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The New Face of Banking: How Synthetic Avatars Are Winning Customer Trust

Mukut Banerjee

Innovation Lead , Synechron

AI

Agentic AI is no longer a concept on the horizon; it's already reshaping the banking industry.  

In a market where digital experience is becoming the foundation for customer loyalty, banks are racing to deliver smarter, more personalized and more human-like interactions.  

Synthetic avatars, powered by agentic AI, are emerging as the new interface between institutions and their customers. And unlike their chatbot predecessors, these agents don’t just respond; they reason, adapt and engage.

A 2025 MIT Technology Review study [1] found that 70% of banking institutions are either deploying or piloting agentic AI. Of those, 95% report success in customer advisory use cases, yet only 38% believe their synthetic agents are capable of full digital autonomy. The gap between potential and reality is clear and it’s shaped by concerns around governance, privacy and trust. 

The Rise of Agentic AI

The shift from static interfaces to synthetic media is more than cosmetic. These avatars are autonomous agents that can plan, reason and act. They deliver financial insights, guide decisions, and handle complex workflows, all while adapting to individual customer needs.

Imagine logging into your banking app and being greeted by an intelligent, emotionally aware agent that understands your financial goals, spending habits and risk appetite. It tailors' investment suggestions, flags upcoming cash flow issues, and even helps you plan for retirement. Anytime, anywhere. 

Engagement, Satisfaction and Efficiency: Redefined

The advantages of synthetic avatars powered by agentic AI are clear:

  • Engagement: Customers now expect 24/7 access to relevant information. Synthetic agents deliver it in a logical, intuitive format, no waiting, no friction.
  • Satisfaction: Interactions are contextual, shaped by customer behavior and historical conversations. That means no more starting from scratch.  
  • Efficiency: Operationally cumbersome requests that take up a lot of workforce time, like document processing or account setup, are handled in minutes, not days.

Through synthetic agents, a major multinational financial services firm is already seeing results. By converting 35 analysts into AI avatars, the bank scaled its video content delivery and boosted client satisfaction by 25%. The initiative is expanding to 5,000 videos annually, meeting demand for shortform, personalized financial insights that empower customers to make confident investment decisions. [2]

Use Cases That Matter

Synthetic agents can analyze vast volumes of financial data in minutes, generating guidance for professionals and basic advice for customers. This unlocks real-world applications:

  • High-net-worth clients receive market insights and financial advice in real time, without waiting on a wealth manager.
  • Large loan decisions are made in under a week, thanks to automated credit origination, down from the typical four to five weeks.
  • Corporate and private banking onboarding is completed in days, not months, using agentic AI to streamline verification and compliance.

A leading US bank is using synthetic audiences (AI-generated personas trained on demographic and psychographic data) to simulate customer segments and accelerate strategy development. This approach has shaved months off traditional research cycles.[3]

The Trust Equation

Of course, synthetic media isn’t without risk. Banks must address four critical concerns:

  • Authenticity: Generative AI models are only as good as the data they’re trained on. Proper data governance and AI guardrails are essential.
  • Trust: Even the best-tuned large language models are probabilistic. For high-stakes decisions like investment advice, human oversight is non-negotiable.
  • Security: Whether hosted on-prem or in the cloud, AI systems must be protected against prompt injections, data breaches and denial-of-service attacks.

Despite these risks, agentic AI is already proving its worth. According to the same MIT Technology Review study, 56% of banking executives cite fraud detection and 51% cite security improvements as top benefits. [1]

Regulation Is Catching Up

Regulators are moving quickly. The EU AI Act is one example of legislation responding to the rise of synthetic media and AI in financial services. In banking, expect increased scrutiny around the use of AI for financial advice and calculations.  

The challenges? Customer acceptance is a big one. The uncanny valley effect (where avatars appear almost human, but not quite) can trigger discomfort. In banking, where trust is paramount, avatars must be designed to feel natural, emotionally intelligent and clearly synthetic.

On top of that, AI’s "black box" nature means that, without explainability, even the most effective systems will face regulatory headwinds. Banks must invest in transparency and build models that can justify their outputs.

What’s Next?

Synthetic banking agents are here to stay, but innovation must be matched with integrity. Banks that balance cutting-edge tech with robust governance will lead the charge.

Expect smarter avatars, tighter regulations and customers who expect their bank to “get” them instantly and intuitively in a rapidly evolving market.  

In short, the new face of banking isn’t just a face, it’s a mind. One that never sleeps, never forgets and never puts you on hold. And if executed right, it might just be the most trusted face your customers ever meet. 

The Author

Mukut Banerjee, Innovation Lead
Mukut Banerjee

Innovation Lead

Mukut Banerjee is a highly skilled IT professional with around 10 years of experience in Product Innovation, Program Management, Market Research, and Business Consulting for Banking, Financial Services, and Insurance industries. Currently, he serves as the Innovation Lead at Synechron, where he manages several innovation initiatives focused on the most pressing needs of the clients. Prior to his current role, Mukut worked as an Analyst at Goldman Sachs, where he built and supported a myriad of trading applications in the Fixed Income business. He gained software development experience working as an Engineer at Wipro Technologies, where he developed solutions on Blockchain and Artificial Intelligence for customers across domains. Mukut has a diverse educational background, with a bachelor’s degree in computer engineering from Delhi College of Engineering and a Master of Business Administration from Indian School of Business.

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