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May 14, 2024

Unleash Efficiency in Back-Office Operations with AI and Generative AI

Credera Team

Credera Team

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The back office is the backbone of any organization. Buzzing with humans working feverishly, largely with data and documentation, it powers the core functions of an organization. Enterprises invest heavily in their back-office operations, and it is imperative that they meet the highest levels of efficiency and effectiveness and deliver maximum value. And yet back offices are vulnerable to inefficiencies for a host of reasons, including the sheer volumes of data they handle, an over-dependence on manual tasks, siloed processes, limited insights, etc.

Enter generative AI, which has the potential to completely transform back-office operations. It can reduce costs and improve productivity and agility, helping enterprises become more profitable. Research by McKinsey shows that generative AI and other technologies can automate up to 70 percent of work activities, adding trillions of dollars in value to the global economy.

How generative AI can supercharge the back-office

Smarter workflows and greater efficiency

Automating tasks such as data entry, report generation, etc., enables employees to focus on high-value tasks. However, generative AI can go much further. For instance, by examining processes, it can eliminate bottlenecks and significantly reduce operational inefficiencies.

Taking things to the next level, generative AI models can analyze massive datasets comprising different types of data to uncover patterns, find relationships between different data points, and discover new processes. In doing so, they can identify and recommend process optimization opportunities. For instance, Pega GenAI™, integrated across Pega Infinity, can help organizations work smarter with capabilities like workflow performance mining, continuous optimization, and adaptation to new automation.

More accuracy and speed

Automation using generative AI can significantly speed up processes by reducing the time taken to complete tasks. It can handle repetitive tasks in back-office operations such as data entry, generate regulatory reports, etc., with speed and precision. AI and Generative AI models trained on the correct historical data can process enormous volumes of data and detect anomalies, reconcile discrepancies, and maintain data consistency. This mitigates the risk of errors and guarantees high-quality output achieved with reduced effort and time.

Support for real-time decisioning and next-best actions

Generative AI models can provide valuable support in decision-making processes. They can extract meaningful insights from structured and unstructured data and help businesses make data-driven strategic choices, leading to more intelligent and efficient decision-making. For example, Pega’s advanced AI algorithms provide intelligent product recommendations tailored to clients’ financial needs and risk appetite. Pega’s Next-Best-Action strategies boost customer retention and cross-selling by suggesting relevant products and services through predictive analytics.

Challenges to implementing generative AI

As with any new technology, there are challenges to implementing generative AI in an enterprise environment. Topping the list are data privacy and security concerns as generative AI models rely on large datasets to produce meaningful results. Enterprises must comply with data-protection laws to safeguard sensitive data from potential breaches. They should also implement robust data governance policies.

Integrating new technology with existing systems can be challenging as well, as employees are often resistant to change. A well-thought-out change-management strategy that involves a detailed technology integration plan and employee training can help businesses seamlessly integrate generative AI into existing business processes.

Businesses must also exercise extreme caution about the data they use to train AI and generative AI models. If the data is biased or faulty, the output will be biased or erroneous. At best, this could result in a loss of reputation and, at worst, financial losses. Businesses must use unbiased and diverse datasets when training AI models. They need to regularly test and monitor the generated outputs to determine errors and signs of bias or discrimination.

Exploring the diverse applications of generative AI

Risk Management

Financial crimes such as fraud and money laundering are placing increasing pressure on financial institutions. Every suspicious alert and potential incident requires detailed investigation, stretching resources to the limit. Insurers are struggling to manage profitability while trying to grow their businesses, manage risk, and retain clients. Additionally, evolving regulatory demands add complexity to workflows, resulting in greater effort and increased costs across operations.

Banks, underwriters, and other financial institutions need a scalable solution to manage fraud and other risks. AI and Generative AI-powered solutions can accelerate risk detection and remediation through real-time data insights and advanced analytics. Pega’s solution, Pega Financial Crime and Alerts Investigation Management Accelerator, provides financial institutions with a unified solution to manage alerts and drive investigations across all departments, jurisdictions, and lines of business, powered by AI and Gen AI capabilities.

By leveraging Pega’s intelligent automation and case-management capabilities and generative AI-powered capabilities, financial institutions can break through operational silos and streamline investigations, resulting in faster resolutions at lower costs.

Personalized customer service and one-on-one engagement

When customers and enterprises shifted to a digital environment, brands were presented with greater opportunities to connect with their customers. But with the consumer landscape changing too, it is not enough to push out more messages or run broad campaigns for customer segments. Brands must deliver consistent, contextual, and personalized experiences to every customer, to build stronger relationships, drive loyalty, and gain a competitive edge.

Generative AI can be used to analyze data to better understand customer behavior and preferences. It allows marketers to tailor their strategies to target audiences. It can process customer signals and make an offer to the customer, execute an action, or trigger a conversation based on the customer’s needs, in real time.

It enables personalized recommendations, targeted advertising, and interactive experiences, which resonate with customers on a deeper level. For example, we leverage AI and Generative AI embedded in Pega’s Customer Decision Hub to help our clients create and refine next-best actions, validate high-value customer scenarios, analyze the performance of decisions, and get actionable recommendations.

Document management

Knowledge workers spend a significant part of their workday on documentation to complete their tasks. This includes searching for information, reading lengthy documents, creating content, and reviewing documents. The time and effort spent is much more in document-heavy functions such as compliance, HR, finance, claims, etc.

Generative AI is revolutionizing the way enterprise document processing is conducted. It has the ability to intake text and offer concise summaries, furnish crucial data points, and accentuate important clauses. This significantly minimizes the duration required for contract reviews and similar tasks. With the capability for users to employ natural language in posing questions about documents or data contained within them, generative AI efficiently locates relevant documents and extracts the sections most pertinent to the inquiry. Pega’s Knowledge BuddyTM solution, leveraging Gen AI capabilities, empowers users to accomplish these tasks seamlessly.

Generative AI has the potential to transform business in ways beyond our imagination. Enterprises that use it as a strategic tool will be able to reimagine their back-office operations, setting the stage for exceptional growth.

Areteans is committed to delivering solutions powered by generative AI to help customers go beyond what’s next.

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