Leveraging AI to transition from Raw Data to Wisdom

David, the Chief Strategy Officer of a NY-based consumer brand, was driven by an insatiable thirst for information, relying on a vast array of data sources and analytical tools to guide decisions. However, when faced with a new market expansion challenge, he became overwhelmed by conflicting signals - engagement metrics showed interest, sales data hinted at potential, but sentiment analysis revealed customer doubts. Seeking clarity, he turned to Sarah from the operations team, known for her pragmatic expertise in streamlining processes. Sarah cut through the noise, linking sentiment, sales trends, and market forecasts to uncover actionable insights. She proposed a phased pilot strategy to address customer concerns and test the market, offering a repeatable blueprint for multi-market entry. This experience was a turning point for David, who realized the true power of data lies not in its volume but in transforming it into meaningful insights for confident, strategic decisions.

This is the real-life story of any organization across industries and countries. Daily, the world generates approximately 402.74 million terabytes of data, encompassing newly created, captured, copied, and consumed information. The global volume of data is expanding at an unprecedented rate. In 2024, the total amount of data created, captured, copied, and consumed worldwide reached approximately 149 zettabytes. This figure is projected to rise to 181 zettabytes by the end of 2025. Corporate employees face a relentless barrage of data from multiple sources. Smartphones deliver notifications, emails, and calendar alerts, while social media, Slack, and Teams add constant updates. CRM systems, ERP dashboards, financial tools, and project management platforms like Asana and Trello flood employees with performance metrics and task updates. Industry reports, market research, and analytics platforms such as Tableau contribute additional layers of complexity, while IoT devices, HR platforms, and compliance tools provide yet more information – Unceasing interruptions that never seem to stop buzzing.

The excessive focus on data in the banking and finance sector has led to significant inefficiencies and productivity losses. Companies are estimated to lose $900 billion annually due to reduced productivity from information overload. This data-centric approach often overlooks the value of insights and wisdom, creating a disconnect between data providers and those seeking actionable intelligence. The impact on decision-making is substantial, with 55% of respondents reporting that information overload hinders their ability to make decisions, and decision fatigue can lead to a 25-40% decline in decision quality. Productivity suffers as well, with information overload reducing knowledge worker productivity by up to 30%, and employees spending an average of 2.5 hours daily searching for information. Interestingly, 43% of consumers prefer companies that personalize experiences by reducing irrelevant information, highlighting the importance of focused, insightful data presentation. This situation demands the need for a shift from mere data accumulation to the cultivation of insights and wisdom, particularly in the banking and finance sector.

In today's data-driven world, organizations often collect vast quantities of information without fully understanding its relevance or how to derive actionable insights. This "more is better" mindset, driven by fear of missing out, technology hype, and a lack of analytical maturity, leads to inefficiencies and obscures decision-making. Leaving aside the new GenAI tools, the number of different systems employees use to perform their jobs has increased significantly in recent years. According to a 2023 Gartner report, the average desk worker utilizes 11 applications to complete their tasks, up from just six in 2019 and on an average 30 plus personal applications installed on mobile. Industries like retail, healthcare, and finance exemplify this issue, where data hoarding results in underutilized insights and wasted resources. To address this, companies must prioritize relevant data aligned with goals, invest in analytical capabilities, adopt a minimalist approach by starting with smaller datasets, and continuously evaluate the utility of their data. By focusing on quality over quantity, organizations can break free from data overload and foster smarter, more ethical decision-making.

At DigiAlly we understand this challenge and hence instead of bringing new data points that will negatively impact efficiency, we bring wisdom and action-based insights for our customers. DigiAlly Pte Ltd is revolutionizing SME finance with its AI-powered Trust Score and Embedded Finance platform. This innovative fintech transforms how lenders assess and serve SMEs, creating value for both businesses and financial institutions. The AI Trust Score, built on insights from thousands of companies over years, provides a holistic evaluation of SMEs' Potential, Intent, and Integrity. By categorizing SMEs into Platinum, Gold, Silver, or Bronze tiers, it enables lenders to efficiently tap into underserved markets. DigiAlly's Embedded Finance platform complements this by offering streamlined lending processes, faster approvals, and reduced operational costs. The results have been impressive: banking and NBFC clients have seen multifold growth in SME portfolios, reduced non-performing assets, and high-speed lending operations. By bridging the gap in SME financial needs with cutting-edge technology and collective insights, DigiAlly is fostering a more inclusive and efficient financial ecosystem.

Institutions with access to SME data have a unique opportunity to drive growth by turning insights into action. Payment analytics from platforms like Stripe, social media metrics, geolocation data, customer sentiment from reviews, and industry trends from tools like Google Trends provide valuable business intelligence. For example, a retail SME can optimize store layouts and inventory using customer footfall data and sentiment analysis, while a logistics SME can reduce delivery times and costs with IoT-powered route optimization. Additional insights from energy efficiency metrics, ESG indicators, workforce productivity tools, alternative credit scoring, and competitive intelligence further enhance decision-making.

Credit for SMEs is at a critical turning point, and while alternative data holds immense potential, it often creates inefficiencies by overwhelming decision-makers with more data rather than actionable insights. Simply providing more data is like asking for faster horses instead of inventing the automobile, as Henry Ford famously noted. The key is not in the quantity of data but in translating it into meaningful insights that drive smarter, faster decisions. Don’t fall into the trap of adding complexity without clarity—focus on leveraging data for innovation, not just accumulation.

To resolve this, AI is the way forward; but we need to understand its key verticals - predictive and generative AI. Predictive AI and Generative AI serve distinct purposes within artificial intelligence. Predictive AI focuses on forecasting outcomes or trends using historical data and statistical models, producing insights like demand forecasts, risk assessments, or fraud detection. In contrast, Generative AI creates new content or data, such as text, images, or designs, by learning patterns through deep learning models like transformers or GANs. While Predictive AI outputs actionable insights to anticipate future events, Generative AI produces creative outputs like articles or synthetic images. Together, they can complement each other, with Predictive AI refining Generative AI outputs or Generative AI providing synthetic data to enhance Predictive AI models.

Predictive AI enhances efficiency, reduces costs, and builds repeatable processes by forecasting trends and optimizing operations. It prevents overstocking or shortages in supply chains, enables predictive maintenance to avoid downtime, and helps schedule staffing based on demand. In marketing, it boosts ROI by personalizing campaigns, while in production, it minimizes waste by aligning output with demand. Predictive AI also optimizes energy use, automates repetitive tasks like claims processing, detects fraud, and scales customer support with AI-driven chatbots. These applications streamline decision-making and drive operational excellence across industries.

Generative AI (GenAI) transforms insights and wisdom gathering by analyzing data, identifying patterns, and providing actionable recommendations. It synthesizes knowledge across domains, contextualizes decisions, and delivers real-time updates for holistic understanding. GenAI supports personalized learning, creative problem-solving, and insight automation by generating reports, summaries, and visualizations. It aids in scenario testing, sentiment analysis, and trend prediction, offering tailored solutions to complex challenges. By enabling knowledge sharing, storytelling, and collaboration, GenAI democratizes data-driven wisdom, ensuring speed, scalability, and accuracy, making advanced insights accessible to individuals and organizations alike.

DigiAlly offers unique combination of Predictive and Generative AI to enable solutions across industries such as #banking and #financialservices, supporting #SME lending, credit scoring, and financial risk management through embedded finance solutions. In supply chain and logistics, it enhances assessment and financing by leveraging data insights. For insurance, DigiAlly enables better underwriting decisions by assessing credit risk and potential claims. In commercial leasing, it provides tools for risk evaluation, portfolio management, and asset optimization. The company also facilitates frictionless cross-border payments and credit evaluations for businesses engaged in international trade. Additionally, DigiAlly partners with fintech platforms to integrate AI-powered Trust Score and credit insights while offering SMEs tools to enhance their #creditworthiness and financial decision-making.

"Data is the new soil, insight is the seed, and wisdom is the harvest that nurtures it into impactful outcomes."

#credit #Ai #machinelearning #genai #credit #digially #predictiveai #payments #trustscore