{"id":64219,"date":"2026-02-19T10:10:46","date_gmt":"2026-02-19T10:10:46","guid":{"rendered":"https:\/\/www.elixirr.com\/en-gb\/?p=64219"},"modified":"2026-02-23T15:43:39","modified_gmt":"2026-02-23T15:43:39","slug":"banking-trends-for-2026","status":"publish","type":"post","link":"https:\/\/www.elixirr.com\/en-gb\/banking-trends-for-2026\/","title":{"rendered":"Banking Trends for 2026"},"content":{"rendered":"\n
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As 2026\u00a0progresses,\u00a0several simultaneous\u00a0factors\u00a0are forcing a reset of priorities. With margin tailwinds fading, banks are\u00a0operating\u00a0in a more\u00a0constrained\u00a0environment as other powerful forces\u00a0such as\u00a0Artificial Intelligence (AI),\u00a0shifting consumer behaviour and escalating fraud risk\u00a0intensify.\u00a0These dynamics are converging at the same moment legacy technology and operating models are\u00a0nearing\u00a0the end of their useful\u00a0lives, compressing the room for\u00a0error\u00a0and\u00a0magnifying\u00a0the cost of slow execution.<\/span>\u00a0<\/span><\/p>\n

For bank leadership teams, the question is no longer whether to transform, but where to focus and how quickly intent can be translated into execution in a\u00a0cost constrained environment. AI will be central to this shift, but it is not a silver bullet. The banks that will\u00a0gain an advantage\u00a0are those that move beyond\u00a0surface-level\u00a0AI deployment and instead industrialise AI within simplified technology estates, resilient operating\u00a0models\u00a0and disciplined decision-making.\u00a0Rather than using AI as a surface layer for tactical improvements,\u00a0the real prize lies in embedding AI into core processes and workflows so\u00a0that\u00a0it drives measurable productivity, faster decision\u00a0making, stronger control and sustainable cost improvement.<\/span>\u00a0<\/span><\/p>\n

The dynamics below set out how the pressure of\u00a0profitability normalisation,\u00a0reinforced by changing customer expectations, technology complexity and rising fraud,\u00a0will shape bank priorities in 2026 and\u00a0how institutions can turn\u00a0constraint into competitive advantage.\u00a0<\/span>\u00a0<\/span><\/p>\n

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  1. \n
    Profitability normalisation intensifies the focus on cost optimisation\u00a0<\/span><\/b>\u00a0<\/span><\/h5>\n<\/li>\n<\/ol>\n

    After several years of margin expansion driven by higher interest rates,\u00a0the next phase of performance will be shaped less by rate cycles and more by balance sheet discipline, granular profitability\u00a0insight\u00a0and active portfolio management.\u00a0<\/span>With\u00a0rates largely\u00a0expected to\u00a0stabilise or fall\u00a0through 2026<\/span><\/a>,\u00a0the industry is shifting\u00a0from interest margin driven growth\u00a0to a far more cost-sensitive operating environment.<\/span>\u00a0<\/span><\/p>\n

    In 2026, deposit competition, structural hedging strategies and repricing asymmetry across markets and product mixes\u00a0move from marginal gains to\u00a0core strategic levers\u00a0as margin sensitivity increases.\u00a0At the same time, finance functions are under increasing pressure to deliver faster, decision-grade insight, with profitability transparency by segment,\u00a0product\u00a0and channel rather than only at legal entity level.<\/span>\u00a0<\/span><\/p>\n

    Whilst\u00a0banks\u00a0operated\u00a0in near-zero rate environments after the\u00a0financial crisis, today\u2019s cycle is different. Banks are more complex, digital channels are non-negotiable and technology spend is unavoidable, resulting in a structurally higher cost base. At the same time, persistent inflation, faltering\u00a0growth\u00a0and AI-driven uncertainty continue to weigh on policymakers.\u00a0In this context, cost optimisation\u00a0becomes even more of\u00a0a strategic imperative. Many banks are still carrying significant\u00a0architecture and infrastructure\u00a0debt due to\u00a0duplication\u00a0created through M&A, over-engineered controls layered onto broken processes, and manual operations that were\u00a0masked by strong top-line growth.\u00a0<\/span>\u00a0<\/span><\/p>\n

    As revenue compression increases, these inefficiencies directly erode returns. In 2026, meaningful cost reduction will not come from broad headcount cuts or isolated efficiency programmes. It will come from simplification at source, rationalising application estates, automating end-to-end processes and redesigning operating models so that controls, data and execution are aligned by design rather than managed through manual intervention.<\/span>\u00a0<\/span><\/p>\n

    Banks that\u00a0will\u00a0outperform\u00a0are\u00a0those that\u00a0will\u00a0treat cost as a core design constraint, not a budgeting exercise, using technology,\u00a0data\u00a0and AI to remove friction from the operating model at source, rather than continually managing around it. With less upside from revenue growth, this shift\u00a0from periodic efficiency drives\u00a0to structural simplification becomes a competitive necessity.<\/span>\u00a0<\/span><\/p>\n

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    1. \n
      Banks must reshape products and services for Gen Z and Gen Alpha\u00a0<\/span><\/b>\u00a0<\/span><\/h5>\n<\/li>\n<\/ol>\n

      Consumer expectations are fragmenting, and traditional customer segmentation is\u00a0evolving.\u00a0Banks are increasingly having to shape products and services around cash-light, mobile-first behaviours and more fragmented credit utilisation\u00a0(i.e.,\u00a0mixing debit, wallets, BNPL and short-term credit alongside traditional lending). This shift is already material:\u00a0<\/span>according to Morgan Stanley more than a quarter of US consumers have used Buy Now, Pay Later<\/span><\/a>\u00a0<\/span>as of mid-2025,\u00a0reflecting growing comfort with embedded, short-term credit at the point of purchase.<\/span>\u00a0<\/span><\/p>\n

      As muted economic fundamentals including persistent cost of living pressures drive weaker cashflow, consumers are\u00a0justifying\u00a0a higher appetite for easily accessed\u00a0debt\u00a0like BNPL, as they look for more flexible ways to manage day to day spending.\u00a0This continued uncertainty from consumers in cashflow\u00a0is visible in spend data: shoppers remained restrained through 2025,\u00a0<\/span>with December marking the eighth consecutive drop in UK consumer spending\u00a0and reinforcing a 2026 mindset defined by value-seeking and AI-enabled\u00a0\u2018savvy shopping\u2019<\/span><\/a>\u00a0\u2013\u00a0where\u00a0consumers rely on algorithmic price comparison, personalised offers, spend insights and automated decision support to optimise value.\u00a0Generation Alpha will\u00a0embody this, entering\u00a0financial\u00a0decision-making through non-bank platforms, creator\u00a0economies\u00a0and embedded finance,\u00a0where\u00a0spending behaviour is increasingly shaped by immediacy,\u00a0personalisation\u00a0and social influence rather than traditional financial planning.\u00a0\u00a0<\/span>\u00a0<\/span><\/p>\n

      For banks, this creates both tension and opportunity. Customers increasingly expect real-time decisions, personalised pricing and credit, and seamless digital journeys. Despite this, many banks are still constrained by batch processing, fragmented\u00a0data\u00a0and channel-specific operating models, leading to\u00a0slower innovation.\u00a0<\/span>As super-apps\u00a0and telcos\u00a0like WeChat,\u00a0Alipay\u00a0and\u00a0Orange\u00a0Money\u00a0continue to serve\u00a0billions of\u00a0users\u00a0and\u00a0capture daily financial engagement outside banking channels,<\/span><\/a>\u00a0<\/span>banks face increased vulnerability to attrition outside of the traditional financial ecosystem.<\/span><\/a>\u00a0<\/span><\/p>\n

      The winners will be those that redesign products and decisioning around how customers\u00a0actually behave, embedding real-time data,\u00a0pricing\u00a0and credit into seamless digital journeys rather than forcing new expectations onto legacy models. In 2026, banks that simplify operating models and move from batch-led processing to always-on, personalised engagement will be best positioned to\u00a0retain\u00a0trust, grow relevance with younger\u00a0cohorts\u00a0and compete effectively with non-bank platforms.<\/span>\u00a0<\/span><\/p>\n

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      1. \n
        Will 2026 be the year banks reduce human capital and grow with a much smaller, AI augmented, workforce?<\/h5>\n<\/li>\n<\/ol>\n

        Despite\u00a0sustained investment in cloud, data platforms and AI tooling, many banks have more technology but less flexibility. Cloud, data platforms and AI tooling have often been layered onto unchanged architectures and ways of working, limiting value realisation.\u00a0<\/span>With financial services AI spend projected to reach $97B by 2027<\/span><\/a>, the message is clear: investment only translates into value when complexity is\u00a0removed,\u00a0and capabilities are embedded into workflows\u00a0\u2013\u00a0from engineering and testing through to operational execution and decision support for frontline and risk teams. Without simplification, AI is more likely to increase cost and risk than reduce it.<\/span>\u00a0<\/span><\/p>\n

        In 2026, the focus must shift from technology adoption to fundamental enterprise redesign, with technology as the catalyst. This means rationalising application estates and standardising platforms, but also rethinking how work is organised, how decisions are made, and how teams are structured. As automation and AI take on more routine processing, monitoring and decision support, banks will need to redesign roles, reduce duplication across\u00a0functions\u00a0and reshape workforce composition to reflect a more AI-augmented operating model. Technology advancement will not only reshape systems, but also the structure and size of parts of the organisation itself.<\/span>\u00a0<\/span><\/p>\n

        Overall, we do not expect\u00a0broad-ranging\u00a0workforce\u00a0reductions\u00a0as a direct consequence of AI. Evidence to date suggests that AI adoption is more strongly associated with productivity gains and task redesign than immediate, large-scale job displacement. Research from the Federal\u00a0<\/span>Reserve indicates that workers using generative AI report meaningful time savings in routine tasks\u00a0translating into measurable improvements in output per hour<\/span><\/a>, showing top and bottom-line growth can be achieved simply with proper AI adoption, rather than headcount\u00a0reductions.\u00a0Similarly,\u00a0<\/span>analysis from the Brookings Institution finds that firms adopting AI often experience growth and reallocation of labour rather than net employment decline<\/span><\/a>. As a result, the more immediate impact for banks in 2026 is likely to be doing more with the same people\u00a0\u2013\u00a0automating routine processing, improving decision\u00a0support\u00a0and reallocating human effort toward higher-value, judgement-based activities.<\/span>\u00a0<\/span><\/p>\n

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        1. \n
          Fraud becomes the defining AI battleground<\/span><\/b><\/h5>\n<\/li>\n<\/ol>\n

          Fraud is no longer a perimeter issue, rather\u00a0it is embedded across payments, onboarding, account\u00a0servicing\u00a0and customer interaction.\u00a0According to\u00a0the payment technology company Visa,\u00a0<\/span>the cost of fraud and cybercrime has grown over 30% year-over-year\u00a0for the past six years.<\/span><\/a>\u00a0<\/span>As\u00a0digital volumes grow and fraud techniques become more sophisticated, manual review and rules-based controls are no longer sufficient, especially as human behaviour\u00a0remains\u00a0one of the largest drivers of cyber risk,\u00a0<\/span>with 74% of CISOs citing\u00a0human error as their top security concern<\/span><\/a>.\u00a0<\/span>\u00a0<\/span><\/p>\n

          AI will\u00a0be\u00a0a differentiator\u00a0in fraud management, but only where it is deployed responsibly and at scale. Leading banks are moving toward real-time, behaviour-based risk scoring, adaptive models that learn as fraud patterns evolve and integrated fraud decisioning across channels\u00a0and products to counter increasingly industrialised,\u00a0fast-moving\u00a0and coordinated fraud activity.\u00a0<\/span>\u00a0<\/span><\/p>\n

          We\u00a0increasingly see fraud as a defining customer proposition rather than a back-office control function. Fraud and identity theft are among the most personal and emotionally charged risks customers face, and banks that demonstrably protect customers can turn security into a source of trust,\u00a0advocacy\u00a0and market differentiation. When AI is embedded end-to-end across fraud\u00a0operating\u00a0models, linking data, controls, customer\u00a0experience\u00a0and regulatory expectations,\u00a0it\u00a0also\u00a0enables banks to intervene faster, reduce false positives, and protect customers without adding friction.\u00a0This must also be paired with deliberate cultural and behavioural change. Sustainable fraud resilience also depends on aligning incentives, improving employee\u00a0awareness\u00a0and embedding secure behaviours as the natural way of working.\u00a0Done well, this shifts fraud from a defensive necessity to an offensive capability, strengthening retention and enabling banks to win customers from competitors rather than simply avoiding trust erosion.<\/span>\u00a0<\/span><\/p>\n

            \n
          1. \n
            How to win<\/span><\/b><\/h5>\n<\/li>\n<\/ol>\n

            In\u00a0an\u00a0agenda\u00a0defined by lower margins, rising risk and compressed decision windows, execution becomes the differentiator.\u00a0<\/span>\u00a0<\/span><\/p>\n

            In 2026, advantage will belong to banks that\u00a0prioritise simplification, embed AI into decision making, adapt to shifting customer\u00a0expectations\u00a0and\u00a0leverage technology to turn\u00a0operational processes into\u00a0differentiators.\u00a0The pace of change means that there will be no silver bullet to sustainable growth, but those who holistically transform strategies\u00a0and cultures\u00a0to truly\u00a0benefit\u00a0from technology advancements\u00a0will create competitive advantage.<\/span>\u00a0<\/span><\/p>\n

            The institutions that\u00a0will\u00a0differentiate themselves\u00a0are those prepared to make hard structural choices early. In 2026, advantage will favour banks that act on four priorities:\u00a0<\/span>\u00a0<\/span><\/p>\n

              \n
            1. Remove structural cost by simplifying technology estates and\u00a0eliminating\u00a0duplication across functions.<\/span>\u00a0<\/span><\/li>\n
            2. Transform\u00a0strategy to\u00a0become\u00a0a\u00a0true\u00a0beneficiary of\u00a0AI,\u00a0whilst\u00a0embedding\u00a0a\u00a0culture of\u00a0agility and\u00a0innovation\u00a0throughout the\u00a0organisation.<\/span>\u00a0<\/span><\/li>\n
            3. Redesign\u00a0roles and team structures\u00a0from first principles\u00a0to reflect an\u00a0AI enabled, real-time operating\u00a0model.\u00a0<\/span>\u00a0<\/span><\/li>\n
            4. Align product design with\u00a0the next generation of\u00a0customers and\u00a0leverage\u00a0technology to\u00a0find new ways of differentiating services.<\/span>\u00a0<\/span><\/li>\n<\/ol>\n

              Those that move decisively on these fronts will improve\u00a0time to market, resilience\u00a0and returns while competitors\u00a0remain\u00a0constrained by legacy complexity.<\/span>\u00a0<\/span><\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n\n

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              \n Learn more about our banking expertise<\/span><\/a> <\/div>\n <\/div> <\/div>\n\n <\/div>\n<\/section>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":40,"featured_media":64220,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[116],"tags":[],"related_service":[],"related_industry":[42,78,343],"class_list":["post-64219","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"yoast_head":"\nBanking Trends for 2026 - Elixirr<\/title>\n<meta name=\"description\" content=\"Banking trends in 2026: how UK and US banks must reset for lower margins, AI adoption, rising fraud risk and shifting Gen Z expectations.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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2026\n <\/h2>\n <\/a> <div class=\"wp-component-card__meta\">\n <p class=\"wp-component-card__date\">\n 19 February 2026 <\/p>\n <div class=\"wp-component-card__terms\">\n <div class=\"wp-component-tags edwp-component\">\n <div class=\"wp-component-tags__tag\">\n Financial Services <\/div>\n <div class=\"wp-component-tags__tag\">\n Retail & Corporate Banking <\/div>\n <div class=\"wp-component-tags__tag\">\n Wholesale Banking <\/div>\n <\/div>\n <\/div>\n <\/div>\n <div class=\"wp-component-card__button-wrapper\">\n <button class=\"btn btn--link arrow wp-component-card__button\">\n Read more <span class='edwp-svg '><svg width=\"20\" height=\"20\" viewBox=\"0 0 20 20\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<g id=\"Lg\">\n<path id=\"Vector\" d=\"M1.12509 9.50162H15.8648L9.43259 3.06941C9.374 3.0113 9.3275 2.94216 9.29576 2.86599C9.26403 2.78981 9.24769 2.70811 9.24769 2.62559C9.24769 2.54307 9.26403 2.46137 9.29576 2.38519C9.3275 2.30902 9.374 2.23988 9.43259 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