Banks are flooded in data, both from traditional structured sources and, increasingly, from external “unstructured” sources ranging from social media to newly accessible government and third-party databases.
Our Analytics solutions make massive, indecipherable lump of facts into a vibrant source of useful insights leading to better business decisions. We help separate the “noise” of irrelevant or uninterpretable data from the “signal” of useful, relevant information.
Segmentation is simply dividing the customers into natural groupings that share similar characteristics or behaviors. The concept of segmentation is not new and frequently used in companies, but Big Data facilitates to create sharper segments faster. It helps to see the existing customer base in new ways, which creates unique business opportunities.
Our Big Data segmentation allows Banks to see how customers are really using products and what issues they care about most. We will enable Banks to discover segments that have traditionally been underserved. Highly optimized marketing messages for each of the groups can then be developed, creating greater resonance with customers.
Targeting the right market groups with the right offers can significantly increase marketing effectiveness. Our Big Data analytics consider aspects beyond traditional segmentation of customer age and marital status and predict the customers groups based on lifestyle, life stage and special events. This allows for new and more representative cohorts of a customer base that reveals the needs and wants with far greater accuracy. The information provides Bank opportunity to design more personalized marketing programs.
Quick fraud detection is essential to minimizing losses. The faster a bank detects fraud, the faster it can restrict account activity. We help Banks build comprehensive analytics for strong bank fraud detection strategy. Our solution dive deep into data and look for patterns that indicate potential fraud. Customers with deposit, checking, credit card and personal loan accounts have usage patterns that deep analytics can combine and check against its own fraud indicators.
Banks and financial institutions by default have sense of urgency about understanding data around risks. A logical choice for better managing risks is to use tools meant to handle the speed and volume at which changes in investment data happens daily. Our Big data solutions enhance the quality of risk management models for Banks. Also, our big data models can simulate a variety of scenarios to realize all of the potential risks, leading to faster reactions to developments within the market.