Number reputation: a new operator asset few think about

A historical parallel

Once there was no credit bureau. Each bank making a loan ran its own check — called the neighbours, asked for guarantors, eyeballed the customer. Over time the industry agreed that a centralised history of payment behaviour makes the market more efficient. The bank issuing a loan checks the bureau, sees the history, takes an informed decision. A customer with good history gets better terms. A customer with bad history gets close attention.

A similar story is unfolding around phone numbers — only there is no credit-bureau equivalent yet.

Each number in Uzbekistan has history. When it was issued. To whom it was registered. How many times it changed owners. How often it was the subject of a SIM swap. What activity patterns it has — passive or active, regular payments or interrupted, use of bank and payment apps. Whether it has appeared on operator anti-scam lists.

This history is a real commercial asset. Each number has a “trust score” that could be expressed as a number. And that score interests a wide range of downstream partners.

Who could need number reputation

Banks. When the customer calls the bank’s contact centre with a request, the bank can check number reputation. The number is new, recently issued — additional verification. The number has existed for 5 years, is active, with regular payments in the banking app — standard procedure.

Payment services. At registration in a payment app, number reputation is the first risk signal. Suspicious patterns — refusal or additional verification.

E-commerce. When the customer places an order with cash-on-delivery, knowing reputation helps identify the risk of refusal or fraudulent delivery addresses.

Government. When a citizen contacts public services through their number, a reputation check helps identify abuse patterns.

Anti-scam systems. Coordination among operators on known scam numbers that switch SIMs to evade blocking.

Each of these has commercial potential. None requires the operator to share private customer information — only an aggregated reputation signal.

What can be built and what cannot

Buildable:

A trust score for the number. A composite score based on tenure, activity, behavioural patterns, anti-scam flags. Not “private data on the customer” — a composite signal.

An API for downstream partners. A bank sends the number, gets the trust score. A payment service does the same. A revenue line.

A shared anti-scam database. Coordination among operators on identified scam numbers. Requires regulatory support and a cooperative agreement, but potentially a meaningful security improvement for the country.

Not buildable:

Sharing private customer information without consent. What the customer uses, what they spend on, their patterns — that is private. Only an aggregated signal to an aggregated question.

Using reputation for discrimination. Reputation for verification — acceptable. Reputation as the basis for refusing service without human review — may infringe customer rights.

Making reputation commercial without regulatory clarity. A new class of data, and the regulator may have its own view on how to handle it.

Where this often gets stuck

Privacy and regulation are unclear. What counts as private is the question. The regulator may treat reputation as “personal data processing” with serious restrictions.

No cooperation among operators. Real value from a reputation database arrives when several operators commit to the shared base. Competing operators rarely agree.

Technically: master data on the number does not reconcile across systems. History of registrations, swaps, blocks may live in several operator systems without a consolidated view.

Pricing model. How much should the banking partner pay per reputation lookup? Too cheap — no revenue. Too expensive — the bank does not use it. Pricing discovery takes quarters.

Internal pushback. Marketing and sales dislike the idea that reputation may expose “quality” segments. If a meaningful share of the base is low reputation, that is a question to acquisition quality.

What a 24-month roadmap could look like

Months 1-6. Foundation. Consolidate number data into a single master view. Audit accuracy. An initial scoring algorithm.

Months 7-12. First product. Trust score API for one banking partner — pilot. Hybrid pricing model (subscription plus per-lookup). Initial measurement.

Months 13-18. Expansion. Additional partners. Anti-scam database — negotiations with other operators and the regulator.

Months 19-24. Sustainable. Multiple revenue streams. Anti-scam coordination established. Regulatory clarity.

By two years in the operator has a real new revenue line that grows. Not astronomical, but revenue that did not exist before, in a new niche.

What often goes wrong

Trust score without validation. A score is delivered without testing whether it correlates with real outcomes (fraud rate, default rate). Partners try, see no value, drop out.

Pricing too high upfront. The operator expects significant revenue from start, sets the price high, the partner declines. Alternative — start lower, prove value, then raise.

Anti-scam without cooperation among operators. One operator does not close scam — the fraudster moves to another. Cooperation is mandatory for effectiveness.

Regulatory backlash. Launching without regulator engagement — the regulator may impose restrictions retroactively and the investment resets.

Misalignment with own anti-fraud work. The reputation system has to be in sync with internal fraud detection. If they say different things — confusion and unworkability.

When not to do it

If master data on numbers and SIM is fragmented across systems and not consolidated, the reputation score is built on a flawed base.

If cooperation with other operators is unattainable, the anti-scam component does not work.

If the regulator has not settled on a framework, the risk-adjusted opportunity does not justify the investment.

If there are no partnerships with banks, the product has no buyer.

If the operator has its own fintech ambitions, the conflict of interest with reputation neutrality undermines positioning.

Discussion points for the committee

What is the current consolidated view of number data? Does a master view exist?

Who are potential partners for a reputation product? Are there warm relationships?

What regulatory framework is needed and what should be filed with the regulator?

Which 2-3 starter use cases are most realistic for a pilot?

What 18-24 month investment commitment is needed?

How SamaraliSoft can help

Number Reputation Strategy & Build — analysis of the feasibility of number reputation as a product line, design of a composite scoring methodology, regulatory engagement framework, pricing strategy, and a pilot with one banking partner over 12-18 months. Including the anti-scam component with cooperation negotiations.

Related reading

• /en/insights/telecom-sim-swap-banking-fraud/ — SIM swap and banking fraud
• /en/solutions/telecom-trust-platform-cornerstone/ — trust platform in detail
• /en/insights/telecom-youth-segments-payments/ — biometrics and UX
• /en/insights/telecom-growth-after-connectivity/ — growth beyond connectivity

Sources

• Central Bank of Uzbekistan — biometric verification for digital banking
• Ministry of Digital Technologies — telecom infrastructure
• Digital Government Portal — digital infrastructure UZ
• UzDaily — telecom market
• MNP.UZ — number portability