1) The "Happy Path" vs. the real world

We have all seen that flowchart.

It is framed in the operations center. It is on slide 4 of the board deck. It maps "Quote-to-Bind" or "Loan Origination" in neat rectangular boxes. Step A goes to Step B, which glides into Step C.

It is beautiful.

It is also, to put it politely, a work of fiction.

If you ask a claims handler or a loan officer whether that chart matches their day, they will not nod. They will laugh. In the real world, Step A goes to "Wait three days for a missing document," then "Email Compliance," then "Re-enter data because the system timed out," and only then, if the stars align, you stumble into Step B.

This is the spaghetti reality of financial services. Legacy systems, manual workarounds, and shadow processes (those spreadsheets everyone uses but no one admits to) create an operational truth that looks nothing like the flowchart on the wall.

For COOs and Heads of Transformation, this creates a visibility gap that is genuinely dangerous:

• You know costs are too high.

• You know cycle times are drifting.

• You know customer and broker patience is getting shorter.

• You suspect that half your "exceptions" are self-inflicted.

But you cannot fix what you cannot see.

It is time to turn on the lights.

2) What is Process Intelligence? (No jargon allowed)

Forget the buzzwords. Here is the simple version.

Every time someone clicks "Approve" in a core system, updates a field in a CRM, or triggers a status change in a workflow tool, they leave a timestamped digital footprint.

Process Intelligence collects these footprints across your systems and reconstructs what actually happened:

• which steps occurred

• in what order

• how long each step took

• where work looped, stalled, or bounced between teams

• which variations create the most cost and delay

It does not rely on interviews or "how we think it works." It uses evidence from the systems that run the work.

"So is that just process mining?"

Close, but not identical.

Process mining is often used to discover and analyze process behavior from event data. Process Intelligence usually goes one step further and turns that analysis into an always-on operating capability:

• continuous monitoring, not just quarterly discovery

• early warning signals, not just retrospective reports

• action loops, not just dashboards

A useful mental model:

• Process mining helps you understand what happened and why.

• Process intelligence helps you spot what is happening now, predict what happens next, and intervene before it hurts.

The outcome you want is not a prettier diagram. It is a system that helps you run operations better on Tuesday morning, not just explain them in next month's steering committee.

3) Why financial services needs this now

You might be thinking: "We survived this long with spreadsheets and experienced people. Why the urgency?"

Because three pressures have converged, and they all punish blind spots.

Pressure 1: Alert overload in financial crime and compliance

Transaction monitoring and screening can generate huge volumes of alerts. Many institutions report that the vast majority of alerts end up being non-actionable, which means expensive teams spend their days clearing noise instead of reducing risk.

Process Intelligence helps by adding operational context. Instead of treating each alert like an isolated event, it looks at the sequence around it:

• where the alert was generated

• how long it waits in queues

• which cases bounce between levels

• which handoffs create rework

• where policies and real behavior drift apart

This does not replace your AML stack. It helps you fix the workflow around it so your compliance effort is focused where it matters.

Pressure 2: The claims and service "black hole" in insurance

In insurance operations, the most dangerous status is "Pending."

A claim can sit in suspended animation for days:

• waiting for a document

• stuck in an approval loop

• paused because the handler is out

• bouncing between teams due to incomplete intake

Without process visibility, it is all labeled "in progress."

With Process Intelligence, you can see the reason for the stall, the exact waiting loops, and the steps that create the bottleneck. Then you can fix the root cause, not just chase the symptom.

Pressure 3: Operational resilience and regulators who want evidence, not opinions

Regulators are increasingly focused on operational resilience, especially around ICT risk, third-party risk, and the ability to withstand and recover from disruptions.

That shift changes the conversation. It is no longer enough to say "we have a policy." You need to show how processes behave in practice, how incidents are handled, and where dependencies create risk.

Process Intelligence provides operational "ground truth" that supports resilience programs with measurable evidence:

• where critical services slow down under stress

• what fails first when systems or vendors degrade

• how long recovery really takes in practice

• where manual workarounds become systemic risk

Confirm your regulatory requirements with your compliance and legal teams, but the direction is clear: resilience needs proof.

Pressure 4: Payments has become a frontline product (not a back-office utility)

This is the part many organizations underestimate.

In banking and payment service providers, payments is not just "processing." It is customer experience, revenue, risk, and reputation in one pipeline.

Payments operations face a brutal combination:

• high volume, low margin

• real-time expectations

• complex exception scenarios

• disputes and fraud pressure

• strict SLAs and scheme rules

• a customer base that will abandon a transaction if it feels slow or uncertain

And here is the trap: most of the cost is not in the happy path. It is in the exceptions.

If you cannot see where exceptions come from, you end up staffing for chaos. If you can see it, you can engineer it out.

4) Banking and payments (PSP) use cases that show real money

These are example scenarios based on patterns we repeatedly see in banking and PSP operations. Your numbers will vary, but the mechanics are consistent.

Use case A: The "decline mystery" and lost revenue you never see

The symptom

Your payment success rate drifts down. Conversions drop. Customer support tickets go up. Everyone argues about whether the problem is issuers, fraud rules, or a specific payment method.

The hidden reality

Declines are not random. They cluster by:

• country and issuer

• merchant category or risk profile

• authentication flow

• time of day

• specific routing paths or gateways

What Process Intelligence reveals

A clean map of the real journey: where the payment fails, which step triggers the failure, and what path leads to a successful retry. You can see:

• which decline reasons are operationally recoverable

• where manual reviews create delay and abandonment

• which flows are "false declines" created by policy or workflow design

What improves

• higher authorization and completion rates

• fewer avoidable retries and support tickets

• a clearer playbook for tuning controls without increasing fraud

Use case B: Chargebacks and disputes as a factory, not a fire drill

The symptom

Disputes are handled like emergencies. Teams jump between tools. Documentation is inconsistent. Case outcomes vary by who picked up the file. Costs are high and merchants are unhappy.

The hidden reality

Disputes have loops:

• missing evidence creates back-and-forth

• timelines slip due to handoffs

• the same root cause triggers repeat chargebacks

• case management becomes "chase the deadline"

What Process Intelligence reveals

• where cases get stuck (intake, evidence collection, review, submission)

• which merchants or products generate repeatable patterns

• which evidence types correlate with win rates

• where automation would remove manual bottlenecks

What improves

• faster dispute cycle time

• more consistent outcomes

• lower operational cost per dispute

• root-cause fixes that reduce repeat disputes, not just manage them

Use case C: Refunds, reversals, and the "where is my money?" support tsunami

The symptom

Refund and reversal inquiries flood contact centers. Customers are angry because "it says refunded" but the money is not visible. Your teams spend hours doing investigation work that does not generate revenue.

The hidden reality

Refund journeys often cross multiple systems and parties. Delays come from:

• inconsistent status updates

• manual approvals

• batching behavior

• breaks in reconciliation

• missing reference data that forces investigation

What Process Intelligence reveals

A single end-to-end view of:

• how long refunds truly take by type and route

• which steps create the longest waiting time

• which exceptions cause the most investigations

• where customer communication triggers avoidable tickets

What improves

• fewer investigation cases

• lower support volume

• more predictable refund SLAs

• better customer trust, which is rare and valuable

Use case D: Exceptions and investigations in payments operations

The symptom

A growing investigation backlog. Too many "repair" cases. A team of smart people spending time on detective work instead of value.

The hidden reality

Exceptions explode when data is incomplete or inconsistent. Investigations are often triggered by:

• missing or mismatched references

• status mismatches between parties

• unclear fee or FX components

• formatting differences across messaging standards

• inconsistent enrichment and validation rules

What Process Intelligence reveals

• the most common exception types and their origins

• the process variants that create investigations

• which upstream step would prevent the downstream break

• where standardization would remove entire classes of repairs

What improves

• higher straight-through processing

• lower cost per investigation

• less operational risk

• fewer customer-impacting delays

Use case E: Merchant onboarding and KYB, where revenue gets stuck at the front door

The symptom

Your pipeline looks great, but activation is slow. Sales says "we signed them." Operations says "we are waiting on documents." Risk says "we need more checks." Merchants disappear.

The hidden reality

Onboarding is full of loops:

• repeated document requests

• inconsistent requirements by segment

• manual reviews routed to the wrong queue

• unclear ownership and SLA enforcement

What Process Intelligence reveals

• where onboarding cases stall and why

• which steps cause rework

• which rules are applied inconsistently

• which segments need a simplified, standardized path

What improves

• faster time-to-live for merchants

• lower onboarding cost per merchant

• fewer drop-offs and better revenue realization

• cleaner risk controls because work is structured, not improvised

5) "Wow" stories across insurance, banking, and payments

Theory is nice. Outcomes are nicer.

These are example scenarios based on common patterns we uncover when process visibility becomes real.

Story 1: Insurance, the looping claim

Symptom: cycle time drifts, NPS takes a hit, teams feel busy but outcomes do not improve.

What the data reveals: a large share of claims bounce between front office and back office multiple times due to one missing field or an inconsistent intake step.

Fix: make intake validations smarter, eliminate the missing field scenario, and automate nudges that keep claims moving.

Result: fewer loops, fewer touches per claim, faster settlement, happier customers, less internal frustration.

Story 2: Lending, the mortgage maze

Symptom: time-to-offer lags behind fintechs and conversion drops during long waits.

What the data reveals: officers re-check data already validated, often due to low trust in legacy systems or unclear UI status.

Fix: improve visibility ("verified" status), simplify decision handoffs, retrain teams to remove unnecessary rework.

Result: faster offers, fewer redundant checks, smoother customer experience without reducing risk controls.

Story 3: PSP, the duplicate payout leak

Symptom: leakage from duplicates, reversals, and "pay-and-chase" recovery.

What the data reveals: specific patterns where duplicates slip through, often due to inconsistent identifiers or repeated submissions.

Fix: targeted controls and automated alerts that catch the pattern before release.

Result: reduced leakage, fewer exceptions, less recovery work, cleaner operations.

Story 4: PSP, the chargeback loop that never ends

Symptom: disputes rise, cost per dispute rises, and the team lives in deadlines.

What the data reveals: a subset of disputes repeatedly fail due to missing evidence, and the same product flow creates recurring disputes.

Fix: standardize evidence intake, automate reminders, and fix the root journey that triggers disputes in the first place.

Result: faster handling, fewer repeat disputes, better merchant satisfaction.

Story 5: Bank payments, the investigation backlog

Symptom: investigations take too long and spill into customer service.

What the data reveals: a handful of upstream data issues create a majority of downstream investigations.

Fix: improve validation and enrichment at the point of origin, standardize exception routing, and monitor investigations as a live operational KPI.

Result: fewer cases, faster resolution, less noise, more trust.

6) The AI connection: you cannot automate a mess

Every board is asking: "What is our AI strategy?"

There is a rush to deploy AI agents in customer service, underwriting, claims, and payments operations. But here is the hard truth:

If you deploy AI into a broken, undocumented process, you do not get efficiency. You get automated chaos, faster.

AI needs:

• a validated process map

• clear decision points and exceptions

• consistent data definitions

• reliable handoffs and outcome tracking

Process Intelligence gives you the ground truth. It turns "we think this is how work happens" into "this is how work actually happens." That is the difference between AI that helps and AI that creates new problems at high speed.

7) Meet Beakwise and QAD Process Intelligence: the live control tower

At Beakwise, we are technology-agnostic, but opinionated about what works in real operations.

We partner with QAD Process Intelligence (formerly LiveJourney) because it addresses the biggest limitation of traditional approaches: latency. Many tools tell you what went wrong last month. That is useful, but it is late.

QAD Process Intelligence is designed to act more like a live control tower:

• Real-time monitoring: see bottlenecks and deviations as they form, not after the damage is done.

• Predictive simulation: run "what-if" questions before you make changes, so decisions are based on data, not hope.

• Action enablement: trigger alerts and integrate interventions, so insight turns into improvement, not another slide.

8) The Beakwise difference: from insight to action

Buying a stethoscope does not make you a doctor. Buying process tooling does not fix operations. It shows you where it hurts.

Beakwise bridges the gap between "knowing it is broken" and "fixing it for good."

Our approach is built to move from diagnosis to delivery:

Diagnose

We implement QAD Process Intelligence to build an objective view of your current state:

• bottlenecks

• loops

• handoff friction

• compliance and resilience risk hotspots

Design

Our business architects translate the evidence into an optimal "to-be" model:

• redesigned workflows

• simplified handoffs

• clear exception management

• measurable controls

Deliver

We do not stop at recommendations. We build the change using our delivery capabilities, including orchestration and workflow execution through the Beaksurance ecosystem where appropriate. The goal is not insight. The goal is outcomes.

9) What usually goes wrong (and how to avoid it)

Process Intelligence delivers value fast, but only if you avoid three common traps.

Trap 1: Turning discovery into a reporting project

If your output is a monthly PDF report, you will not change operations. You will just document the pain more accurately.

Avoid it by: tying findings to an action plan, owners, and measurable KPIs (touch count, cycle time, rework rate, SLA breach risk).

Trap 2: Fixing symptoms instead of loops

Teams often chase visible backlog instead of removing the loop that creates the backlog.

Avoid it by: prioritizing loop elimination, intake quality, and exception routing before "more headcount."

Trap 3: Creating a dashboard no one owns

If no one owns the process, the dashboard becomes a spectator sport.

Avoid it by: assigning process owners, defining control thresholds, and embedding monitoring into daily operating rhythms.

10) Conclusion: turn on the lights

The era of managing by best-guess is over.

Complexity is higher. Regulation is stricter. Competitors move faster. Customers and partners are less patient. Operating in the dark is now an expensive habit.

You already have the data. You just need the lens to see it.

Stop arguing about whose version of the process is correct. Let the process tell you the truth.

Ready to see your business as it actually runs?

Let's turn the lights on in your back office.

Book a Process Discovery Workshop with Beakwise