Data Analytics


Financial Services

The financial services industry was recently identified as the industry most likely to be disrupted and transformed by millennials in the US. There are similar indications at the global level. The changes in the banking and financial services industry in the coming years will be seismic. As an example, global banks are setting up innovation centers and specialized teams to focus on blockchain, heralded as a disruptive force that offers multiple opportunities such as overhauling existing banking infrastructure, speeding up settlements and streamlining stock exchanges.

Financial institutions are being continuously challenged by shrinking revenues and need to improve operational cost efficiencies. Rising fintech startups and incumbent technology giants are deploying new business models causing disruption and challenging traditional banking business models. Regulators in all geographies are demanding stricter compliance and stronger financial discipline, from the Federal Reserve in the US to the European Banking Authority (EBA) in the EU, the Prudential Regulation Authority (PRA) and the Financial Conduct Authority (FCA) in the UK.

Financial institutions have the benefits of large customer bases and access to rich transactional data.

Creating newer business models or frameworks that leverages the available data allows financial institutions to monetize data to deliver superior customer value.

Winning in this dynamic market will be underpinned by how the financial institutions can derive value from data. The convergence of machine and human intelligence is disrupting traditional decision-making by equipping organizations with knowledge and insight to predict and prescribe business outcomes. Advances in big data and analytics have led to new products, solutions and services making financial institutions smarter, agile and more competitive. Newer regulatory and compliance requirements, fraud and anti-money laundering preventive steps are placing more emphasis on stronger governance and risk management. Data security and data protection is gaining significance. This is driving up operating expenses necessitating financial institutions to explore avenues to improve operational efficiencies. Here are some key trends reshaping the financial services industry:

  • Extremely large data sets to analyze to reveal patterns, trends and correlations
  • Real-time predictive and prescriptive analytics for driving deep actionable insights
  • Risk and compliance demanding timely availability of trustworthy, measurable and secure data
  • Adoption of machine learning and cognitive capabilities
  • Democratization of data enabling more self-service
  • Consumerization of BI through best-of-breed data discovery, exploration and visualization tools
  • Digital platforms powered by 360 view of customers
  • Data and BI landscape transformation and modernization to reduce cost and embrace new-age technologies
  • Analytical master data management capabilities
  • Strengthening data governance capabilities

Infosys point of view

Financial institutions are rapidly transforming themselves into “data-driven” organizations with data collection and analysis underpinning their business strategy and day-to-day decision-making. “Data” in financial institutions has reached the C-suite level with most organizations appointing Chief Data Officers (CDOs) who are responsible for defining the enterprise-wide data and information strategy, governance and quality, controls and policies. CDOs are becoming the catalysts for effectively exploiting data as a corporate asset to create business value.

Financial institutions hold volumes of unstructured data. Historically, this data has been largely underutilized but with advances in technology, they are now able tap into different types of unstructured data – machine data from ATMs and servers, social data from Facebook and Twitter, clickstream data from websites, voice logs from call centers, communication data from e-mails, etc. They are investing in platforms that combine structured and unstructured data and leverage data science and analytics to obtain powerful insights to drive better and seamless customer experience across channels and reduce operating expenses. Infosys’ service offerings are aligned to the key themes of boundaryless information, pervasive analytics and progressive organization. Below are some areas where financial institutions are effectively leveraging data and analytics:

Consumer and commercial banking

  • Supporting consumer analytical models focused on customer lifetime value analysis, customer call center analytics and deposit growth analytics
  • Voice of customer analytics to measure customer sentiment in social media
  • Supporting 360 view to enable cross-sell and upsell


  • Influencing customer purchase behavior through real-time targeted and personalized offers
  • Leveraging large amounts of consumer data across multiple service delivery channels to uncover consumer behavior patterns and understand channel profitability
  • Measuring campaign effectiveness to continuously refine the marketing strategy

Fraud and operations

  • Analyzing customer data to achieve customer intimacy by providing next best action and customer lifecycle interventions
  • Reducing financial losses through real time fraud detection and prevention

Governance, risk and compliance

  • Supporting new regulatory and compliance requirements through stronger policies, procedures and governance practices leveraging newer technologies
  • Hardening predictive credit risk models that tap into large amounts of payment data to prioritize collections
  • Optimizing delinquency models that can predict the probability of loan default

Capital markets, cards and payments

  • Augmenting card and customer data with new-age parameters to derive competitive product pricing models, innovative rewards, assess creditworthiness for underwriting and recommend optimal lines of credit
  • Deriving deeper insights into portfolio performance, liquidity positions and working capital requirements

Success Stories

Enabled compliance with regulations in the areas of AML, FATCA, Dodd-Frank, Basel-II, Basel-III and Volcker by creating a Boundaryless Data Platform for financial services clients that integrated data from many internal and external systems, provided the right validations and controls to improve the trustworthiness of the data and made all the data available to business users in a self-service manner for data exploration, insight generation and analytics

Reduced next-best-offer execution time from 12 weeks to 2 weeks by delivering a high-performance analytics solution for a US-based financial services organization

Improved analysis time by 20% by automating the anti-money laundering (AML) engine dealing with approximately 1 billion transactions for a global bank

Created a 360-degree view of customers to derive insights by implementing a customer MDM solution sourcing data from 50+ source systems comprising of 4000+ entities. It has helped a client reduce operational costs by USD 720k annually.

Support in all aspects of data and information management as part of CDO mandate and delivered a 15% Y-o-Y savings through automation, standardization and reuse for a banking client

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