pricing credit thousands names challenge next months build automated system provide differential pricing thousands credits 5 000 year end credits illiquid terms market price information making challenge harder end result important terms competitive pricing advantage need overall strategy plan achieve quantitative perspective currently several models credit pricing either use development fmc model default probability approach using bloomberg fair market par yield curves probabilities generated risky libor default bankruptcy swap prices computed using expectation methodology fmc model credit spread approach using fmcs directly taking libor credit spread tenor adjusting basis compounding differences bond model fmc approach taking fmcs benchmark curves model regresses input bonds specific name two best fitting benchmarks result zero yield curve shape fmcs level tweaked specific issuer prices generated using spread probability approaches testing bond model spline approach taking bonds specific issuer model fits exponential cubic spline zero coupon price curve builds zero yield curve testing market prices certain liquid names sectors ratings cds market prices used recovery event discount used get bankruptcy swap prices kmv using expected default frequencies edfs kmv model database build model price default swaps making appropriate risk adjustments kmv installed model worked next models returns price credit default bankruptcy accuracy price depends many factors liquidity regulatory differences bond cds markets recovery assumptions risk premia capital charges etc aim accurately price many liquid names possible based upon models use prices alongside financial information backbone full automated pricing system inputs proposed pricing system specific name model market prices issuers alongside name specific soft data credit reports financial statements credit liquid enough price generated information otherwise credit mapped onto subset liquid credits financial information historical price movements providing mapping weights model price periodically adjusted align market trader prices adjustment feed back weighting mapping composition loose terms could think system price illiquid credit weighted average liquid market prices bonds equities default swaps weightings calibrated using credit analysis financial ratios etc key steps implementing system establishing exactly want predict price rating probability score need clean market history calibrate really ratings need develop mapping rating score price getting cleaning historical financial credit data required calibrate model building mechanics model ie calibration methodology neural nets fuzzy logic seem obvious candidates exact methods software packages use determining automated methodology mapping names limited information model getting true market price order feed back error present price exists credits allocating resources development mckinsey claimed system would take 6 10 man months develop ideas comments requested need develop strategy asap model description fairly vague yet knowledge needed fill specific details help especially required continue move internet speed regards ben