Rewards that reach the right people

The risk

Where reward programs lose money

Rewards are attractive to misuse because they are close to cash. The common patterns are familiar: the same claim made twice, rewards redeemed far faster than normal activity would allow, and accounts set up only to collect rewards.

Cash rewards raise the stakes. A payout to the wrong UPI ID or bank account is hard to recover, so verification has to happen before money moves.

Reward Max combines two layers: identity — knowing who each recipient is — and behaviour — spotting activity that doesn't fit.

Two layers

Identity and behaviour checks

Built into every reward.

Best practice

Balancing protection and speed

Verify once, early. KYC at enrolment means checks don't slow down every reward later.

Review flags regularly. A short daily or weekly review of flagged activity keeps genuine members moving and stops misuse before it grows.

Use the reports. Fraud metrics alongside redemption data show finance and audit that controls are working.

• KYC at enrolment
• Regular review of flags
• Fraud metrics in reports
• Verified accounts for every cash payout

Setting it up

Designing fraud controls for a rewards program

Good fraud controls are layered. Identity checks at enrolment — Aadhaar eKYC, PAN verification and bank account validation — stop fake accounts before they can redeem. Automated checks on every redemption catch what gets through: duplicate claims, suspicious redemptions and velocity abuse.

Decide in advance what happens when something is flagged: who reviews it, how quickly, and how the member is told. A clear process protects the budget without leaving honest members waiting.

Tie the payout account to the verified identity. When cash rewards go only to validated bank accounts and UPI IDs in the member's name, it is much harder for rewards to be diverted.

• Verify identity before the first redemption
• Check every redemption automatically
• Agree a review process for flagged cases
• Pay cash only to validated accounts

Reviewing it

Learning from flagged activity

Fraud patterns change as programs grow. Review flagged cases regularly, look for repeat patterns by region, scheme or reward type, and tighten rules where the same issue keeps appearing.

Use fraud metrics in Reward Max dashboards alongside redemption and scheme ROI, so finance and program teams look at the same numbers. Audit support and compliance reporting give you a record of what was flagged and how it was resolved.

Knoxy, the AI Chief of Staff in IMAST 360, detects fraud and anomalies across loyalty, rewards and orders and alerts the right people, so patterns that span products don't go unnoticed.