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Five Ways in Which Big Data Helps You Grow as a Lender

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Everyone is after big data these days, thinking more data means more success. On the go, they realize it is not data alone that matters, but also the tools to manage and analyze them. A recent survey by Gartner Inc. found that in 2013, 37.8% of North American organizations had invested heavily in big data. The proportion rose to 47% in 2014, and is expected to be 74% by 2018. Customer information is particularly important to the lending sector. As regulations increase, finding the best customers should not involve overheads that don’t translate into profit. That is why big data is a vital aspect in technology that supports lenders. What lending institutions can do with big data –  Security and fraud detection Big data technology identifies patterns buried in data and gives a holistic view to customers. It makes predictive analytics an important part of banking software. By clustering information, technology can help to distinguish suspicious activities from others. This pre-emptive intelligence helps you eliminate fraudulent transactions. Risk Management An integrated finance and risk management data platform can quickly address new requirements. This will facilitate new regulations for better internal management. Offering the right mortgage is necessary because it minimizes the risk of defaults and revenue loss for lenders. Offer personalized products Integrated processes help understand customers’ spending habits, and identify online channels they use and who the key influencers are. This helps take the right mortgage plans to the right people. For some borrowers, you already have their basic data and financial profiling. If they have enquired somewhere else about refinancing, or listed their house for sale, or advertised to buy a new house, you will get an alert through big data technology. That is the most opportune time to offer them new products matching their new needs. Group borrowers for better targeting Big data intelligence helps to classify potential customers based on their buying behavior, interests, age, purchasing power and more. This can boost the response rate to sales, promotions, and marketing campaigns. Compliance and regulatory reporting The Dodd-Frank Act requires lending firms to document everything that goes into the deal through a deal monitoring system. New generation data technology can ensure thorough documentation and automated compliance with regulations. Big-data based subscription to software services will allow your system to stay updated on new regulations as well. Big data is all the data possible to be related to the daily life of your potential borrower. It comprises customer data recorded at your organization, data that the systems harvest from mobile, social media, and ecommerce sites, and data that you can buy from data vendors. You can also avail credit ratings from relevant agencies to maintain in-depth knowledge about your market.

FAQs - Tavant Solutions

How does Tavant leverage big data to help lenders achieve growth?
Tavant uses big data analytics to identify new market opportunities, optimize pricing strategies, improve risk assessment accuracy, personalize customer experiences, and predict market trends. Their platform processes millions of data points to drive strategic growth decisions.
What big data capabilities does Tavant provide for lender expansion?
Tavant offers customer segmentation analytics, market penetration analysis, portfolio optimization tools, predictive modeling for loan performance, and competitive intelligence dashboards that guide strategic growth initiatives.
How does big data improve lending decisions?
Big data improves lending by analyzing alternative data sources, identifying patterns in borrower behavior, predicting default risk more accurately, enabling dynamic pricing, and providing insights into market opportunities.
What types of data do lenders use for growth strategies?
Lenders use demographic data, transaction histories, social media signals, economic indicators, geographic data, competitor analysis, customer feedback, and behavioral patterns to identify growth opportunities.
How can small lenders compete using big data?
Small lenders can leverage cloud-based analytics platforms, focus on niche markets, use alternative data for underserved segments, implement automated decision-making, and partner with data providers to level the playing field.

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