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Transformations in Financial Technologies

Jacob Sorensen, CIO, Bank of the West

Jacob Sorensen, CIO, Bank of the West

Massive and rapid shifts in technology are affecting everything we do in our daily lives, from the way we move around within a city to how we buy groceries and communicate with each other.

In the business community, finance is at the forefront of change, with the need for faster and more accurate data— heightened due to the role finance plays to manage a company’s critical functions like treasury, financial planning, accounting, and capital planning. Therefore, finance needs to be on the cutting edge of technological changes in data, its accuracy, and how it’s delivered and utilized. Finance is at the forefront of moving from explaining what happened, to predicting what will happen, and enabling the business to prepare for that future.

That means reliable, accurate data about a company’s current state is central to a company’s success, and the way it communicates its status in real-time with employees, partners, or even regulators.

Finance also helps show what’s in a company’s future, so predictive analytics are critical for business health and growth. This has finance moving from being the “scorekeeper” to the “fortune teller” and leveraging data and advanced analytics, including machine learning techniques, as critical tools.

Finance is at the forefront of moving from explaining what happened, to predicting what will happen, and enabling the business to prepare for that future

Digital is now fundamental, from the front to the back of the house, for employees and customers, online and mobile. For finance, being able to automate monotonous data-related tasks is an important way to help employees have time to provide strategic, value-added views of what the data means and how you can use it to help your business. Digital processes that leverage accurate data and API’s are critical to advanced automation. Beyond that, leveraging the growing Robotics (RPA) capabilities are allowing even desktop solutions to automate significant parts of what were once manual routines. Automation and digitization also have the added benefit of standardization of data, which helps with data quality and allows for more predictability by inserting machine learning and AI in the process.

Trust is critical for any business related to customers, shareholders, employees, and regulators. For finance, trust is related to an organization’s stability in terms of capital and liquidity, which re-emphasizes the earlier points about reliable data and strategically evaluating it.

For many, trust involves information security, and the safety and soundness of the organization overall. At the very least, businesses must have an effective plan that protects employees and customers while meeting regulatory requirements. The environment changes consistently, so change must be a constant, with an eye on being proactive and predictive in identifying current and future threats, while also supporting business growth and innovation.

Just as data and analytics are most effective when they’re timely, organizations are trying to deliver their services in more nimble and effective ways. Aligning business and technology teams leveraging agile delivery models creates solutions faster with more predictability, and improves quality with less rework.

In conclusion, staying up-to-date on data quality and delivery are no longer “nice to have” investments for finance organizations. Instead, accurate, reliable data is key to managing a company’s profitable growth, risks, and reputation.

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Transformations in Financial Technologies

Machine Learning

Financial

Information Security

Predictive Analytics

Wealth Management

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