Building data-driven business systems in financial services

In conversation with Microsoft’s Rupesh Khendry, we discover how the company is helping its customers in the financial services sector garner insight from data

Sean Dudley
Sean Dudley
By Sean Dudley on 12 August 2015
Building data-driven business systems in financial services

This article was first published in the Summer 2015 issue of OnWindows

A new generation of business systems is shaping how companies and organisations within the financial services sector approach and carry out transactions, and it’s a revolution that’s being driven by data.

At the 2015 Convergence event, Microsoft CEO Satya Nadella explained that the combination of unlimited computing capacity of the cloud and data platforms that can reason over data in real time is enabling Microsoft to build what he calls ‘systems of intelligence’.

“These systems of intelligence don’t sit in isolation,” Nadella said. “They, in fact, build on the entire digital fabric that we have with the systems of record and systems of engagement, and create one feedback loop. This feedback loop helps us take all of the digital information we have and make it much more real-time in terms of how we can drive both performance and efficiency.”

With information now coming in a variety of forms and from a variety of sources, it’s vital companies use systems of intelligence that are built around processing vast amounts of disparate data.

“In financial services, data is the business, so it is extremely mission-critical to have the right data to delight your customers, manage your risks and run your business,” says Rupesh Khendry, Microsoft’s director of Worldwide Financial Services.

Because much of this data is no longer static, businesses must be prepared to handle vast amounts of information in flight, with a point in time relevance. And with the ‘electronification’ of the markets, trading and payments information is crossing borders with much lower latency, meaning the importance of immediately actionable predictive insights cannot be underscored enough.

“The days of deploying a plethora of disparate toolsets operating in silos are over, especially in a highly-regulated industry such as financial services, where relevant and timely insights can be the difference between garnering market share growth and incurring huge penalties,” says Khendry. “Financial institutions need to instil a data-driven culture which creates a platform for building the strategy, and need to leverage a seamless set of solutions that offer an end-to-end offering, from data capture to predictive analytics, that can be provisioned and consumed anywhere in a truly mobile world.”

Microsoft is recognised as a leading player in the advanced analytics space. Gartner has recently ranked the company as a visionary in its Magic Quadrant for Advanced Analytics Platforms report, stating that Microsoft has “unparalleled reach into most organisations” with its product offerings, as well as a cloud offering that brings together “best-of-breed components, deep integration with R, the world’s most widely-used programming language for statistical computing and predictive analytics, and R packages and solutions from an entire ecosystem of third parties.”

Khendry identifies three key areas in which Microsoft’s advanced analytics stack can play a vital role in helping financial services companies put data-driven insights at the centre of their business.

The first is fraud detection and risk management – “the ability to manage and grow business directly depends on how well you are able to predict and manage your risk,” he says. The second is advisory services, with more customers asking their financial advisors ‘what have you done for me lately?’ Another high impact area is customer service, with companies looking to anticipate and manage customer churn, as well as offer next product recommendations.

So what is Microsoft doing in this arena to help?

“Microsoft has made huge investments to support our customer initiatives with a best-in-class machine learning offering that is fully managed, integrated and enables customers to collaborate effectively and deploy in minutes,” Khendry explains. “We also recently acquired Revolution Analytics, the leading commercial provider of software and services for R, to help customers use the power of R and data science to unlock big data insights with advanced analytics. When combined with solutions such as stream analytics, a hosted service that processes large volumes of streaming event data with low latency, our customers can derive insights, draw conclusions, and trigger actions in real time.”

Microsoft’s cloud platform provides customers with the flexibility and agility to spur innovation, launch new products rapidly and expand in new markets.

“With intelligent systems and the intelligent cloud, it’s really about having machines that learn and understand the business and the customers,” Khendry says. “Business users can predict risk and provide the solutions or portfolio strategies that are most relevant to them.” From an advisory standpoint, Microsoft’s technology is enabling financial advisory firms to analyse customer preferences, risk appetite and previous investments based on the public information that is available, as well understand their customers’ reasoning over various variables. This is fuelling the rise of ‘robo-advisors’ – systems that are being used to complement or replace the standard financial advisor approach. Firms can also enter new segments that were previously inaccessible due to lack of resources and staff.

And this is just the start. Microsoft has also recently bought Datazen, a leading mobile business intelligence and data visualisation company. Datazen helps organisations create a ‘data culture’ by providing the tools to enable users to extract maximum value from data, from anywhere and on any device.

“It all fits into the strategy of empowering our financial services customers to develop a competitive edge by finding new value in predictive and proactive insights with an end-to-end advanced analytics stack,” says Khendry.

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