Ever wonder if your enterprise should create your own integrated Channel Analytics solution customized to its business needs? Jen Melton and her team are in process of building it out themselves--though it was by necessity rather than design. She has some takeaways from her journey to help you assess if your organization will provide fertile ground for such a project, how to deliver on immediate needs while building to the strategic vision, how to approach balancing the needs of multiple stakeholders to build a true enterprise platform and how to spot potential landmines before they derail your effort.

By several accounts, a majority of business decisions are still made by hunch as opposed to be driven by evidence. Evidence-based management establishes guidelines to leverage analytics in order to create and monitor effective performance metrics, which in turn enable superior decision making and deliver superior results. Evidence-based management finds applications in a number of fields including medicine, sales, and marketing. If you liked the movie Moneyball, you’ll probably enjoy learning how evidence-based management can improve your business.

The talk will focus on understanding how the financial service industry is looking at web data and applying predictive analytics to generate business-critical insights. It will start with an overview of web data, how it is collected and stored, the challenges faced etc. We will then look the various types of web data ranging from online marketing campaign data, site click-stream data and more recently mobile and social data where we are applying predictive analytics. We will wrap it up by covering some key used cases of predictive analytics applied to web data like targeted acquisition marketing, targeted site experience, risk management and risk splitting. The following is a detailed view of the talk.

Bank of America has a proactive approach to ensure we are serving the needs of low-to moderate-income (LMI) and multicultural (MC) customers. With disciplined focus and dedicated resources, we are able to serve these vital customer segments while adding shareholder value and mitigating reputation and regulatory risk. Strong analytics, senior management accountability and tactical execution have driven our strong LMI and MC lending performance. This same disciplined approach will benefit the industry as we work closely with the Consumer Financial Protection Bureau to operationalize Dodd-Frank and implement the new qualifying mortgage and Basel III rules and government-sponsored entity (GSE) reform.

Banking organizations are facing a range of issues, from reducing risk to rebuilding trust to attracting and retaining increasingly demanding consumers. Banks have access to seemingly unlimited data, but are still not using this information to make better decisions. With IBM SPSS Predictive Analytics, you can determine the right offer for the right customer at the right time, improve bad debt collections, eliminate credit risk, and detect fraudulent banking activities. Attend this session to learn how various organizations are using SPSS Predictive Analytics to increase consumer satisfaction, improve operations, reduce fraud and increase profitability.

Establishing a framework for injecting Insights into business decisions requires effective communication, information relevance and partnership that can achieve broader adoption across the organization. The presentation will cover how to establish Analytics' Value Proposition with business partner for insight adoption.

The presentation “Projecting Profitability” demonstrates how statistical tools are used on a foundation of what drives a business model to bound uncertainty in financial forecasting. Steven will use examples relating to launching Investment Products for illustration.

Every day, analytics professionals receive more and more data. But we have to ask ourselves? Do we REALLY need all this data? The presentation will cover the following topics: Risks of getting unnecessary data, Costs of storing unnecessary data, “Making sales pitch” to client to gather avoid getting unnecessary data, Partnering with client to get the right amount of data, Proper disposal of unnecessary data, A case study.

Increased regulatory scrutiny and market forces are driving firms to better exploit hidden connections in their data in order to proactively detect network intrusion, enable real time market sensing, investigate fraud and understand firm-wide exposure. Once hypotheses have been validated, they can be baked into a predictive analytics or CEP type process that catches the events that fit those patterns. This session will lay out some of the challenges in facilitating discovery and will offer potential solutions which can address these challenges.

Has your organization retooled its customer segmentation strategy and models as Digital transforms it's product set? As Digital revolutionizes one industry after another and develops mass consumer penetration, the traditional customer segmentation models based on demographic, technographic and psychographic techniques are breaking down. As a result, marketing as well as customer management stage models are degrading and fast becoming absolete. What is going on? Join for an engaging discussion on how to reorient the approach to customer segmentation analytics.

Risk management is an integral part of any financial institution. Managing risk often requires the collection, evaluation, and analysis of data. The data typically include well structured data, e.g., provided from predefined drop-down lists, as well as unstructured data like that collected via free form text fields. Traditional analysis and reporting has focused on using the well structured data; however, a great deal of information is embedded in the unstructured text. This presentation covers the topic of mining information-rich bodies of text to enhance risk management practices.

Present 2-3 case study where banking payment industry partnership with international retailer / airline industry on leveraging big data from both sides to design marketing analytics plan, learn customer insight through customer behavioral segmentation, develop actionable campaign strategy, drive spending and revenue growth for both banking and partnerships.

This session will discuss how analytics has evolved over the years, what analytics software products and services are being offered by public companies and what types of companies VCs are funding for the years ahead. We will also cover evolving technology and business models, and their impact on creation of new economic value.

Panelists include:

VP, Specialty Analytics, BNY Mellon
Director, Customer Experience & Analytics, Discover
Senior Statistical Analytics Consultant, Wells Fargo