Creatio has introduced six pre-built AI agents tailored for the banking sector, focusing on enhancing revenue generation and operational efficiency. These agents, which include the Referral Agent, Renewal Agent, Retention Agent, Customer Onboarding Agent, Loan Preparation Agent, and Loan Servicing Agent, can be deployed either as standalone solutions or integrated within Creatio’s platform. According to Andie Dovgan, the firm's chief growth officer, these agents serve as digital employees that can streamline banking processes and resolve specific challenges.

Banks are increasingly leveraging AI agents to automate routine tasks and enhance workflows, resulting in improved ROI. For instance, Morgan Stanley is developing a "super agent" to manage branch operations by working alongside client service associates to simplify tasks like account management and money transfers. This automation allows staff to focus more on high-value client interactions.

BNY is also utilizing AI “digital engineers” to autonomously resolve low-complexity coding problems, enhancing operational efficiency. As banks invest in these digital employees, software providers like Salesforce are offering platforms such as Agentforce specifically for financial services.

Creatio’s new agents can rapidly boost referrals, renewals, and retention metrics, with performance tracking available through dashboards. Designed to operate within productivity tools like Microsoft Teams and Outlook, these AI agents can independently manage banking workflows while maintaining essential human oversight.

As institutions shift from testing to practical implementations, they are keen to measure tangible ROI from these AI deployments, marking a significant step in the banking industry's digital transformation.

Emperor Financial Services Group (EFSG), a leading Hong Kong firm specializing in bullion, forex, and Contract for Difference (CFD) trading, has significantly improved customer service and operational efficiency by implementing Microsoft Dynamics 365 Contact Center, Dynamics 365 Customer Service, Microsoft Power Platform, and Microsoft Copilot Studio. This comprehensive integration has allowed EFSG to streamline processes, enabling the frontline staff to interact with customers via multiple channels—such as chat, email, phone, and social media—through a single interface, enhancing overall responsiveness and customer satisfaction.

The implementation of Copilot Studio has facilitated the creation of custom chatbots capable of handling common inquiries, which has notably decreased the workload on human agents. The AI-powered features, including speech recognition for automatic transcriptions and text-to-speech for personalized greetings, have further optimized customer interactions and reduced note-taking time, ensuring accurate records of conversations. As a result, customer service representatives can access relevant information quickly, thus improving case resolution rates.

Additionally, EFSG leverages Power Automate for workflow automation and Power Apps to create custom applications, enabling a responsive approach to changing market demands. This agility allows uniform customer experiences while ensuring data protection and management efficiency. The integration has empowered EFSG to gain real-time insights into customer interactions, allowing supervisors to prioritize impactful interventions.

Overall, the deployment of these innovative AI-driven solutions has transformed EFSG’s operations, reducing costs while enhancing service delivery, aligning them to maintain a competitive edge in the financial services sector. As they continue to explore further capabilities, EFSG remains committed to innovation and enhancing customer experiences.

Agentic AI is revolutionizing the role of tax professionals, transforming them from seasonal compliance workers into strategic, year-round advisors. By automating intricate workflows, agentic AI not only increases efficiency but also enhances client relationships, leading to higher profitability for firms. Unlike traditional automation, which merely streamlines processes, agentic AI uses generative AI and large language models to execute complex tasks autonomously, adapting to new circumstances without continuous human input.

Tax professionals are utilizing concrete applications of generative AI to improve their daily operations, including:

• Research Assistance: Swiftly summarizing tax code changes and locating relevant guidance.
• Document Drafting: Creating initial drafts for memos, client letters, and technical analyses.
• Data Analysis: Spotting patterns in financial data and flagging unusual transactions.
• Knowledge Retrieval: Answering technical accounting questions with precision.

Agentic AI builds on these generative capabilities, automating compliance tasks and strategically enhancing tax planning. For instance, Thomson Reuters' "Ready to Review" automates tax compliance by monitoring legal changes, analyzing data, and identifying compliance risks, while "Ready to Advise" offers proactive tax planning recommendations based on real-time client data analysis.

Furthermore, Thomson Reuters CoCounsel Tax exemplifies agentic AI's research capabilities by autonomously navigating extensive databases, delivering clear and cited answers to complex questions.

With offerings like CoCounsel tailored explicitly for tax, audit, and accounting professionals, firms can streamline workflows, enhance accuracy, and provide personalized insights. Agentic AI not only boosts efficiency but empowers firms to better meet client demands for strategic advice, ensuring they remain competitive in an evolving landscape. The real challenge lies in how quickly firms will integrate agentic AI to secure their future as industry leaders.

Artificial intelligence (AI) is revolutionizing the finance sector, enhancing the way leaders manage teams, processes, and strategies. At the recent MIT Sloan CFO Summit, prominent CFOs discussed how AI applications, like forecasting and automating repetitive tasks, enable teams to concentrate on strategic initiatives.

During the summit, MIT Sloan professors interviewed industry leaders. For example, Jeff Hoffmeister, CFO of Shopify, highlighted the tailored approach to AI experimentation. Meanwhile, Jason Child, CFO of Arm Holdings, emphasized the necessity of clean data before embarking on AI projects.

Here are four key insights for finance teams on utilizing AI effectively:

1. Identify Specific Use Cases and Validate ROI: Child advises starting with small projects to demonstrate ROI before larger commitments. Arm Holdings exemplified this by transitioning from Excel to AI for forecasting royalties, significantly streamlining the process.

2. Tailor AI Technologies to Business Needs: Hoffmeister noted that there’s no universal AI solution. Different applications serve varied functions across departments. Child stressed that automation can often address fundamental issues, particularly in accounting.

3. Prioritize High-Quality Data: Quality data forms the backbone of successful AI applications. Child advised that 60-80% of data project time is spent cleaning data. Solid data infrastructure enables the effective deployment of automation and machine learning.

4. Encourage Creative Problem-Solving: AI experimentation fosters creative solutions, especially within younger employees who can leverage AI innovatively. Yet, Repenning cautioned against relying solely on younger employees, highlighting the need for critical thinking and foundational skills.

By strategically implementing AI, finance teams can drive efficiency, navigate complex data landscapes, and foster innovative solutions, ultimately enhancing organizational effectiveness.