Best debt collection software in Colombia 2026: technical comparison

Quick answer

If you want a single answer, this is the most honest one:

• Among the official sources of these seven providers reviewed through July 27, 2026, Colektia published the largest-scale comparative case we found for mass-market collections.
• Moonflow has a broad SaaS offering, public pricing and well-documented text and voice agents.
• Debitia and Intiza bring maturity, accounts-receivable processes and regional experience.
• Giitic stands out for modular breadth, mobility and enterprise integrations.
• PorCobrar has a clear fit for invoicing, payments and reconciliation within the Mexican ecosystem.
• Certeza is our editorial fit recommendation for Colombian organizations that don't want to merely license a tool: they need specialized agents, accompanied operation, obligation-level control, payment reconciliation and a commercial structure potentially aligned with recovery, subject to evaluation and contract.

That doesn't mean Certeza has more years, more clients or more published certifications than everyone else. It means that, for that specific problem, it combines capabilities that normally force you to hire and coordinate several pieces: software, conversational automation, collections operation, promise tracking, reconciliation and exception review.

Editorial disclosure: Certeza publishes this guide and appears among the analyzed alternatives. We are not an independent outlet. We contrasted the official sources of each provider consulted through July 27, 2026, and reviewed Certeza's implementation at a level of detail that is not available for its competitors. That is why we always distinguish between what is publicly stated, what is observed in the product, and what still has to be proven in a comparable pilot.

The standard almost no "best debt collection software" list meets

In software marketing, most "Top 6" or "Top 10" rankings are search-ranking contests, not technical audits: the one who invests most in content and links tends to appear first, not the one who recovers debt best. The list published by Colektia, which places its own product in first place, is just one example of a common practice across the entire sector. We don't single it out as an exception: we use it to show what the industry standard is missing.

It is legitimate for a company to explain why it considers its solution strong. What none of these lists allows you to conclude is that a general winner exists, because they almost never publish:

1. how the six participants were chosen;
2. what weight each criterion received;
3. which features were verified and which were taken from a marketing page;
4. how SaaS products, managed operations and enterprise suites were compared;
5. what portfolio, country, volume and delinquency bucket the comparison represents;
6. how much it costs to obtain the result;
7. what errors, complaints or human interventions occurred;
8. how the naturalness, accuracy and consumption of the AI agents were measured.

"Most innovative" is a value judgment. "Up to 25%" is an observed maximum, not an expected result for any portfolio. Having WhatsApp, email and voice shows channel availability, but does not prove they are coordinated. Showing a payment link doesn't prove the system can correctly reconcile a partial payment, a duplicate or an incomplete reference.

A useful comparison should not reward vocabulary. It should follow the money and the real states of the obligation.

What a finance leader actually buys when buying collections

A company does not buy messages sent. It buys a controlled improvement in cash:

• recovering more than it would have recovered without the intervention;
• recovering sooner;
• reducing the cost per peso recovered;
• reducing debt that migrates to worse delinquency buckets;
• avoiding wrong contacts or contacts after payment;
• knowing what was promised, what was kept and what a person must review;
• correctly applying the payment to the obligation;
• keeping evidence to respond to the client, an audit or management.

That is why the unit of reporting should not be "number of automations." It should include the resolved and reconciled obligation, with its cost and its contact experience. Experimental assignment, however, must be done per person, company, resident or household: splitting obligations of the same debtor across providers would contaminate the test and could duplicate contacts.

A hyperspecific fit: homeowner association management (propiedad horizontal)

Large mass-market providers optimize for banking, fintech, telco and retail. That scale leaves underserved a segment where collections has its own rules: the management of residential complexes and homeowner associations (propiedad horizontal). There the problem is not sending more reminders, but absorbing a very particular operational load:

• strict control per unit or property, not just per person;
• matching manual receipts that residents send by photo or PDF;
• reconciling association fees, interest and partial agreements;
• tracking payment agreements with residents and boards;
• careful communication so as not to damage the community's coexistence.

Certeza is designed to understand those pain points: it models the obligation per unit, leaves the receipt in review when there is ambiguity and keeps the agreement alive across channels. We don't claim it is the only one able to operate this sector; we do claim that its obligation-based architecture and its conservative reconciliation fit the reality of a residential administration better than a suite designed for mass portfolios.

Proposed pilot rubric: 100 points and non-compensable filters

This is the weighting we propose to design a pilot. This article does not yet assign these 100 points to any provider, because there are not enough comparable results. Before using it, you must publish the spreadsheet, the normalization formulas, the thresholds, the treatment of missing data and N/A, the confidence intervals, the ties, the plan or package tested and the disqualification criteria. Everything must be frozen before seeing results.

There are also critical incidents that no average should hide: data leakage between clients, unequivocal disclosure of a debt to a third party, unauthorized access, a false legal threat or an unauthorized financial mutation. Other events must be measured against an SLA and their cause. For example, a contact after payment is a major failure if the platform already received the event and the agreed suppression window expired; it is not necessarily one if the bank or ERP had not yet reported the payment.

The evaluation must produce two separate results:

1. performance, calculated only with comparable pilot data;
2. evidence level, indicating how much support exists for each claim.

For the second result, use these labels:

• V1 — verified in a comparable pilot;
• V2 — verified in a demo or contractual document;
• D — publicly declared by the provider;
• NE — we found no comparable evidence;
• N/A — does not apply to the evaluated model.

"NE" does not mean a capability doesn't exist and must not become a zero or a performance penalty. The provider is left without a conclusive score on that criterion until it delivers comparable evidence.

A randomized contemporaneous control allows the strongest inference. A matched contemporaneous control is limited evidence. A historical baseline is quasi-experimental and exposed to seasonality, portfolio changes, payment means and the economic environment; it is not equivalent to a control group.

Downloadable resource — The definitive framework to audit collections software. We turned this 100-point rubric, its normalization formulas and its pilot template into a ready-to-use spreadsheet. You can request it to evaluate any provider —including Certeza— with the same rigor. Write to us to receive it in exchange for your corporate email.

Quick comparison of the seven alternatives

Public security: a starting point, not an audit

The reviewed pages let you identify statements, not certify a provider's effective security.

Not finding a certificate in the reviewed source does not mean it doesn't exist. Ask for it and confirm product, entity, period and scope; a logo or a policy is no substitute for the document.

Certeza under the same microscope

Certeza should not present itself as "another collections chatbot." The verifiable differentiation is in its operational architecture.

1. Decides the next step, not just drafts a message

The engine evaluates the state of the portfolio and can:

• schedule a contact;
• wait for an active promise;
• stop because all obligations are disputed;
• respect a pause or exclusion;
• change phase or channel;
• not schedule an action when there are no actionable obligations.

Ambiguous or sensitive cases can move to separate flows for pause, transfer and human review.

Before executing an action, it re-checks the state. This reduces the risk of sending a message that was correct when scheduled but stopped being correct after a payment, a dispute or an instruction from the team.

2. Separates conversation, analysis and mutations

This is probably the most important security differentiator in the whole analysis, and the one that should weigh most against any tool that promises "100% autonomous AI." The biggest fear when adopting AI in collections is that a model hallucination applies an unauthorized discount, forgives a debt or alters the official balance. Certeza prevents this by design:

• the live agent converses and queries context;
• a later analyzer identifies promises, disputes, receipts and other durable outcomes;
• authorized use cases validate and write changes;
• accounting and the official balance are not modified because a language model "believed it understood" something.

The agent that replies on WhatsApp cannot, on its own, change balances, apply payments, grant discounts, create legal conditions or alter the accounting record. That separation sacrifices apparent automation to gain real control.

Put directly: a language model should never have direct write permission over collections accounting without a structured validation in between. Every mutation goes through authorized, verifiable use cases, not through what a conversation "believed it understood."

3. Can retain context across enabled channels

Certeza can query a recent shared history across WhatsApp, SMS, email and calls when those channels are configured. The architecture supports continuity between interactions; this does not imply that all four channels are active for every client, nor does it by itself prove a complete omnichannel operation in production. The goal is not to repeat the same text four times. It is that the next contact can know whether the person:

• already replied;
• promised to pay;
• sent a receipt;
• reported a dispute;
• asked for another channel;
• is not the account holder;
• must be handed off to a person.

Multichannel means availability. Omnichannel means continuity and coherence.

4. Treats reconciliation as an evidence problem

A receipt is not yet an applied payment nor does it confirm the money reached the bank. Certeza can look for matches by third party, date, amount, currency, obligation and reference against payments already recorded in the accounting source. If several possibilities exist, information is missing or a duplicate appears, it avoids modifying the balance merely because it received the supporting document and leaves the case in review.

For WorldOffice there is a specialized import flow that interprets charges and receipts, relates properties and receipts and applies payments to obligations. It is not a banking API nor a native real-time sync. For Siigo, Alegra and Helisa the prudent statement is that Certeza can work with files, exports or an evaluated connection. We do not yet claim a native, bidirectional, real-time sync for the three.

5. Designs naturalness for Colombia, but doesn't declare it a winner without proof

The agent is designed to converse in Colombian Spanish with a formal, warm tone, short messages, context and handling of everyday language. Certeza has an evaluation framework whose rubric penalizes responses that are:

• robotic or unnecessarily long;
• repetitive;
• aggressive or legally fabricated;
• foreign to Colombian Spanish;
• disclosing private information;
• ignoring what the person already explained.

The framework covers promises, disputes, payments, fraud, wrong person and cases requiring intervention. It includes execution, replay, deterministic checks and an optional judge, but in this review we found no stored results or an approval rate. It shows that a methodology has been designed; it does not yet prove its performance or a victory over other agents. A protocol of 30 synthetic cases, five repetitions, hidden marks, critical-failure criteria and blind human evaluation is already defined. Superiority in naturalness must come from running and publishing that benchmark, not from the opinion of whoever built the product nor from cherry-picking a real conversation that went well.

6. Prepares AI measurement without confusing tokens with results

Certeza persists per turn the input, output and cache tokens of the WhatsApp conversational agent, plus the model, and can aggregate them without reading the message content. It also instruments traces with OpenTelemetry. However, we did not find a closed end-to-end bridge that directly links conversation, consumption, latency, later analysis, retries, tools, outcome and attributed payment. The history tokens also do not by themselves represent voice, transcription, evaluators or other inferences.

Before publishing a comparative figure we must close that key and distinguish "WhatsApp conversational agent tokens" from "total AI cost of the operation."

The metric the client buys is not "fewer tokens." It is:

AI cost per correctly resolved conversation and per peso of incremental recovery, keeping a threshold of accuracy, naturalness and compliance.

An agent may use few tokens because it lost context. Another may use many because it repeats instructions. Neither wins until it proves it resolved better and at a lower total cost.

7. Combines product and managed operation

Certeza can offer, subject to evaluation and contract, a structure with no initial fixed fee and fees on attributable recovery. It is not equivalent to free software: percentage, channel costs, taxes, portfolio, window, exclusions and reversals vary by contract.

The value of the model is alignment: the provider shares the result and an assigned Customer Success accompanies data, rules, launch and exceptions. The client's work does not disappear, but it avoids being left with a configurable platform without a responsible operation.

8. Has an early recovery signal, not yet a controlled case

Certeza reports that, in all handled cases that had completed implementation at the time of this review, it recovered at least 10% of the portfolio during the first two weeks after full go-live.

That figure is promising, but its evidence level must be clear:

• it is an internal observation declared by the company, not an independent audit;
• we still must publish the number of implementations included, the exact definition of the initial portfolio and the treatment of credits, reversals and payments already in progress;
• there is no contemporaneous control cohort that would allow claiming all that collection was incremental or caused exclusively by Certeza;
• it is not a guarantee for a new portfolio: sector, age, data quality, contactability, policy, payment means and operational capacity change the result.

The correct commercial wording is "early result observed in completed implementations," not "guaranteed recovery." The next step is to turn this signal into a reproducible case with denominator, cohort, period, applied payments net of reversals, cost and limitations.

9. States its limits

A reliable comparison also says when not to choose Certeza:

• it is a young company and has less independent public evidence;
• it has not yet published a controlled case comparable to Colektia's;
• it does not replace the ERP, core or accounting system;
• it is not a payment gateway and does not custody money;
• it does not lend, buy portfolios or repair credit history;
• it performs preventive, administrative and pre-legal out-of-court management, but does not file lawsuits, seize assets or provide judicial representation;
• a technical rule helps comply with a policy but does not by itself guarantee legal compliance;
• integrations, volume and availability must be confirmed in the scope.

Acknowledging those boundaries does not weaken the product. It reduces the risk of buying an ambiguous promise.

Certeza vs Colektia

Colektia is the benchmark with the most demanding public evidence among the sources we reviewed. It publishes a three-month early-delinquency pilot with 12,000 accounts: 6,000 managed with AI and 6,000 through human agencies under conditions it describes as comparable. It reports 78% versus 75% containment, more than USD 25,000 additional and a 3.6x saving according to its own methodology. These are data published by the provider, not an independent audit.

That is more public evidence of scale and result than Certeza can present today. We should not hide it.

The question is whether that strength solves the same problem. Colektia is oriented to mass infrastructure and operation in banking, fintech, telco and retail. Certeza becomes more attractive when a Colombian organization needs to:

• start with a sample and imperfect accounting data;
• direct accompaniment from the team that implements;
• configuration by sector and type of obligation;
• granular reconciliation;
• review of receipts and exceptions;
• a contract where cost depends on attributable recovery.

Fit hypothesis: for enterprise scale and public evidence, Colektia starts ahead. For a Colombian company that wants a specialized, accompanied operation with fees potentially tied to results, Certeza deserves to be in the pilot. The decision must come from a comparable cohort.

Certeza vs Moonflow

Moonflow is a complete SaaS platform. It publishes reference B2B plans —at the time of review, Lite USD 79 monthly, Essential USD 399 and Pro USD 499, with lower values for annual billing—, plus assisted onboarding, Academy, support, channels, text and voice agents, portal, segmentation, payments, interfaces and indicators. It also documents that WhatsApp Business API, SMS, telephony and AI tokens can generate additional consumption. See the B2B detail and its communication-balance documentation.

Its strength is that the buyer understands the product better before talking to sales and can self-manage a sophisticated operation.

The underlying difference is not about features but about what the client is buying. A subscription SaaS model sells the right to use a tool: the client pays a recurring license —plus channel and token consumption— and runs the operation, so the cost accrues the same whether recovery is high or low. Certeza is offered, above all, as a managed collections service: it does not merely license the software, it operates the recovery and can align its remuneration to recovery, so its revenue depends on the result rather than on a fixed monthly fee. Under that logic the client is not buying platform “seats” but resolved and reconciled obligations.

That distinction should not be built by saying Moonflow "only sends reminders" or lacks accompaniment, because that would be false. It should be framed like this:

• Moonflow offers a product-led, self-service model, with onboarding and support per plan, whose cost is essentially a subscription independent of the result;
• Certeza combines platform, agents and accompanied execution as a service, and can tie its fees to recovery with contractual scope;
• Moonflow separates licenses and several consumptions that the client pays and administers;
• Certeza concentrates its design on obligation, exception and local reconciliation, whose advantage must be validated with the same cases;
• so the client must compare the full cost against the recovered result, not just the monthly fee or the commission in isolation.

Fit hypothesis: Moonflow is strong for teams that want control and SaaS self-service with accompaniment and prefer a predictable subscription cost. Certeza fits better when the company wants a collections partner whose remuneration moves with recovery, rather than a tool that costs the same whether or not there are results. The pilot must prove which division of labor —and which cost structure— produces the best total result.

Certeza vs Debitia

Debitia declares more than 15 years of experience, more than 200 organizations in 15 countries, workflows, portal, channels, agents, collectors, ERP and core integration and a mature operation.

It would not be serious to describe it as an elementary tool. Its advantage is in its work structure, supervision and track record.

Certeza can differentiate itself by:

• an architecture centered on decisions and states of the obligation;
• strict separation between conversation and durable writes;
• a specific rubric designed for Colombian naturalness;
• conservative reconciliation and a pause when there is ambiguity;
• close rollout and a result-based model.

Fit hypothesis: Debitia offers maturity and workflow control. Certeza deserves priority in the pilot when controlled conversational autonomy, Colombian operation and economic alignment matter. Without comparable results, we do not claim that one recovers more than the other. Debitia's software-selection guide lets you dig deeper into its own scope.

Certeza vs Intiza

Intiza has a solid position in B2B receivables, Customer Success, methodology and integrations via API, SFTP or files. It publishes cases with improvements in days past due and promise effectiveness: Parque Arauco reports a reduction from 90 to 55 days and a drop from 40% to 20% in portfolio over 30 days; Algorithm reports a reduction from 47 to 5 days in six months; and Magic reports 15% more promise effectiveness. These are cases published by the provider and not all use a contemporaneous control.

Its strength is helping the finance team organize the process and increase collector productivity.

Intiza's reviewed public documentation does not allow verifying the same level of conversational autonomy that Certeza designed around conversations, responses, next steps, promises, disputes and receipts. Intiza does publish AI, automation and reconciliation capabilities; the difference must be proven with identical cases, not inferred from a feature list. See its product and AI interview and the Algorithm case.

Fit hypothesis: Intiza is a mature alternative to organize B2B receivables. Certeza should be evaluated especially when the company wants specialized agents to take on operational work under rules and with conservative reconciliation.

Certeza vs Giitic

Giitic offers a Colombian suite of more than twenty modules, web and mobile apps, offline operation, routes, portal, payments, escalation to legal departments, customization and enterprise integrations. It names connectors such as SAP, Siigo, Helisa and World Office. Its collections plans also publish different limits for import, export, storage and email across packages, so its breadth must be compared on the plan actually quoted.

That breadth can be decisive for organizations with field collectors, routes, signatures, related modules and custom development.

Certeza's hypothesis is in specialization:

• fewer peripheral modules;
• an architecture concentrated on collections conversation;
• states and decisions per obligation;
• reconciliation and exception review;
• accompanied operation;
• cost tied to the result.

Fit hypothesis: Giitic can win when an extensive suite, mobility or enterprise customization is needed. Certeza deserves to be included when the priority is to test specialized agents and managed operation against a horizontal project.

Certeza vs PorCobrar

PorCobrar combines invoicing, receivables, payments, reminders and reconciliation. Its public information is clearly tied to the Mexican ecosystem: SAT, CFDI, RFC, SPEI, OXXO and gateways used in that market. On the reviewed WhatsApp pages we found mainly a flow to share links; we did not find enough evidence to classify it as a comparable autonomous agent. Its terms assign processing to third parties and publish, for certain card payments, a fee of 2.5% plus VAT. The described automatic reconciliation depends on the corresponding gateway flow.

That does not make PorCobrar a bad product. It makes it a product that must demonstrate localization before being recommended for Colombia.

Certeza offers a more direct contrast:

• Colombian company and operation;
• local rules, schedules and scenarios;
• conversational agents;
• follow-up per obligation;
• a specialized WorldOffice import flow and data routes for systems used in Colombia;
• reconciliation by property, third party, invoice, receipt or reference;
• explicit B2B and pre-legal out-of-court scope.

Fit hypothesis: for invoicing and collection within the Mexican ecosystem, PorCobrar can be appropriate. For a Colombian operation that needs specialized management, Certeza deserves priority on the shortlist.

The indicators that separate real collections from a pretty demo

The following indicators form the methodology proposed for the pilot; they are not an inventory of metrics already available in each platform. Certeza currently computes active portfolio, aging, recovery rate, payments, disputes, broken promises, actions per channel, phases and autopilot activity. Incremental recovery, cure/roll rates, effective contact, kept promises, reconciliation accuracy and cost per result require additional instrumentation or calculation.

Financial result

Gross collection does not prove causality. Attribution must be frozen before starting and count all payments from the originally assigned group, even if they arrived through another channel; otherwise it rewards tracking ability, not the effect. DSO and CEI are corporate context and also change with sales, terms, invoicing and seasonality.

Roll rates require cutoffs of equal duration, frozen buckets and a complete matrix of persistence, deterioration, improvement and cure, both by accounts and by balance.

Contactability and promises

• coverage with an authorized and technically valid channel;
• deliverability;
• response rate per unique person;
• contact with the correctly verified account holder;
• valid promises with amount, date and verifiable acceptance;
• Kept Promise Rate: matured promises kept within the predefined grace ÷ promises whose due date already passed;
• promise-to-cash conversion: associated reconciled value ÷ promised value already due;
• broken promises;
• agreements that remain on track at day 30, 60 and 90.

A WhatsApp sent is not effective contact. A promise that has not yet come due is not a kept promise.

Reconciliation and accounting truth

• percentage reconciled without intervention;
• matching accuracy and coverage;
• automatic payments later reversed;
• time between payment and correct application;
• age of unapplied money;
• accuracy of the communicated balance;
• people contacted who were already current;
• contacts after payment;
• receipts linked correctly;
• latency between ERP, bank, platform and channel.

This category usually reveals the difference between a flashy automation and a safe operation.

Experience and compliance

• complaints per 1,000 people contacted;
• confirmed complaints;
• resolution time;
• do-not-contact requests applied within the SLA;
• unauthorized channel;
• contact outside allowed hours;
• excessive frequency;
• disclosure to a third party;
• legal accuracy of the message;
• complete and exportable history.

Law 2300 of 2023 regulates channels, frequency and schedules in the covered relationships. Law 1581 of 2012 and Law 1266 of 2008 remain relevant for personal data and financial, credit, commercial and services information.

Cost and productivity

• full cost per peso recovered;
• cost per gross peso: full cost of the arm ÷ net recovery;
• incremental cost per incremental peso: cost difference ÷ recovery difference;
• incremental ROI: (recovery difference − cost difference) ÷ cost difference;
• cost per kept promise;
• human hours per 1,000 accounts;
• human interventions per resolved case;
• rollout time;
• time to the first verifiable result.

The full cost includes license, rollout, integrations, channels, models, voice, OCR, storage, support, staff, review and error correction. If there is no positive incremental recovery, a ratio that might look favorable must not be shown: the result is "no positive incremental recovery."

How to test whether an agent is really more natural

Don't ask the vendor whether its agent "sounds human." Give the same cases to all providers, hide the brands, randomize the order and repeat each scenario at least three times. Between 40 and 60 scenarios and three evaluators are a starting point, not a statistical guarantee: the sample must cover risks, sectors and types of obligation, and inter-rater agreement must be measured.

Score separately:

• task success;
• accuracy of balances, dates and amounts;
• unsupported claims;
• policy violations;
• Colombian naturalness;
• relevance and brevity;
• consistency across repetitions;
• latency;
• correct escalation;
• cost per successful case.

Naturalness without accuracy is dangerous: a wrong answer can sound very convincing.

Tokens: the comparison almost always done wrong

Tokens are a technical input, not a collections result. Furthermore:

• tokenizers change between models;
• some providers do not disclose model or consumption;
• cache, retries, tools, OCR and voice modify the cost;
• less context can reduce accuracy;
• a short answer may require several later attempts.

It is only valid to claim "Certeza consumed less" if you keep the same model, version, tokenizer, context, cases, tools and quality threshold.

For different models, compare:

1. AI cost per correctly resolved task;
2. total cost per matured kept promise;
3. technology cost per million pesos incrementally recovered;
4. the quality–cost frontier: how much you save before degrading accuracy, safety or experience.

We did not find a standardized token benchmark across the seven providers in the official sources reviewed and listed. Certeza can audit the per-turn consumption of its conversational agent, but will publish a quantitative advantage only after closing the end-to-end instrumentation and running a common benchmark.

The team behind the product is audited too

The word "geniuses" does not help a buyer reduce risk. These questions do:

• do the founders take part in implementations and incidents?
• who masters collections, payments, reconciliation, data and AI?
• who is responsible for Customer Success?
• how long does the team take to fix an error?
• what percentage of implementations reaches production?
• what part of the product is proprietary and what part is resold?
• what references can validate the quality of the accompaniment?

Certeza is a Colombian, bootstrapped company, founded by John Sebastián Urbano Lenis, Steven Ma Mei and Sebastián Arango Vergara, with a reported team of nine people. An internal audit of the development history found hundreds of traceable contributions from the founders in the platform. We do not use lines of code or commit counts as a measure of talent: those counts are distorted by migrations, generated files and branches. What they do allow verifying is that the founders build the product directly.

• John Sebastián Urbano Lenis leads the commercial and growth front, with technical involvement in infrastructure, deployments, contact automation and product. He was on the Icesi Telematics Engineering honor roll in 2020-2, with a 4.5 GPA, and his development footprint includes infrastructure as code, CI/CD, cloud and the first SMS and email flows.
• Steven Ma Mei is the main technical architect of the platform and its specialized agents. Icesi documents that he graduated as a systems engineer magna cum laude, researched cyber-threat analysis and took part in the Latin American Programming Marathon. At Certeza his work spans the portfolio engine, agents, promises, receipts, multichannel context, security and data model.
• Sebastián Arango Vergara leads integrations, reconciliation, financial automation and voice agents. Icesi documents that he graduated magna cum laude, spent three years in its Programming Club and qualified for South American regionals; in 2019 he earned an honorable mention at the International Mathematics Competition for University Students. At Certeza he has built, among other components, the specialized WorldOffice import, payment assignment, voice flows and Colombian amount pronunciation.

The engineering team that builds the collections core also includes three developers with traceable, sustained contribution in the backend. Their evidence is internal —the collections engine's development history—; we do not attribute academic credentials we could not verify publicly:

• A first backend developer is the most active contributor of this group in the collections core, with work concentrated on multichannel notifications, account and organization management, the customer portal and imports.
• A second developer works on account management, agents and notifications of the collections engine, with a focus on domain logic.
• A third developer contributes to notifications, account and organization management, with strong integration-test coverage.

Steven and Sebastián also competed together for Icesi in the 2019 Latin American programming regional. This background does not by itself prove that a strategy recovers debt. It does explain part of the discipline with which the team breaks down problems of states, constraints, evidence and exceptions.

The sentence Certeza must earn in every implementation is:

Proprietary collections platform and logic, integrated with specialized AI, cloud and communications providers, plus direct accompaniment from a team that implements, measures and is accountable for the contracted scope.

The pilot that should decide the purchase

1. Define size and freeze a cohort

Compute the size with the base rate, the minimum detectable effect, power, balance and the correlation between obligations of the same debtor. Segment by sector, balance, days past due, history, contactability and authorized channel. Exclude payments already initiated, litigation, defective data and cases that must not be contacted.

2. Assign treatment and control

Do random, stratified assignment by debtor, company, resident or household when possible. Never allow two arms to contact the same person. If you cannot randomize, create matched contemporaneous cohorts and declare the limitation. Measure by original assignment —intention to treat—, not just by contacted account, and adjust uncertainty for clustering.

3. Use the same conditions

Run the arms in parallel and keep portfolio, authorized discounts, payment means, available data, schedules, policy and window comparable. Each provider's contact strategy is part of the treatment. The duration must let promises and reversals mature and include follow-up; 60 to 90 days can be an operational reference, it does not replace the sample calculation or the real payment cycle.

4. Reconcile before declaring a winner

Cross payments, reversals and applications against the official source. Report accounts, balance, sample losses, intervals and errors. Do not declare a winner when the intervals materially overlap.

5. Audit the conversations

Run representative synthetic scenarios. A real sample can only be used with a legal basis, controller instructions, minimization, anonymization where applicable, a processing agreement and a secure environment. Remove provider logos and names. Use independent evaluators, a frozen rubric, random order, repetitions and consistency measurement.

6. Compute the full cost

Compare equivalent contractable plans and include software, operation, channels, AI, integrations, support and client hours. Decide by net incremental recovery and risk, not by messages.

So, which is the best debt collection software in Colombia?

There is no universal winner. There can be a winner for a well-defined problem.

• Choose Colektia if your priority is mass scale and you want to start from published enterprise cases.
• Choose Moonflow if you want a broad, self-service SaaS platform with visible pricing.
• Evaluate Debitia or Intiza if you value regional maturity and receivables management structure.
• Evaluate Giitic if you need a modular suite, mobility or custom development.
• Evaluate PorCobrar if you operate in the Mexican invoicing and payments ecosystem.
• Include Certeza among the first options in the pilot if you operate in Colombia and want specialized agents, accompanied execution, obligation-level control, reconciliation and a structure that can tie fees to recovery subject to evaluation and contract.

Certeza does not win because its name was written in first place. It wins if, on the same portfolio, it recovers more incremental money, reconciles it correctly, needs less total cost and does so with fewer errors, complaints and human effort.

That is the only number-one position worth buying.

Frequently asked questions

Is Certeza a software or a collections company?

It is a B2B platform and managed operation. It can organize obligations, coordinate contact, record responses and promises, reconcile payments and accompany exceptions within the contracted scope.

Does Certeza charge if it does not recover?

It can offer, subject to evaluation and contract, a structure with no initial fixed fee and fees on attributable recovery. It is not equivalent to free software: percentage, channel costs, taxes, portfolio, window, exclusions and reversals vary by contract.

What early result has Certeza observed?

The company reports that, in all fully implemented cases reviewed to date, it recovered at least 10% of the portfolio during the first two weeks after full go-live. It is an internal figure not yet audited, not a guarantee nor a measure of incremental recovery. Before turning it into a public case, sample, denominator, net payments, baseline and limitations will be documented.

Is Certeza a payment gateway?

No. It can facilitate the link or portal against the chosen gateway and reconcile references, but it does not process or custody money.

Does Certeza integrate with WorldOffice, Siigo, Alegra and Helisa?

There is a specialized, verifiable flow for importing WorldOffice charges and payments. For Siigo, Alegra and Helisa it can work with exports, files or evaluated connections; the productive scope must be confirmed before promising reading, writing or automatic synchronization.

Does Certeza perform judicial collection?

No. It performs preventive, administrative and pre-legal out-of-court collection. It does not file lawsuits, request seizures or provide judicial representation.

Do more channels produce more recovery?

Not necessarily. They can increase contactability, but also repetition, cost and complaints. They must share context, respect the rules and be measured by net result.

Does fewer tokens mean a more efficient agent?

Not by itself. The valid comparison considers quality, total cost and correctly resolved task. A cheap agent that gets it wrong or does not recover can be the most expensive.

How do I verify an agent's naturalness?

With identical scenarios, hidden marks, several repetitions and blind evaluators. Score naturalness separately from accuracy, legality, safety, latency and resolution.

Sources consulted

Providers

• Colektia
• Santander case published by Colektia
• Colektia policies and security
• Moonflow Colombia
• Moonflow B2B plans
• Moonflow Talk
• Moonflow communication balances and consumption
• Moonflow privacy
• Debitia Colombia
• Debitia selection guide
• Debitia terms
• Intiza
• Intiza Algorithm case
• Intiza product and AI interview
• Intiza privacy
• Giitic
• Giitic collections plans
• Giitic financial portfolio
• PorCobrar
• WhatsApp in PorCobrar
• PorCobrar terms
• Certeza
• Certeza security

Team

• Icesi rector's speech at the 2021-2 graduation
• Icesi 2020-2 honor roll
• Official IMC 2019 results
• 2019 Latin American programming regional results

Regulation and methodology

• SIC: comparative information and advertising
• Law 256 of 1996 on unfair competition
• Law 2300 of 2023
• Law 1581 of 2012
• Law 1266 of 2008
• NIST AI Risk Management Framework
• ITU-T P.852 for chatbot evaluation
• CFPB: settlement and cure definitions
• OCC: delinquency transition analysis
• SAP: DSO methodology
• Oracle: Collections Effectiveness Index

This content is informational and commercial. It does not constitute legal, accounting, financial or security advice. The application of the rules and the collections result depend on the type of obligation, data, sector, contract and operation.