Category: Uncategorized

Why Strategic Administration Matters

Administration is often viewed as a support role focused on daily operational tasks such as scheduling, record keeping, and compliance. While these functions remain critical, a modern administrative strategy elevates this work into a driver of organizational culture and employee satisfaction.

Strategic administration:

• Reduces operational friction
• Enhances communication between teams
• Supports leadership decision-making
• Strengthens employee trust in organizational systems

By reframing administration as a strategic enabler rather than a back-office function, organizations align HR and administrative activity with broader business goals.

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Optimizing Recruitment and Onboarding Experiences

Attracting top talent begins with efficient administrative systems that streamline the recruitment process. Strategic administration ensures that candidate communication is timely, interviews are coordinated without redundancy, and onboarding processes are clear and welcoming.

Key actions include:

• Structured candidate tracking and feedback processes
• Digitized onboarding documentation and compliance checks
• Clear communication checkpoints throughout onboarding

These processes not only improve the candidate experience but also make new hires feel supported from day one, which positively impacts early engagement and reduces early turnover.

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Enhancing Employee Engagement Through Administrative Support

Employee engagement is a systemic outcome—not an isolated HR initiative. Administrative systems play a significant role in creating predictable, transparent employee experiences. For example:

Performance Evaluation

A systematic process for performance evaluation that is fair, transparent, and frequent fosters employee trust and performance motivation. Administrative professionals ensure that evaluation cycles are properly scheduled, data is collected accurately, and feedback is communicated effectively.

Career Development and Training

Administrative structures help facilitate career development through effective scheduling, tracking training outcomes, and maintaining accessible employee development records. When employees can see their progress and opportunities for growth, engagement increases.

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Administrative Systems and Remote Work Support

Remote work has redefined workplace structures. Administrative professionals now coordinate policies that balance flexibility with accountability—ensuring that remote teams remain connected, productive, and engaged.

Key administrative supports include:

• Remote scheduling systems
• Online collaboration platforms
• Structured protocols for remote reporting and feedback

These systems mitigate the isolation of remote work and reinforce organizational norms even when employees are distributed geographically.

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Building a Healthier Workplace Culture

A healthy workplace culture is one where employees feel valued, respected, and fairly treated. Strategic administrative practices contribute to culture building by ensuring:

• Consistent enforcement of workplace policies
• Diversity and inclusion considerations in HR processes
• Transparent communication regarding changes in policy or benefits

Administrative professionals often serve as the bridge between management intentions and employee perceptions—translating policy into action.

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Reducing Turnover Through Retention-Focused Administration

High turnover not only disrupts operations but also increases recruitment and training costs. Administrative systems can reduce turnover by supporting retention strategies such as:

• Exit interview analysis to identify systemic issues
• Structured career and skill development paths
• Recognition and reward programs integrated into HR workflows

Analyzing turnover data through administrative reporting systems helps leaders make informed decisions that improve employee retention.

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Performance Metrics and Administrative Reporting

Data-driven decision making is now central to competitive advantage. Administrative professionals are custodians of key performance metrics related to employee satisfaction, attendance, training outcomes, and performance reviews.

When HR teams work in partnership with administration to:

• Collect accurate data
• Design performance dashboards
• Present insights to leadership

organizations gain visibility into operational issues and can respond proactively.

This alignment also supports strategic confidence and accountability across departments, enabling smarter planning and execution.

Why Employee Experience Starts with Efficient Administrative Systems

The benefits of digital transformation have been clear for years: efficiency, organizational agility and transparency, which, in turn, can foster trust, customer satisfaction and growth. And yet, when it comes to the embrace of modern, cloud-based platforms, finance departments have tended to be laggards, not leaders. That’s changing, as more and more CFOs are realizing the benefits of modernizing their companies’ payments.

Colin Anderson, the founding partner of Friends & Family Capital and former CFO of Palantir Technologies, recently spoke with Modern Treasury about why CFOs should be champions of digital finance transformation, even in today’s tumultuous economy. Disruption, he says, is happening one way or another. The question is: will you disrupt, or be disrupted?

What’s the biggest challenge facing CFOs today?

First and foremost, a key priority and constant challenge for CFOs is creating legibility into and understanding of what’s actually happening in their businesses. One of the beautiful things about finance is that no matter what the atomic units of your business, at some point there will be a translation into a number or metric, typically as a transaction, collection or payment. At a basic level, customers should only pay you if you create value for them. The way your business shares in that value creation is by collecting cash from your customers. The way you know where your business is investing is by looking at your bills.

Connecting all those dots is literally one of the main challenges, and ties into payment operations. Do you have legibility into everything that’s happening in real time?

Do I have the cash where it needs to be to meet my obligations? Am I supporting all of my customers in the way they need to be supported? Am I getting paid by the people who need to pay me? Do business operators have confidence that their teams are investing in the right areas? From the seat of the CFO, a first order approximation that can answer these questions really comes through having the legibility to follow the money.

How does legibility relate to managing for growth and scale?

I tend to follow simple models because you can remember them as complexity grows. One simple model we used inside Palantir through periods of rapid growth was that of an accelerating train. Here your company is the train, and it’s traveling faster and faster. Your job as a CFO is not just to make sure it’s in motion, but also to look ahead and ask yourself some important safety questions. How far down the track can you see? Is there an obstruction? If so, what are your options? Do you have the levers to slow the train down or to switch to a different track? Do you need to build a bridge? Will you need to do something crazy like turn the train into a plane to fly over an obstruction or chasm? Using these first principles questions can help you stay above all the noise that you’re constantly bombarded with when you’re a CFO.

So as you scale, keep answering those fundamental questions: Do I have money? Is it safe? How do I know it’s safe? What’s it invested in? On the payment operations side, is my money sitting with me until it goes out? Or is it sitting with a third party until it goes out? Do you have faith in that third party? If you’re getting payment data as the lifeblood of legibility of your business, how far in advance can you see with it? Do you have a week of forecasting and parameterization? A month? A year?

It’s about constantly extending your thinking, or—in the train metaphor—extending your visibility. And then considering how to react and respond.

How can technology enable digital finance transformation?

Technology is a force multiplier to humans, especially at scale. Software can handle data very, very quickly and accurately. So let a computer do that. And let humans do what they’re best at in the world, which is looking at the broader context and trends, and examining whether things make sense. Answering fundamental “why” questions is not a strength of computers today. That’s for humans.

Think about embedded payments, for example. They can unlock members of a finance, accounting or product team from having to do rote processes where computers may be best. And that, in turn, empowers those teams to think about the bigger picture. It’s up to humans to figure out processes and ask questions: Are my workflows connected in the right way? Why are we doing this? For what purposes and under what conditions? That’s what humans should focus on: the higher order piece. And when it comes to payment matching ledgers, let technology, embedded payments, solve it.

With this technology, you can run faster, you can do things more safely, with fewer errors, and your team is going to be happier. You’ll have fewer fire drills when something goes wrong. You can focus on the “why.”

Why Digital Transformation in Finance Should Start with Visibility

Digital onboarding revolutionizes the onboarding of new employees: efficient, location-independent and structured. It replaces time-consuming, manual processes with smart tools and creates seamless integration – perfect for the requirements of the modern working world. But how exactly does it work and what advantages does it offer?

Why Digital Onboarding is Essential

Digital onboarding is transforming the way companies integrate new employees. By automating administrative tasks, it saves time, improves efficiency, and allows employees to get started quickly. With the right tools, companies can streamline the onboarding process and provide a consistent, engaging experience, regardless of the employee’s location.

Benefits of Digital Onboarding

Efficiency and Time Savings

Digital onboarding automates repetitive tasks like document management, contract signing, and training modules, saving HR teams significant time. New hires can access important materials and complete necessary tasks before their first day, speeding up the overall process.

Location Independence and Flexibility

Digital onboarding can be done anywhere, making it perfect for remote or hybrid work models. Employees can complete onboarding at their own pace, accessing materials as needed, ensuring a flexible work-life balance.

Consistency and Automation

Digital tools ensure that all new hires receive the same information and follow a structured process. Automation helps minimize errors and ensures smooth operations.

Improved Employee Experience

A well-organized digital onboarding process makes a strong first impression. Studies show that companies with strong onboarding programs see higher employee retention rates—up to 82% according to Glassdoor (2021).

Data-Driven Optimization

Onboarding tools provide valuable insights into how employees are progressing. This data helps companies identify areas of improvement and make necessary adjustments.

Features of a Digital Onboarding Tool

Centralized Document Management

Digital onboarding platforms store contracts, policies, and other essential documents, allowing employees to sign them electronically, reducing paperwork.

Interactive Training Modules

E-learning platforms provide interactive training on company culture, job-specific skills, and compliance topics. These modules improve engagement and retention.

Personalized Onboarding Plans

Onboarding tools allow for the creation of customized onboarding plans, ensuring new employees have a clear structure and milestones to follow.

Feedback and Monitoring

Tools offer built-in feedback mechanisms, so HR teams can track progress and make adjustments where needed.

Communication Platforms

Integrated messaging and video call functions help employees feel connected and engaged with the team, even in remote work environments.

Why Digital Onboarding is Essential for First-Day Employee Productivity

The hidden costs of poor data quality

The effects of poor data quality are often invisible, but devastating. Studies show that companies lose between 15% and 25% of their annual revenue due to poor data quality. For a company with €500 million in revenue, this means potential losses of €75 to €125 million annually.

These losses arise from:

• Bad decisions at the top: When board members and CEOs make plans based on wrong info, it can mess things up for years.
• Inefficient processes: Employees spend up to 50% of their time cleaning and validating data instead of performing value-adding activities.
• Compliance risks: In the DACH region, violations of the GDPR can result in fines of up to 4% of global annual revenue.
• Missed market opportunities: Companies with poor data quality react more slowly to market changes and miss out on innovative business opportunities.

Data quality as a driver of innovation

While poor data quality slows companies down, high-quality data acts as a catalyst for innovation. Here are the key areas where this effect is evident:

Artificial intelligence and machine learning

AI systems are only as good as the data they are trained with. The principle of “garbage in, garbage out” applies here in particular. Companies with high-quality, cleaned data sets can:

• Develop more accurate prediction models
• Making automation processes more reliable
• Creating personalized customer experiences
• Identify and minimize risks earlier

Real-time decisions

In today’s business world, decisions often have to be made in real time. High-quality data enables:

• Automated decision-making: Systems can respond independently to market changes if they have access to reliable data.
• Predictive analytics: Companies can predict trends and act proactively instead of just reacting.
• Operational excellence: Production optimization, supply chain management, and resource planning become more precise and efficient.

Digital Transformation

Digital transformation often fails due to poor data quality. Successful transformation projects rely on:

• Uniform data standards across all systems
• Automated data validation and cleansing
• Central data governance structures
• Continuous data quality measurements

The challenges in 2026

The coming years will bring specific challenges for data quality:

• Exponential data growth: Companies must learn not only to manage more data, but also to ensure its quality.
• Tighter regulations: The EU is working on further data regulation laws.
• More complex system landscapes: Modern companies use countless different applications. Each integration increases the risk of data quality problems.
• Skills shortage: The lack of qualified data specialists makes it difficult to set up effective data quality programs. Companies must rely on automated solutions and self-service tools.

Why Data Accuracy is Your Best Competitive Advantage in 2026

The Reality Check: Why Modern CRM Implementations Struggle

CRM implementation isn’t just about installing software; it is about changing how your business breathes. Most projects don’t fail because the “code” is broken. They fail because the human and strategic elements were ignored. 

1. Lack of Executive Sponsorship and “Champion” Buy-In

If your leadership team treats the CRM as “an IT thing,” your staff will treat it as optional. Successful projects require an executive champion who uses the tool and reinforces its importance. Without this top-down accountability, the system quickly becomes a “ghost town.” 

2. Paving Over Path-Holes: Automating Broken Manual Processes

One of the most common CRM mistakes is moving a messy, manual process directly into a digital tool. If your sales funnel is confusing on paper, automating it will only make it confusing faster. You must optimize your workflow before you digitize it. 

3. The “Garbage In, Garbage Out” Data Integrity Crisis

A CRM is only as valuable as the data inside it. Migrating thousands of duplicate, outdated, or incomplete records into a new system is a recipe for disaster. When sales reps can’t trust the phone number on a lead card, they stop using the system entirely. 

4. Feature Bloat: Overcomplicating the Minimum Viable Product (MVP)

It is tempting to turn on every bell and whistle on day one. However, overloading your team with 50 mandatory fields and complex automation usually leads to CRM adoption issues. Start with the essentials and scale complexity only when the basics are mastered. 

5. Neglecting the Human Factor: Low End-User Adoption

According to a McKinsey study on digital transformation, the “human factor” is the primary driver of project success. If the software feels like extra work rather than a helpful tool, your team will find workarounds. Adoption fails when the “What’s in it for me?” factor isn’t clearly answered for the end user. 

Why CRM Implementation Often Fails (And It’s Not About the Software).

What’s actually driving longer cycles

1. CFO involvement on every deal over $25K. Post-2022 budget tightening normalized CFO sign-off on what used to be team-level decisions. CFOs evaluate differently — they need business-case framing, not feature demos.

2. Buying committees expanded from 3-5 people to 6-10. More stakeholders, each with veto power, each requiring tailored proof points.

3. “Wait and see” is a default answer. Buyers who would have decided in Q2 are pushing decisions to Q3 to see how their own business performs. Most opportunity isn’t lost — it’s slipping.

4. AI fatigue. Buyers have heard so many AI pitches that the differentiation work required to break through has multiplied. Generic pitches don’t move; specific ROI pitches do.

What sales orgs that are winning are doing differently

1. Tighten qualification ruthlessly. If a deal can’t articulate the specific business problem it’s solving in dollar terms, it shouldn’t advance to discovery. The cycle starts being long the moment you advance unqualified deals.

2. Send the business case to the CFO before they ask for it. The deals that close faster are the ones where the rep proactively builds and delivers a CFO-ready business case in week 2 of the sales cycle, not week 8.

3. Multi-thread aggressively, but selectively. Cycles slow when champions disappear. Multi-threading isn’t about meeting more people — it’s about identifying the 2-3 stakeholders whose loss would kill the deal and proactively maintaining them.

4. Use AI for the prep, not for the relationship. AI-researched accounts, AI-drafted business cases, AI-summarized calls — all reduce rep busy-work. The relationship and judgment work doesn’t scale and shouldn’t be automated. 

Common responses that make it worse

More activity volume. “Let’s just send more emails” — if anything, this makes cycles longer because reps spread thin across more accounts. Concentrate on fewer, higher-conviction deals.

Aggressive discounting. Discounting accelerates the buyer’s perception that you’re desperate, which slows the deal. Use discounting only when there’s a specific calendar reason (year-end, fiscal close).

Replacing your CRM. A new CRM doesn’t fix slow cycles. Slow cycles are caused by qualification, business-case quality, and multi-threading discipline — none of which the CRM controls.

Why B2B Sales Cycles Are Getting Longer (And How to Fix It)

Automating EPF and SOCSO compliance is non-negotiable for business leaders because manual payroll is fraught with risks and legal liabilities. Automation guarantees 100% accurate statutory deductions, eliminates costly human errors, protects against severe penalties, and safeguards both your company’s finances and your leadership reputation.

Here is why automated compliance is a critical priority:

1. The Real Cost of Non-Compliance

Manual calculations across varying salary structures, allowances, and overtime often lead to inaccurate submissions. Statutory bodies enforce strict deadlines (usually by the 15th of the following month):

• EPF (KWSP): Late payments incur a dividend rate plus an additional 1% monthly interest. Furthermore, failure to pay or persistent defaults can lead to fines up to RM10,000 to RM20,000 per employee and imprisonment.
• SOCSO & EIS: Deducting contributions but failing to remit them is a serious offense. Late payments result in daily fines per employee, and authorities actively prosecute offending businesses.

2. Time and Productivity Gains

As your company scales—processing complex payrolls that include new hires, resignations, and unpaid leave—manual calculations become a massive administrative burden. Automated HR and payroll platforms automatically adjust to updated government requirements and securely format files for direct submission. This allows your HR teams to focus on strategic growth rather than repetitive data entry.

3. Employee Trust and Morale

Employees depend on their statutory contributions being processed accurately and on time for their future welfare and security. Automation guarantees payslip transparency, significantly lowering disputes and boosting workforce confidence.

4. Simplified Audits and Risk Management

Malaysian employment regulations mandate that businesses keep accurate payroll records for at least 7 years. Using certified, automated compliance software creates built-in, unalterable audit trails. If an audit or review is ever triggered, your platform easily generates the necessary government-approved reports.

To take the next step toward streamlining your business, you might evaluate whether an automated system best fits your setup.

Why Automated Compliance (EPF/SOCSO) is Non-Negotiable for Business Leaders.

One of the abiding urban myths that misinforms sales pipeline management is the idea that sales people need at least 3* pipeline coverage in order to achieve their quota. Where this “golden number” came from, nobody seems to know, but it’s a fair bet that it dates back beyond the Neolithic.

Another widespread urban myth is the idea that whenever you have a bigger sales pipeline, you end up selling more. It’s the sort of misconception that leads marketing teams to drive to create an ever-larger number of MQLs without any regard for how many of them ever actually result in any revenue.

The simple fact is that there is no one-size-fits-all answer to the question of what the optimum coverage ratio for any specific sales pipeline is…

In my experience, one of the things that distinguishes top sales performers from the rest is that they have too much respect for their own time to waste it pursuing opportunities that they have no realistic chance of winning – while their less-discriminating colleagues cling onto every available opportunity until long past its sell-by date, often because they misguidedly fear that qualifying out will make their pipeline look smaller.

This is not always just the sale person’s fault – sales managers are often to blame as well, by focusing more on the size of the sales person’s pipeline than the quality of the opportunities it contains.

If we’re to address this issue, we need to turn to rational methodology, and not urban myth. We need to instrument our sales pipelines so that we can identify the root causes of success and failure, and the behaviours that result in winning outcomes.

There’s a growing body of evidence to suggest that pipelines that are too large to manage are just as problematic as pipelines that don’t contain enough opportunity in the first place. For every sales environment, there is an optimal range of pipeline coverage – it just isn’t the same in every situation.

Here are a few of the factors that most commonly impact pipeline conversion efficiency:

• Type of business (new customer vs. cross-sell vs. up-sell vs. renewal)
• Type of purchase (required vs. considered)
• Complexity of selling/buying process
• Number of stakeholders involved in decision
• Deal value (and approval level required)
• Experience of sales person
• Adoption of sales process

Some of these factors impact the efficiency and predictability of the sales pipeline as a whole – others reflect predictable differences between the performances of different product offerings or even individual sales people.

Applying a single, untested (and often unmeasured) universal pipeline coverage target makes no sense at all. And with the emergence of sales analytics into the mainstream, there’s no excuse for not knowing what the real optimum target ought to be across a range of different sales scenarios.

I’ll be addressing this point in my upcoming webinar with the Association of Professional Sales on the 4^th April, on the subject “Why size isn’t everything: assessing the true value of your organisation’s sales pipeline” – you can register for the event here.

But back to that mythical 3* coverage ratio: the team at InsightSquared (the leading sales analytics platform for salesforce.com users) have done a great job of debunking the myth in this excellent article.

Their research shows that companies that emphasise quantity over quality in their sales pipelines tend to have much lower quality leads within their sales pipelines – and far lower conversion ratios. They also found that big deals (2x or more above average) tend to have lower likelihoods of closing and longer sales cycles.

Analytics can also show which sales people are more efficient than others in converting initial interest into sales action. Studying and comparing the shape of individual sales people’s funnels can highlight where some are more effective than others – and suggest ways in which targeted coaching can improve performance.

My own experience of applying sales analytics has convincingly proven that better qualified opportunities (using rational, consistent qualification criteria) have a measurably higher conversion rate and shorter sales cycles.

In fact, it’s pretty clear that the old 3* sales pipeline coverage mindset really ought to be long past its retirement date. There’s simply no excuse for not adopting a smarter, situational and evidence based approach.

Why a Clean Sales Pipeline is More Valuable Than a Large One

In today’s supply chain environment, customers expect more than on-time delivery — they expect visibility, communication, and control. As shipping networks become more complex, real-time tracking has emerged as one of the most effective tools for improving customer satisfaction across logistics operations.

Real-time shipment visibility doesn’t just show where freight is located. It reduces uncertainty, improves responsiveness, and builds trust between shippers, carriers, and end customers.

Visibility Reduces Customer Inquiries

One of the most immediate benefits of live trip tracking is a measurable reduction in customer service inquiries.

Without real-time visibility, customers often ask:

• Where is my shipment?
• Is it on schedule?
• Has there been a delay?
• When should I plan labor or receiving staff?

Live tracking answers these questions before they are asked. When customers can see shipment status, ETA updates, and alerts in real time, they don’t need to call or email for updates. This reduces inbound inquiries, lightens the load on customer service teams, and allows operations staff to focus on execution instead of status reporting.

Faster Issue Resolution Builds Confidence

Delays and disruptions happen — weather, congestion, mechanical issues, or facility bottlenecks are part of logistics reality. What matters most to customers is how quickly issues are identified and addressed.

Real-time tracking enables proactive response. When shipments go off plan, alerts allow teams to:

• Identify issues immediately
• Communicate accurate updates
• Reroute or adjust schedules
• Minimize downstream disruption

This proactive approach reassures customers that their freight is being actively managed, not passively monitored. Over time, this consistency builds confidence and strengthens long-term partnerships.

Transparency Increases Trust

Trust is earned through transparency. Customers are far more comfortable when they have access to the same information as their logistics provider.

Real-time tracking creates a shared view of the shipment lifecycle, reducing misunderstandings and setting realistic expectations. Instead of relying on estimates or manual updates, customers see accurate, data-driven information that reflects actual conditions on the road.

This transparency turns logistics from a black box into a collaborative process — one where customers feel informed and in control.

Improved Communication Drives Higher NPS Scores

Net Promoter Score (NPS) is often influenced less by perfect execution and more by communication quality. Customers may tolerate minor delays, but they react negatively to surprises or silence.

Live tracking improves communication by:

• Providing real-time ETAs
• Triggering alerts when conditions change
• Supporting consistent, proactive updates

When customers feel informed and supported, satisfaction increases — even during challenging scenarios. Over time, this leads to higher NPS scores and stronger customer loyalty.

Technology That Supports the Customer Experience

Modern logistics technology isn’t just about efficiency; it’s about experience. Real-time tracking platforms integrate data from vehicles, drivers, and systems to provide actionable insight for both operators and customers.

For shippers managing complex networks, this technology becomes a competitive advantage — enabling better planning, fewer disruptions, and more reliable service outcomes.

The Truth About Real-Time Logistics and Customer Loyalty

The Cost of Human Error

The risk of human error rises as financial institutions handle more transactions. Bad data alone costs U.S. businesses more than $3.1 trillion a year, according to a report from IBM.

Human error in the financial services sector runs the gamut from accidental “reply all” emails and coding errors to mistakes in data entry and security breaches that give bad actors access to sensitive information. According to one report, the average employee makes 118 mistakes a year.

Costs are just one measure of the impact of human error. While not all mistakes are like Citi’s $900 million blunder, even small errors can impact the bottom line. Social media can add to the financial pain by amplifying the mistakes, potentially tarnishing a bank’s reputation. Trust has always been important when it comes to money matters, but it is even more vital when customers are relying on a rock-solid firewall to keep their account and financial details safe.

Financial institutions are already fighting an uphill battle when it comes to trust, and highly visible mistakes can make matters worse. For example, in a recent study by the Reputation Institute, only two of 40 large financial institutions were ranked as “excellent.” Even more telling, from one year to the next, more than 50% of the 40 banks saw their reputation ratings decline.

AI and Automation Reduce Risk

Human error is part of the cost of doing business, but automated systems powered by artificial intelligence can help financial institutions detect mistakes before they require costly intervention.

One of the keys to reducing human error is the use of human-in-the-loop automation (HITL) systems. With a HITL system, human experts validate a machine learning model on the fly. Financial institutions interested in reducing risk can use AI and automation to analyze financial documents and data streams. This is a state-of-the-art, real-time analysis that combines machine learning with human review.

The combination of AI analysis and automation with human insight with human insight facilitates good decision-making. Automation can, for example, be used to analyze bank statements, pay stubs, photo ids, and other key documents used for loan underwriting. Companies such as Plaid and PayPal are using human-in-the-loop technology in order to make faster, smarter decisions – reducing the likelihood of human error.

Intelligent automation, now a mainstay of the financial ecosystem, is getting more efficient thanks to AI and automation. One study, conducted by the University of Nevada-Las Vegas, found that human-powered automation technology is over 20-times more accurate than old-school manual verification.

Better Accuracy, Fewer Errors with Artificial Intelligence and Automation

Today, refined machine learning algorithms are routinely used by financial institutions to either replace or complement manual processes. In addition to ensuring more accurate document and data processing, automation helps financial institutions reduce risks and improve efficiency. The automation of tasks such as cash flow analytics and document fraud detection not only minimizes errors, it frees up personnel to focus on more value-added strategic responsibilities. According to a McKinsey report, AI can potentially unlock $1 trillion of incremental value for banks.

AI and workflow automation go hand in hand in the analysis of everything – from revenue and income to financial ratios and trends. Lenders can now use the power of automated analytics to build predictive risk models that outperform existing credit evaluation metrics. Machine learning systems also can be used to identify fraud and flag transactions for deeper human scrutiny. That translates into less risk and smarter decisions.

Automation enables financial institutions to reduce overhead costs while improving security and efficiency. Machine learning, combined with human-in-the-loop review, improves business productivity and helps to increase margins while delivering friction-free customer experiences. Essentially, any business can start solving for the cost of human error with a little help from AI and automation.

Ocrolus uses HITL machine learning to train models for identifying document types, data fields, and the actual data. To learn more about how Ocrolus can help automate your processes and start reducing error, you can schedule a demo today.

The True Cost of “Human Error” in Your Financial Closing Process