in insurance. Despite improvements in model-building capabilities, many firms are hindered by complex internal structures, including fragmented data, outdated systems, and talent shortages. Genpact's research indicates that these "enterprise debts" result in an estimated $1.4 trillion in unrealized value for banks and $1.1 trillion for insurers, with a significant majority of leaders in both sectors acknowledging the burden of these challenges.

In banking, the urgency of closing the last mile is particularly evident in compliance and financial crime operations, where the volume of alerts and regulatory scrutiny continues to grow. Traditional processes struggle to keep pace, leading to inefficiencies that can undermine trust among regulators and customers alike. Genpact's solutions, such as the Banking Analyst Suite and riskCanvas, are designed to enhance transaction monitoring and fraud workflows by integrating AI capabilities with necessary governance measures.

Similarly, in the insurance sector, inefficiencies in underwriting and claims processing are costing the industry billions annually. With underwriters spending a substantial portion of their time on administrative tasks rather than decision-making, Genpact's Insurance Policy Suite aims to streamline these workflows, reducing cycle times and increasing operational efficiency. The integration of AI in these processes not only accelerates decision-making but also enhances the explainability and reliability of outcomes.

As financial institutions navigate the complexities of AI integration, they must prioritize governance, operational readiness, and measurable business outcomes. Successful leaders in this space will adopt a holistic approach that treats AI as an ongoing operational asset rather than a one-time implementation. This mindset fosters a culture of continuous improvement and accountability, essential for maintaining compliance and trust in an increasingly regulated environment.

Looking ahead, the competitive landscape will be defined by the ability of financial services firms to bridge the execution gap in AI deployment. The next generation of leaders will not merely rely on access to AI technology; they will excel in embedding AI into their core operations, enabling sharper decision-making and enhanced customer experiences. As institutions strive to close the last mile, those that effectively harness AI to deliver tangible business outcomes will emerge as the frontrunners in a rapidly evolving market.