Columbus, OH, June 25, 2021 –(PR.com)– Today, Proven Optics LLC, a practitioner-founded software and services company, announced the Proven Optics Enterprise Budgeting & Forecasting Application and the ITFM Cost Modeling Application from its Financial Management Application Suite are now certified as part of the ServiceNow Built on Now Program. This new Application Suite combines the platform native capabilities with over twenty years of Technology Business Management (TBM) practitioner experience to bring a modern approach to financial management. These solutions have met the high standards of the ServiceNow Built on Now Program designed to recognize partners with proven ServiceNow expertise that creates value for customers across industries.

The Financial Management Application Suite combines an industry agnostic experience with digital workflows to evolve the end user, financial manager, and leadership user experience. The Enterprise Budgeting & Forecasting Application manages the annual budgeting process, monthly forecasting, and actuals monitoring on the ServiceNow platform. The ITFM Cost Modeling Application has service-based costing that enables next generation ITFM Cost Modeling for IT leaders to drive strategic decision-making capabilities and better business outcomes. Accompanying the Cost Modeling Application is an application that facilitates customer invoicing and chargeback of the different IT services customers are consuming in the cost model.

“Building on the Now Platform created easy accessibility for our customers to onboard into these applications and completely divorce themselves from 90% of the technical challenges that come from implementing a standalone point solution,” said William Miller, Founding Partner of Proven Optics.

Leveraging the Now Platform’s native functionality, these capabilities have redefined what ease-of-use means for the stakeholder. Features like workflow automation, CMDB integrations, and automatic allocation tables eliminate data maintenance and clean up across multiple teams and drives the focus towards outcomes and analysis for leadership.

You can find the Proven Optics Enterprise Budgeting & Forecasting Application and the Proven Optics ITFM Cost Modeling Application on the ServiceNow store today. Public Sector versions of these Applications are also available.

The ServiceNow Built on Now program empowers partners to build, test, certify, distribute and sell applications for the Now Platform. Built on Now-designated solutions deliver Now Certified digital workflows for the Now Platform, at scale, through the ServiceNow Store, OEM, and Service Provider (SP) channels.

Proven Optics is a software and services company that focuses on one thing: Financial Management. We help clients in both IT and Finance organizations implement financial management toolsets on SaaS platforms that leverage our 20+ years of practitioner experience and 100+ Commercial & Federal implementations. Our solutions enable financial management modernization to provide IT & Finance leaders with the necessary analytics and insights to make better business decisions. For information or demonstration of our products, please contact Ben Perkins at ben.perkins@provenoptics.com.

ServiceNow, the ServiceNow logo, Now, Now Platform, and other ServiceNow marks are trademarks and/or registered trademarks of ServiceNow, Inc. in the United States and/or other countries.

Most enterprises are still migrating workloads from data centers to the cloud. Although saving money is generally not the driving force for such migrations, it doesn’t hurt if money is saved along the way for better scaling or reliability, or an end to IT capital expenses.

The financial benefits of cloud computing, though not as inevitable as years of hype made folks expect, are real. The following are the top five strategies CIOs can use to reap those cost benefits.

1. Avoid lift and shift
It gets easier to shift a workload or a set of integrated workloads into a cloud environment with minimal modification. If a cloud migration is motivated by a looming data center lease expiration, a lift and shift of virtual machines (VMs) and data sets may be the only way to meet the deadlines. However, it will probably come with a cost increase for providing the shifted services in the near term.

Systems that were not designed to run in the cloud usually don’t take advantage of the features of cloud that hold the greatest potential for savings: the ability to scale infrastructure dynamically both up and down in response to load, and the ability to scale horizontally by spinning up new VMs or containers. Between them, these features allow IT to pay for only as much infrastructure as the workload needs, when it needs it. In-house resources must always be present to handle the peak load of the system and shifting a workload to the cloud unchanged usually means it is overprovisioned most of the time. As a result, enterprises wind up paying more to run in the cloud.

Nemertes Research found that IT shops on average spend about 12% more to run a workload in the cloud than in their own data center.

Therefore, IT should be seeking to refactor workloads to be more cloud-friendly wherever possible or seeking to replace pre-cloud architectures with cloud-native ones built on the premise of just-in-time infrastructure. In Nemertes’ research on cloud operations, the organizations best at this were, on average, running workloads for just 40% of what they had spent on premises.

To facilitate a cloud migration, IT should have in place a consistent workload placement process (WPP) to follow in evaluating workloads for migration. The WPP should take into account the architecture of the workload, prioritizing cloud-friendly systems over cloud-hostile ones, and weigh numerous other factors such as the risk associated with hosting in cloud versus on premises (it is often lower risk to provide service from the cloud now), the performance requirements of the workload and so on.

2. Utilize commitment and tiering
Too many cloud teams fail to take full advantage of committed instance pricing, and therefore are unable to get discounted rates on their resources. They do so out of an overabundance of either caution or optimism — not wanting to make a long-term commitment on a system that might be refactored or replaced in the near term.

CIOs should set up a process for sequencing such changes and utilize as much long-term pricing as they can based on the schedule that falls out of it. Any slight overcommitment will be more than balanced by savings.

3. Pay attention to data gravity
Surprise expenses often come in the form of data egress charges — the cost of moving data out of a cloud environment into another or back on premises. The WPP must include consideration of data affinities and should be used to group together systems that produce heavy traffic among themselves.

4. Use PaaS
Nemertes’ research on cloud operations found that organizations can save on average 15% to 20% on staff costs by shifting to database as a service or application server environments consumed as PaaS.

5. Empty racks, rooms, buildings
One of the primary goals should be supporting infrastructure in data centers and to realize savings there as fast as possible. Being able to empty racks entirely means also being able to reduce cooling and UPS service.

Ultimately, the important takeaway is that financial benefits of cloud computing are possible but not inevitable. All CIOs, even if they are pursuing cloud for reasons other than cost savings, should factor the possibility of savings into their decisions and planning, aiming to realize them when it doesn’t prevent them achieving their strategic goals for cloud.

In many instances, though, this significant investment of time and resources simply isn’t producing measurable outcomes that matter to the broader financial services organization. Developers may be coding faster and new operating efficiencies may be realized, but little else has changed. Teams are simply unable to move the needle in support of core business strategies that determine success or failure in the marketplace.

Why the disconnect? Often those assigned to IT transformation projects work in isolation. They have no way of knowing whether they are delivering what customers need, when and how they need it. What’s more, they are unable to deliver the metrics and feedback needed by product development and strategy teams to guide continuous improvement and innovation.

Is it any surprise that during tough times, transformation teams are often among the first on the chopping block in the financial services space? They have simply been unable to demonstrate that the significant investments made in their work are worth it.

A 2-Step Solution
If your DevOps team is committed to modernization, consider this two-step approach to resolving the disconnect between the work you do and the core business you serve.

First, don’t work with blinders on. Broaden your mindset and involve all critical stakeholders, from business strategists and developers to operations specialists and customer-facing support teams. Engaging this broader group of constituents can help you gather multiple perspectives on what success looks like and where you need to focus your time and attention. You can determine what outcomes truly matter to your organization and what criteria you need to monitor to demonstrate the value you produce.

Second, it’s time to rethink testing and the role it plays in your organization. Adopt an automated, technology-agnostic platform that can provide continuous feedback to everyone on your expanded team, not just developers writing code.

The experiences of a global 500 banking and finance company show why a broadened approach to testing matters. The company was treating testing as an event, part of a linear application development process. Projects were prioritized, code was written and testing was conducted to determine whether the work was bug-free.

Test creation and maintenance relied on manual effort, making it impossible to keep up with the continuous code development of agile teams. In addition, proprietary testing tools were difficult to use. It was impossible to shift left for continuous integration of fully tested code early in development. And it was impossible to shift right to monitor and learn from application performance and customer experiences.

As a result, the company lacked a continuous loop of predictive insights and feedback that could be accessed and used by stakeholders across multiple geographic locations to advance the priorities of the business.

The bank rethought its approach and adopted a new artificial intelligence-powered platform based on open source standards. Now all stakeholders can run tests and monitor services from anywhere, with tools that are easy for anyone to use. And they can do so without sensitive data ever leaving their network. They have the insights they need to create focus and deliver results that matter.

Making a Smart Investment
If you’re ready to broaden your DevOps mindset and make the move to continuous testing, keep the following tips in mind. Look for an open source, enterprise-ready test automation environment that is easy to use and integrates seamlessly with your existing testing tools. In addition, insist on the following features that will help you broaden the strategic impact of your testing and monitoring program:

Single-pane business insights: Select a solution that helps you keep everyone on the same page, enabling a continuous flow of predictive insights and feedback that is easily accessed and understood. Make certain you can track trends from multiple builds and can share interactive test results and graphs with all your teammates and stakeholders.
On–demand scalability: Many legacy tools have limited load-generation capacity. Look for a solution that can help you overcome that hurdle. You should be able to upload tests and emulate network conditions on demand across multiple geographies, while simulating millions of virtual users.
Decentralization: Your new test environment should let you broaden your testing program by shifting both left and right as you orchestrate new releases. Make certain you can easily broker new automated tools for continuous monitoring and empower all stakeholders to use them. This democratic approach will help you overcome manual testing bottlenecks and promote faster intervention when issues arise.
Self-service test creation: Make certain the user interface for your new platform is “load and go,” with no proprietary languages or special skills required. Anyone should be able to create small-scale, self-service tests from a local machine, then seamlessly reuse the same tests at scale via the cloud to accelerate test automation as part of your continuous delivery pipeline.
The Payoff for Financial Services Firms
It’s time to make certain your transformation efforts are headed in the right direction and that your team isn’t working in isolation from the broader business. Expand your mindset and your toolset to encompass key stakeholders and to align with your organization’s business strategy.

Embed test automation into every activity across your software delivery life cycle and create a continuous feedback loop that informs planning, development and operations. When you do, you can turbocharge velocity, improve quality, boost efficiency and keep pace with customer expectations, all while supporting what matters most to the success of your enterprise.

There has never been a more essential time to ensure teams work together and deliver features with speed and efficiency. Implementing DevOps practices into your workflows gives your business the structure for constant evolution, cutting costs and optimising efficiency. This ensures you can grow secure in the knowledge that you have the best systems in place to support your development, using automated processes and a personalised strategy to create resilient, future-proof growth. Here are the 4 layers of DevOps for financial institutions.

Infrastructure to Code

It is important to clarify that the definition of ‘DevOps’ deviates from the perhaps more traditional banking definition, that being a union of Development people and Operations people, but rather it is a combination of Technical Development people and Machine Operations people. The machine operators that would’ve usually built the physical computing infrastructure now work on projects together with developers, becoming a single team. Machine operators are therefore able to help the developers understand how to construct and code the infrastructure of their applications for efficiency and longevity. Essentially, recreating the physical processing power infrastructure within code.

Microservices

Microservices are about system architecture. They are a fragment of code that give every function of an application its own ‘container’. The inputs and outputs of each fragment are static. This means we can change anything in the code without it affecting the rest of the system, giving us independently deployable services, this means we won’t need to do a complete system test or full impact analysis every time we want to make a change.

The benefits of microservices can easily be seen on the world’s most popular website: Google.com, the image sitting above the search bar is a Microservice. Consider how often that image changes? Now compare that with how often you’ve seen Google take down their entire system/website to make sure the image is going to work for everybody on the endless variety of devices that visit the website.

Microservices may be small but when they are appropriately constructed in their fragments, interfaced correctly and built out, microservices can make some of the most complex systems in the world. From collateral management entirely done on the web using microservices to trading systems for bonds and equities, microservices are leveraged to help keep your systems running at all times. Microservices reduce the amount of testing that has to be done substantially, and as many of you know, testing often chews up 30% – 50% of your budget on any well-run project.

Build-to-Test

This is a change in mindset. We used to write a spec, have a committee sit on it and then sign it off, put it under change control, give it to developers to code it, then finally to the quality assurance testing team. Now when using a collection of microservices to meet a customer need, we can build-to-test. This means the code can be built inside the testing tool, the advantage to this is the ease at which we can make changes to or test elements of a system, radically changing the pace at which testing models take place. Through this, by having infrastructure-to-code, developing in microservices, and building to test (all of the above), we achieve what is known as CICD (Continuous Integration, Continuous Deployment), and that means we can put changes into production on a regular basis without impacting the client base, even while they are still using the system. So how do we actually code this?

Agile Methodologies

This is where the cultural mind shift occurs. This layer will consist of 3 elements. The 1st is the way in which we conduct our business requirements. Instead of having highly-qualified business analysts sitting down and consulting with users on how things are done, what if now the users can just ‘tell a story’. Perhaps they could say something like “I came in this morning and sat down at my desk and I put my finger on the finger print reader and it gave me a list of things that I have to do today.” That’s an example of a ‘user story’.

For all the technical people reading this: can you imagine what you would be coding if you received that story? Allow me to elaborate, it would go something like this – “I’d need fingerprint recognition, therefore biometrics. Then the application needs to automatically open upon recognition and on the right-hand side the user should see a list of actions that they need to take today.” By building entire pipelines of user stories that meet each specific user’s need, we can describe complex systems in terms that any user can describe.

These then go to squads, the 2nd element, which consists of about 7-12 people. Each squad will receive a number of user stories. What is a squad? A squad has defined roles, it’s made up of a Product Owner, Scrum Master or an Agile Coach and a number of technical and testing roles. In order for these squads to be highly productive they need to be co-operating fully throughout the day. But for those that are offshoring from east to west, or vice-versa, how can your squads be productive when there is up to a 10 and-a-half hour time difference? But if you were to offshore north to south you will be looking at an hour or two in time difference at the most, then you can begin to see highly productive squads who will all be awake at the same time.

Now the 3rd and final element, the squads will be given time boxes, typically 2 to 3 weeks, and they will sit down and create what is called a sprint plan by looking at the number of user stories they have, the size of their squad, how many they can get done within 2 to 3 weeks, and they will plan perhaps the next 3 or 4 time boxes. As they go through the process of developing, testing and putting into production they may need to make adjustments in order to meet that 2 to 3-week period, either by bringing some forward if they’re doing well and ahead of schedule or pushing a couple back to the next sprint if there’s been a delay.

This method enables us to have defined deliverables that can easily be changed. Now, why is that valuable? Ask yourself – how many times have you expected your next-year’s budget to be changed after 3 months, or 6 months, or 9 months? How many times has that happened to you in the past? By using these Agile methods, the ability to chop and change means that you can better control your budgets in a very volatile world, and let’s face it, the world has changed.

Technical vs. Fundamental Analysis: A Quick Distinction

Strictly technical traders focus on price history, chart patterns, and mathematical indicators rather than factors such as earnings, competitive positioning, or management quality. The goal is to identify trends and short-term price fluctuations that can be acted on quickly. Because these traders often hold positions for short periods, they pay close attention to support and resistance levels—price points where a stock has historically bounced or reversed.

Ichimoku Cloud: Span A vs. Span B

The Ichimoku Kinko Hyo (often shortened to Ichimoku Cloud) is a comprehensive indicator that plots several lines on a price chart. Two of the most watched are Span A and Span B, which together form the “cloud” (also called the Kumo).

• Span A is the midpoint of the Conversion Line and the Base Line, plotted 26 periods ahead.
• Span B is the midpoint of the highest high and lowest low over the past 52 periods, also plotted 26 periods ahead.

When Span A is above Span B, the cloud is colored green, which many traders interpret as a bullish signal—suggesting that upward momentum may be building. When Span B is above Span A, the cloud turns red, indicating a potentially bearish environment. Price trading above the cloud is generally considered bullish; price below the cloud is considered bearish.

Commodity Channel Index (CCI)

The Commodity Channel Index was originally developed by Donald Lambert for commodity markets but has since become a popular equity indicator. The CCI measures the difference between an asset’s current price and its historical average price, normalized by mean deviation.

Key interpretation guidelines:

• The indicator oscillates above and below a zero line.
• Readings typically stay within a range of -100 to +100 during normal market conditions.
• A reading above +100 may signal overbought conditions.
• A reading below -100 may indicate oversold territory.
• Readings between -100 and +100 are generally considered neutral.

Traders often combine CCI readings with trend direction to decide whether an extreme reading represents a reversal opportunity or simply a continuation of a strong trend.

Relative Strength Index (RSI)

The RSI is a momentum oscillator created by J. Welles Wilder, first introduced in his 1978 book New Concepts in Technical Trading Systems. It measures the speed and magnitude of recent price changes to evaluate whether an asset is overbought or oversold.

RSI ranges from 0 to 100:

• Readings above 70 are commonly interpreted as overbought.
• Readings below 30 are commonly interpreted as oversold.
• A reading near 50 suggests roughly balanced momentum.

The 14-period RSI is the most widely used setting, but traders also monitor shorter periods such as 3-day and 7-day RSI for near-term momentum shifts. Shorter RSI periods are more sensitive to recent price changes and will signal overbought or oversold conditions more frequently, while longer periods smooth out the data and generate fewer signals.

The RSI is calculated based on the average gain versus average loss over the chosen period, using closing prices. It is displayed as a line chart beneath the main price chart, making it easy to spot divergences—situations where the RSI moves in the opposite direction of price, which can sometimes foreshadow a reversal.

Moving Averages: 50-Day and 200-Day

Moving averages smooth price data to reveal the underlying trend direction. Two of the most commonly watched are the 50-day moving average (MA) and the 200-day MA.

• The 200-day MA is used to assess the long-term trend. Price consistently above the 200-day MA is generally considered a bullish sign.
• The 50-day MA provides a medium-term view and is often used alongside the 200-day to identify crossover signals.
• A Golden Cross—when the 50-day MA crosses above the 200-day MA—is widely considered a bullish signal.
• A Death Cross—when the 50-day MA crosses below the 200-day MA—is generally interpreted as bearish.

Traders may also watch the 20-day MA for shorter-term trend insights, particularly in fast-moving markets.

Average Directional Index (ADX)

Also developed by J. Welles Wilder, the ADX measures the strength of a trend—not its direction. It is plotted as a single line ranging from 0 to 100.

• Below 20: Suggests no discernible trend; the market may be ranging.
• 20–25: A borderline zone; the trend signal is not yet clear.
• Above 25: Generally indicates a strong trend is in place.
• Above 40–50: Indicates a very strong or extreme trend.

A rising ADX line means the existing trend—whether up or down—is gaining strength. A falling ADX line suggests the trend is weakening. The ADX itself does not indicate whether the trend is bullish or bearish; it must be read alongside directional indicators (the +DI and -DI lines) for that information.

Williams %R

Developed by Larry Williams, Williams %R is a momentum indicator that compares a closing price to the high-low range over a specified period (commonly 14 days). It is designed to identify when a security may be approaching an overbought or oversold extreme and could be due for a reversal.

Williams %R oscillates between 0 and -100:

• Readings between 0 and -20 are generally considered overbought.
• Readings below -80 are generally considered oversold.
• The further the reading is from the center, the more extreme the condition—and potentially the more likely a reversal could occur.

Like all oscillators, Williams %R works best in ranging markets. In strongly trending markets, overbought and oversold readings can persist for extended periods without producing a reversal, so traders typically use it in combination with a trend indicator such as ADX.

Combining Indicators: A Practical Approach

No single indicator tells the complete story. Experienced technical traders typically combine multiple signals to improve the reliability of their entries and exits:

• Use ADX to confirm whether a trend is strong enough to trade directionally.
• Use moving averages to determine overall trend direction.
• Use RSI or CCI to identify momentum and potential turning points within the trend.
• Use Williams %R to spot short-term overbought or oversold extremes.
• Use Ichimoku Span A/B for a multi-dimensional view of support, resistance, and trend bias.

Beginners are generally advised to master two or three indicators before adding more. A crowded chart with conflicting signals can create more confusion than clarity. Starting with a trend indicator and a momentum oscillator is a common and practical approach.

Final Thoughts

Technical indicators are tools, not guarantees. Each of the indicators covered here—Ichimoku Spans, CCI, RSI, ADX, and Williams %R—offers a different perspective on price behavior. Understanding the theory behind each indicator, including its strengths and limitations, helps traders apply them more effectively and avoid over-relying on any single signal. As with any trading methodology, risk management and position sizing remain critical regardless of how compelling the technical setup appears.

Overview

TFS Financial Corporation (NASDAQ: TFSL) and Old Second Bancorp Inc. (NASDAQ: OSBC) are both participants in the Regional – Midwest Banks sector. Despite operating in the same regional banking space, the two companies present notably different financial profiles across valuation, profitability, risk, dividends, analyst coverage, and share ownership. This article breaks down those differences across each dimension to give investors a clear, side-by-side picture.

Valuation and Earnings

The table below compares gross revenue, price-to-sales ratio, net income, earnings per share (EPS), and price-to-earnings (P/E) ratio for both companies.

TFSL generates significantly higher gross revenue than OSBC, but OSBC delivers a higher EPS ($1.09 vs. $0.30). This apparent paradox is explained by share count: TFSL has a much larger share base, which dilutes per-share earnings. TFSL also trades at a substantially higher P/E ratio (56.63 vs. 11.81), making it the more expensive stock by that measure. OSBC’s lower price-to-sales ratio of 3.01 compared to TFSL’s 15.86 further reinforces that OSBC is valued more conservatively relative to its revenue.

Profitability

The profitability comparison covers net margins, return on equity (ROE), and return on assets (ROA).

Net margins are nearly identical between the two companies (roughly 26.7%). However, OSBC demonstrates meaningfully stronger capital efficiency. Its ROE of 14.7% is more than three times that of TFSL’s 4.7%, and its ROA of 1.2% is double TFSL’s 0.6%. These metrics suggest OSBC is generating more profit per dollar of equity and assets — a sign of stronger operational efficiency relative to its balance sheet size.

Volatility and Risk

Beta is a common measure of a stock’s price volatility relative to the broader market (S&P 500). A beta below 1.0 indicates lower volatility than the market.

• TFS Financial Corporation (TFSL): Beta of 0.21, indicating approximately 79% less volatility than the S&P 500. TFSL is a relatively stable, low-movement stock.
• Old Second Bancorp Inc. (OSBC): Beta of 0.96, indicating price movement very close to the broader market — approximately 4% less volatile than the S&P 500.

TFSL’s very low beta may reflect its mutual holding company structure and conservative lending focus, which tend to insulate the stock from broader market swings.

Dividends

• TFS Financial Corporation (TFSL): Annual dividend of $0.92 per share, representing a dividend yield of approximately 5.17%.
• Old Second Bancorp Inc. (OSBC): Annual dividend of $0.04 per share, representing a dividend yield of approximately 0.31%.

TFSL offers a substantially higher dividend yield, which may appeal to income-focused investors. OSBC’s minimal dividend suggests the company prioritizes retaining capital for growth or balance sheet strength over returning cash to shareholders.

Analyst Ratings

TFSL carries no active analyst coverage at the time of this comparison, which is not uncommon for companies with a mutual holding company structure and limited institutional trading interest. OSBC holds one Buy rating, with an analyst price target of $15.00 — implying a potential upside of approximately 21.16% from the price at the time of writing.

Institutional and Insider Ownership

• TFS Financial Corporation (TFSL): Institutional ownership at approximately 93%; insider ownership at roughly 0.3%.
• Old Second Bancorp Inc. (OSBC): Institutional ownership at approximately 67.6%; insider ownership at roughly 2.6%.

TFSL’s very high institutional ownership reflects the fact that most of its public float is held by large asset managers, pension funds, and similar entities. OSBC’s higher insider ownership (2.6% vs. 0.3%) can be interpreted as a sign that management has meaningful skin in the game, which is often viewed favorably by investors aligned with long-term value creation.

Price Performance

The table below shows rolling price performance across multiple timeframes as of late June 2019.

TFSL showed positive price momentum across all measured timeframes, with a one-year gain of approximately 14.32%. OSBC, by contrast, posted negative returns across the same periods, declining roughly 11.75% over the prior year. This divergence in price trend — TFSL bullish, OSBC bearish — is a significant contrast given their similar net margin profiles.

Company Background: TFS Financial Corporation

TFS Financial Corporation is the holding company for Third Federal Savings and Loan Association of Cleveland, one of the largest thrift institutions in the United States. The company focuses primarily on residential real estate mortgage loans and retail savings deposits. Its product lines include:

• Savings accounts, checking accounts, certificates of deposit, IRAs, and other qualified plan accounts
• Residential real estate mortgage loans, residential construction loans, and home equity loans and lines of credit
• Net lease transactions on commercial buildings
• Escrow and settlement services
• Reinsurance of private mortgage insurance on residential mortgage loans

The company operates through its main office in Cleveland, Ohio, along with 38 full-service branches and 8 loan production offices across Ohio and Florida. Founded in 1938 and headquartered in Cleveland, TFS Financial Corporation is a subsidiary of Third Federal Savings and Loan Association of Cleveland, MHC.

Summary

These two Midwest regional banks offer contrasting investment profiles. TFSL is a large, low-volatility thrift with high institutional ownership, a strong dividend yield, and positive price momentum — but trades at a premium valuation and shows weaker capital efficiency. OSBC is a smaller community bank with stronger ROE and ROA, more competitive valuation multiples, and meaningful insider ownership, but has experienced negative price momentum and offers a minimal dividend. Investors should weigh these factors alongside their own risk tolerance and investment objectives, and consult current financial data before making any decisions.

All financial data cited in this article is sourced from stocksbeat.com and reflects figures available as of June 2019. This article is for informational purposes only and does not constitute investment advice.

A financial services company will retrain its help desk staff to be app developers and SREs, while AI handles the grunt work for the company’s call center employees.

Software-based automation of menial tasks will pave the way for more meaningful work among IT ops pros at a financial services company.

Until 2018, IT ops teams at Freedom Financial Network, a 17-year-old financial services company focused on consumer debt reduction, were largely focused on help desk tasks for the company’s 2,200 call center employees. The company had also made some progress in cloud migration and the adoption of Agile and DevOps practices, but wanted to take a more automated approach to its everyday IT tasks and rethink how it assigned its employees.

“Having people do application support and begin SRE training changes the game versus paying people $22 an hour to answer the phone and open ServiceNow tickets,” said Mark Tonnesen, CIO at Freedom Financial, headquartered in San Mateo, Calif.

Tonnesen said he briefly considered AI help desk features from ServiceNow and AIOps software from Moogsoft, but heard word-of-mouth recommendations from other CIOs about a stealth startup called Moveworks. The company, officially launched in April 2019, was founded by former Google employees that specialized in natural language processing at the web giant.

The SaaS-based Moveworks AI help desk software integrates with Slack, Microsoft Teams and other ChatOps services, along with email. It interacts with Freedom Financial’s call center employees through chatbots and email conversations, and processes their help desk requests through an AI-driven probabilistic decision engine.

“There are a lot of help desk automation tools on the market that do things like password resets,” Tonnesen said. “But they usually still require people on the back end.”

Since it implemented Moveworks in 2018, Freedom Financial has automated between 15% and 20% of its help desk tasks, and hopes to automate 25% to 30% by the end of 2019. At the same time, it will rework its IT ops teams and retrain them.