To win customers, start with analytics

Data analytics has become a driver of success for modern businesses. Finance teams can use the same tools to optimise liquidity and performance.

A McKinsey study in 2024 found that companies rated as digital and artificial intelligence (AI) leaders delivered more than double the shareholder returns of laggards across sectors like insurance, retail, and banking, between 2018 and 2022.¹ In retail banking specifically, digital leaders achieved faster mobile app adoption, stronger digital sales, and reduced reliance on contact centres — proving that analytics-driven transformation creates measurable value on both the top and bottom line.

The gap is becoming ever clearer. HSBC Global Investment Research’s Data Science team analysed earnings calls in February and found that companies that spoke about practical AI implementation had outperformed their peers.²

The team refreshed their analysis in June and found the outperformance had continued.³ With generative AI poised to supercharge decision-making, this gap between adopters and laggards could widen further.

It's therefore no surprise that adoption is soaring. IBM’s Global AI Adoption Index shows that 42% of large enterprises with over 1,000 employees surveyed in 2023 had already embedded AI in their operations.⁴ Typical AI applications included enhancing business intelligence, streamlining self-service for customers and employees, improving the precision of marketing and sales efforts, and even financial planning and analysis.

Within those findings, the financial services sector topped the list for AI adoption, with roughly half of respondents’ IT teams reporting that they had deployed AI in their operations.

Other industries are not far behind. Retail, in particular, has become a proving ground for analytics-driven transformation.

In the US, Walmart has deployed an AI-driven space and assortment platform that integrates shelf location and sales data, saving an estimated USD5.6 million annually in FTE hours as store teams become better at curating product selections and streamlining inventory layouts.⁵

Colruyt Group, a leading grocery chain in Belgium, France, and Luxembourg, has piloted AI-enabled image recognition at checkouts, cutting transaction times by up to 20% and making the in-store experience seamless.⁶

In March, a KPMG study focusing on Indian retailers found that more than half reported AI-driven returns on investment exceeding 10%, with one in five seeing returns above 30%, thanks to cutting-edge tools enhancing personalisation, supply-chain visibility, and chatbots.⁷

Advanced analytics can also improve operational efficiencies within the production process of millions of goods every day. In Germany, Henkel uses Internet of Things (IoT) sensors across its factories to detect defects in consumer goods like fabric softeners in real-time, reducing waste and improving quality.⁸

Finally, advanced analytics solutions can also improve customer-facing interactions by improving the digital experience, a key expectation for increasingly digital-native customers. Korean Air, for example, leveraged real-time behavioural analytics to fix booking bottlenecks — boosting its app-store rating from 2.9 to 4.6 and cutting bug-resolution times from two days to just hours.⁹

In the world of banking, HSBC is helping businesses achieve the same edge in improving finance operations.

Economic uncertainty, stubborn inflation, and elevated costs of capital had made it extremely important for HP’s regional treasury team in Asia Pacific to focus on liquidity management, cash forecasting and working capital management. HP adopted HSBC’s Cash Flow Forecasting tool for real-time visibility and automated reporting, cutting hours of manual work across Asia Pacific entities and improving liquidity planning.¹⁰

But analytics can also be a leveller for smaller businesses. Specialist retailer Phoon Huat in Singapore has moved its FX operations to HSBC Evolve, enabling instant execution across 50 markets and 10 currencies — allowing it to handle higher FX volumes without adding headcount, helping it manage volatile currencies.¹¹

In quick-commerce, speed drives loyalty for customers and riders alike. That’s why Delivery Hero subsidiary foodpanda partnered with HSBC to automate rider payments, saving 30 hours of manual processing each month while boosting rider satisfaction — essential for a dependable delivery.¹²

Innovation also powers HSBC’s institutional banking offerings. HSBC’s AI Markets platform uses natural language processing (NLP) to generate bespoke analytics and real-time cross-asset insights.¹³

Through NLP technology, HSBC Global Investment Research’s analysis of earnings calls also found a higher proportion of US companies benefiting from AI technologies compared to European peers. Companies that had spoken about practical AI implementation as well as those which are practically implementing Generative AI – i.e. not just AI hype – into their operations, had also outperformed peers.¹⁴

The takeaway from the research is that companies that are implementing and using AI for operational efficiency, automation, and cost reduction are likely to emerge as long-term winners in their respective sectors.

As markets grow more complex and cost pressures mount, real-time insights and automation are critical to maintaining agility and profitability. Advanced analytics doesn’t just optimise performance; it can fuel innovation, customer loyalty and growth.

Businesses that partner with a banking provider that understands these needs will be best positioned to lead in a fast-moving, data-driven world.